mirror of
https://github.com/msberends/AMR.git
synced 2026-09-22 12:20:52 +02:00
Compare commits
1
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 github-actions[bot]
|
8e522cd988 |
@@ -1,37 +0,0 @@
|
||||
^.*\.RData$
|
||||
^.*\.Rproj$
|
||||
^\.Renviron$
|
||||
^\.Rprofile$
|
||||
^\.Rproj\.user$
|
||||
^\.travis\.yml$
|
||||
^\.zenodo\.json$
|
||||
^_noinclude$
|
||||
^_pkgdown\.yml$
|
||||
^appveyor\.yml$
|
||||
^codecov\.yml$
|
||||
^cran-comments\.md$
|
||||
^CRAN-RELEASE$
|
||||
^\.github$
|
||||
^doc$
|
||||
^docs$
|
||||
^git_.*\.sh$
|
||||
^index\.md$
|
||||
^installed_deps$
|
||||
^Meta$
|
||||
^pkgdown$
|
||||
^public$
|
||||
^data-raw$
|
||||
^\.lintr$
|
||||
^tests/testthat/_snaps$
|
||||
^vignettes/AMR\.Rmd$
|
||||
^vignettes/benchmarks\.Rmd$
|
||||
^vignettes/*\.not$
|
||||
^vignettes/datasets\.Rmd$
|
||||
^vignettes/EUCAST\.Rmd$
|
||||
^vignettes/MDR\.Rmd$
|
||||
^vignettes/PCA\.Rmd$
|
||||
^vignettes/resistance_predict\.Rmd$
|
||||
^vignettes/SPSS\.Rmd$
|
||||
^vignettes/WHONET\.Rmd$
|
||||
^logo.svg$
|
||||
^CRAN-SUBMISSION$
|
||||
@@ -1,71 +0,0 @@
|
||||
#!/bin/sh
|
||||
|
||||
echo "Running pre-commit hook..."
|
||||
|
||||
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
|
||||
echo ">> Updating R documentation..."
|
||||
if command -v Rscript > /dev/null; then
|
||||
if "$(Rscript -e 'cat(all(c('"'roxygen2'"', '"'pkgload'"') %in% rownames(installed.packages())))')" == "TRUE"; then
|
||||
Rscript -e "suppressMessages(roxygen2::roxygenise())"
|
||||
currentpkg=`Rscript -e "cat(pkgload::pkg_name())"`
|
||||
git add man/*
|
||||
echo ">> done."
|
||||
else
|
||||
echo ">> R packages 'roxygen2' and 'pkgload' are not installed!"
|
||||
currentpkg="your"
|
||||
fi
|
||||
else
|
||||
echo ">> R is not available on your system!"
|
||||
currentpkg="your"
|
||||
fi
|
||||
echo ">> "
|
||||
|
||||
|
||||
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
|
||||
echo ">> Updating semantic versioning and date..."
|
||||
|
||||
# get tags from remote, and remove tags not on remote:
|
||||
git fetch origin --prune --prune-tags --quiet
|
||||
currenttagfull=`git describe --tags --abbrev=0`
|
||||
currenttag=`git describe --tags --abbrev=0 | sed 's/v//'`
|
||||
if [ "$currenttag" = "" ]; then
|
||||
# there is no tag, so set tag to 0.0.1 and commit index to current count
|
||||
echo ">> - no git tags found, create some using v(x).(y).(z)"
|
||||
currenttag="0.0.1"
|
||||
currentcommit=`git rev-list --count HEAD`
|
||||
else
|
||||
# there is a tag, so base version number on that
|
||||
currentcommit=`git rev-list --count ${currenttagfull}..HEAD`
|
||||
if (( "$currentcommit" == 0 )); then
|
||||
# tag is new, so this must become the version number
|
||||
currentversion="$currenttag"
|
||||
fi
|
||||
echo ">> - latest tag is '${currenttagfull}', with ${currentcommit} previous commits"
|
||||
fi
|
||||
if [ "$currentversion" = "" ]; then
|
||||
# combine tag (e.g. 1.2.3) and commit number (like 5) increased by 9000 to indicate beta version
|
||||
currentversion="$currenttag.$((currentcommit + 9001))" # results in e.g. 1.2.3.9005
|
||||
fi
|
||||
echo ">> - ${currentpkg} pkg version set to ${currentversion}"
|
||||
|
||||
# set version number and date to DESCRIPTION file
|
||||
sed -i -- "s/^Version: .*/Version: ${currentversion}/" DESCRIPTION
|
||||
sed -i -- "s/^Date: .*/Date: $(date '+%Y-%m-%d')/" DESCRIPTION
|
||||
echo ">> - updated DESCRIPTION"
|
||||
# remove leftover on macOS
|
||||
rm -f DESCRIPTION--
|
||||
# add to commit
|
||||
git add DESCRIPTION
|
||||
|
||||
# set version number to NEWS file
|
||||
if [ -e "NEWS.md" ]; then
|
||||
sed -i -- "1s/.*/# ${currentpkg} ${currentversion}/" NEWS.md
|
||||
echo ">> - updated NEWS.md"
|
||||
# remove leftover on macOS
|
||||
rm -f NEWS.md--
|
||||
# add to commit
|
||||
git add NEWS.md
|
||||
else
|
||||
echo ">> - no NEWS.md found!"
|
||||
fi
|
||||
echo ">> "
|
||||
@@ -1,149 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
on:
|
||||
push:
|
||||
# run after a git push on any branch in this repo
|
||||
branches: '**'
|
||||
schedule:
|
||||
# run a schedule everyday at 1 AM.
|
||||
# this is to check that all dependencies are still available (see R/zzz.R)
|
||||
- cron: '0 1 * * *'
|
||||
|
||||
name: R-code-check
|
||||
|
||||
jobs:
|
||||
R-code-check:
|
||||
runs-on: ${{ matrix.config.os }}
|
||||
|
||||
continue-on-error: ${{ matrix.config.allowfail }}
|
||||
|
||||
name: ${{ matrix.config.os }} (R-${{ matrix.config.r }})
|
||||
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
config:
|
||||
# test all systems against all released versions of R >= 3.0, we support them all!
|
||||
- {os: macOS-latest, r: 'devel', allowfail: true}
|
||||
- {os: macOS-latest, r: '4.1', allowfail: false}
|
||||
- {os: macOS-latest, r: '4.0', allowfail: false}
|
||||
- {os: macOS-latest, r: '3.6', allowfail: false}
|
||||
- {os: ubuntu-22.04, r: 'devel', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
|
||||
- {os: ubuntu-22.04, r: '4.2', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
|
||||
- {os: ubuntu-22.04, r: '4.1', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
|
||||
- {os: ubuntu-22.04, r: '4.0', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
|
||||
- {os: ubuntu-22.04, r: '3.6', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
|
||||
- {os: ubuntu-22.04, r: '3.5', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
|
||||
- {os: ubuntu-22.04, r: '3.4', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
|
||||
- {os: ubuntu-22.04, r: '3.3', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
|
||||
- {os: ubuntu-22.04, r: '3.2', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
|
||||
- {os: ubuntu-22.04, r: '3.1', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
|
||||
- {os: ubuntu-22.04, r: '3.0', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
|
||||
- {os: windows-latest, r: 'devel', allowfail: true}
|
||||
- {os: windows-latest, r: '4.1', allowfail: false}
|
||||
- {os: windows-latest, r: '4.0', allowfail: false}
|
||||
- {os: windows-latest, r: '3.6', allowfail: false}
|
||||
env:
|
||||
R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
|
||||
RSPM: ${{ matrix.config.rspm }}
|
||||
R_REPOSITORIES: "https://cran.rstudio.com"
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
|
||||
- uses: r-lib/actions/setup-r@v2
|
||||
with:
|
||||
r-version: ${{ matrix.config.r }}
|
||||
|
||||
- uses: r-lib/actions/setup-pandoc@v2
|
||||
|
||||
- name: Install Linux dependencies
|
||||
if: runner.os == 'Linux'
|
||||
# update the below with sysreqs::sysreqs("DESCRIPTION") and check the "DEB" entries (for Ubuntu).
|
||||
# we don't want to depend on the sysreqs pkg here, as it requires quite a recent R version
|
||||
# as of May 2021: https://sysreqs.r-hub.io/pkg/AMR,R,cleaner,curl,dplyr,ggplot2,knitr,microbenchmark,pillar,readxl,rmarkdown,rstudioapi,rvest,skimr,tidyr,tinytest,xml2,backports,crayon,rlang,vctrs,evaluate,highr,markdown,stringr,yaml,xfun,cli,ellipsis,fansi,lifecycle,utf8,glue,mime,magrittr,stringi,generics,R6,tibble,tidyselect,pkgconfig,purrr,digest,gtable,isoband,MASS,mgcv,scales,withr,nlme,Matrix,farver,labeling,munsell,RColorBrewer,viridisLite,lattice,colorspace,gridtext,Rcpp,RCurl,png,jpeg,bitops,cellranger,progress,rematch,hms,prettyunits,htmltools,jsonlite,tinytex,base64enc,httr,selectr,openssl,askpass,sys,repr,cpp11
|
||||
run: |
|
||||
sudo apt install -y libssl-dev libxml2-dev libcurl4-openssl-dev
|
||||
|
||||
- name: Restore cached R packages
|
||||
# this step will add the step 'Post Restore cached R packages' on a succesful run
|
||||
uses: actions/cache@v2
|
||||
with:
|
||||
path: ${{ env.R_LIBS_USER }}
|
||||
key: ${{ matrix.config.os }}-r-${{ matrix.config.r }}-v4
|
||||
|
||||
- name: Unpack AMR and install R dependencies
|
||||
if: always()
|
||||
run: |
|
||||
tar -xf data-raw/AMR_latest.tar.gz
|
||||
Rscript -e "source('data-raw/_install_deps.R')"
|
||||
shell: bash
|
||||
|
||||
- name: Show session info
|
||||
if: always()
|
||||
run: |
|
||||
options(width = 100)
|
||||
utils::sessionInfo()
|
||||
as.data.frame(utils::installed.packages())[, "Version", drop = FALSE]
|
||||
shell: Rscript {0}
|
||||
|
||||
- name: Remove vignettes on R without knitr support
|
||||
if: matrix.config.r == '3.0' || matrix.config.r == '3.1' || matrix.config.r == '3.2'
|
||||
# writing to DESCRIPTION2 and then moving to DESCRIPTION is required for R < 3.3 as writeLines() cannot overwrite
|
||||
run: |
|
||||
rm -rf AMR/vignettes
|
||||
Rscript -e "writeLines(readLines('AMR/DESCRIPTION')[!grepl('VignetteBuilder', readLines('AMR/DESCRIPTION'))], 'AMR/DESCRIPTION2')"
|
||||
rm AMR/DESCRIPTION
|
||||
mv AMR/DESCRIPTION2 AMR/DESCRIPTION
|
||||
shell: bash
|
||||
|
||||
- name: Run R CMD check
|
||||
if: always()
|
||||
env:
|
||||
_R_CHECK_CRAN_INCOMING_: false
|
||||
_R_CHECK_FORCE_SUGGESTS_: false
|
||||
_R_CHECK_DEPENDS_ONLY_: true
|
||||
_R_CHECK_LENGTH_1_CONDITION_: verbose
|
||||
_R_CHECK_LENGTH_1_LOGIC2_: verbose
|
||||
# during 'R CMD check', R_LIBS_USER will be overwritten, so:
|
||||
R_LIBS_USER_GH_ACTIONS: ${{ env.R_LIBS_USER }}
|
||||
R_RUN_TINYTEST: true
|
||||
run: |
|
||||
R CMD check --no-manual --run-donttest --run-dontrun AMR
|
||||
shell: bash
|
||||
|
||||
- name: Show unit tests output
|
||||
if: always()
|
||||
run: |
|
||||
find . -name 'tinytest.Rout*' -exec cat '{}' \; || true
|
||||
shell: bash
|
||||
|
||||
- name: Upload artifacts
|
||||
if: always()
|
||||
uses: actions/upload-artifact@v2
|
||||
with:
|
||||
name: artifacts-${{ matrix.config.os }}-r${{ matrix.config.r }}
|
||||
path: AMR.Rcheck
|
||||
@@ -1,89 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- development
|
||||
- main
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
|
||||
name: code-coverage
|
||||
|
||||
jobs:
|
||||
code-coverage:
|
||||
runs-on: macOS-latest
|
||||
env:
|
||||
GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
|
||||
- uses: r-lib/actions/setup-r@v2
|
||||
with:
|
||||
r-version: release
|
||||
|
||||
- uses: r-lib/actions/setup-pandoc@v2
|
||||
# with:
|
||||
# pandoc-version: '2.7.3' # The pandoc version to download (if necessary) and use.
|
||||
|
||||
- name: Query dependencies
|
||||
# this will change once a week, so it will cache dependency updates
|
||||
run: |
|
||||
writeLines(paste(format(Sys.Date(), "week %V %Y"), sprintf("R-%i.%i", getRversion()$major, getRversion()$minor)), ".github/week-R-version")
|
||||
shell: Rscript {0}
|
||||
|
||||
- name: Restore cached R packages
|
||||
# this step will add the step 'Post Restore cached R packages' on a succesful run
|
||||
uses: actions/cache@v2
|
||||
with:
|
||||
path: ${{ env.R_LIBS_USER }}
|
||||
key: ${{ matrix.config.os }}-${{ hashFiles('.github/week-R-version') }}-v4
|
||||
|
||||
- name: Unpack AMR and install R dependencies
|
||||
run: |
|
||||
tar -xf data-raw/AMR_latest.tar.gz
|
||||
Rscript -e "source('data-raw/_install_deps.R')"
|
||||
shell: bash
|
||||
|
||||
- name: Show session info
|
||||
run: |
|
||||
options(width = 100)
|
||||
utils::sessionInfo()
|
||||
as.data.frame(utils::installed.packages())[, "Version", drop = FALSE]
|
||||
shell: Rscript {0}
|
||||
|
||||
- name: Test coverage
|
||||
env:
|
||||
CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
|
||||
R_RUN_TINYTEST: true
|
||||
run: |
|
||||
install.packages("covr", repos = "https://cran.rstudio.com/")
|
||||
library(AMR)
|
||||
library(tinytest)
|
||||
x <- covr::codecov(line_exclusions = list("R/atc_online.R", "R/mo_source.R", "R/translate.R", "R/resistance_predict.R", "R/aa_helper_functions.R", "R/aa_helper_pm_functions.R", "R/zzz.R"))
|
||||
print(x)
|
||||
shell: Rscript {0}
|
||||
@@ -1,70 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation.
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- development
|
||||
- main
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
|
||||
name: lintr
|
||||
|
||||
jobs:
|
||||
lintr:
|
||||
runs-on: macOS-latest
|
||||
env:
|
||||
GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
|
||||
- uses: r-lib/actions/setup-r@v2
|
||||
|
||||
- name: Query dependencies
|
||||
run: |
|
||||
install.packages('remotes')
|
||||
saveRDS(remotes::dev_package_deps(dependencies = TRUE), ".github/depends.Rds", version = 2)
|
||||
writeLines(sprintf("R-%i.%i", getRversion()$major, getRversion()$minor), ".github/R-version")
|
||||
shell: Rscript {0}
|
||||
|
||||
- name: Cache R packages
|
||||
uses: actions/cache@v2
|
||||
with:
|
||||
path: ${{ env.R_LIBS_USER }}
|
||||
key: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-${{ hashFiles('.github/depends.Rds') }}
|
||||
restore-keys: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
install.packages(c("remotes"))
|
||||
remotes::install_deps(dependencies = TRUE)
|
||||
remotes::install_cran("lintr")
|
||||
shell: Rscript {0}
|
||||
|
||||
- name: Lint
|
||||
run: lintr::lint_package(linters = lintr::with_defaults(line_length_linter = NULL, trailing_whitespace_linter = NULL, object_name_linter = NULL, cyclocomp_linter = NULL, object_length_linter = lintr::object_length_linter(length = 50L)), exclusions = list("R/aa_helper_pm_functions.R"))
|
||||
shell: Rscript {0}
|
||||
@@ -1,60 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
# Create a website from the R documentation using pkgdown
|
||||
# Git commit and push to the 'gh-pages' branch
|
||||
|
||||
on:
|
||||
push:
|
||||
# only on main
|
||||
branches: 'main'
|
||||
|
||||
name: Update website
|
||||
|
||||
jobs:
|
||||
update-website:
|
||||
runs-on: ubuntu-latest
|
||||
continue-on-error: true
|
||||
steps:
|
||||
# Set up R (current stable version) and developer tools
|
||||
- uses: actions/checkout@v3
|
||||
- uses: r-lib/actions/setup-pandoc@v2
|
||||
- name: Set up R
|
||||
uses: r-lib/actions/setup-r@v2
|
||||
with:
|
||||
r-version: "release"
|
||||
# use RStudio Package Manager (RSPM) to quickly install packages
|
||||
use-public-rspm: true
|
||||
- name: Set up R dependencies
|
||||
uses: r-lib/actions/setup-r-dependencies@v2
|
||||
with:
|
||||
extra-packages: any::pkgdown
|
||||
|
||||
# Send updates to repo using GH Actions bot
|
||||
- name: Create website in separate branch
|
||||
run: |
|
||||
git config user.name "github-actions"
|
||||
git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
|
||||
Rscript -e 'pkgdown::deploy_to_branch(new_process = FALSE, clean = TRUE, install = TRUE, branch = "gh-pages")'
|
||||
-29
@@ -1,29 +0,0 @@
|
||||
Meta
|
||||
doc
|
||||
.Renviron
|
||||
.Rproj.user
|
||||
.Rhistory
|
||||
.RData
|
||||
.Ruserdata
|
||||
AMR.Rproj
|
||||
tests/testthat/Rplots.pdf
|
||||
inst/doc
|
||||
/src/*.o
|
||||
/src/*.o-*
|
||||
/src/*.d
|
||||
/src/*.so
|
||||
_noinclude
|
||||
*.dll
|
||||
vignettes/*.R
|
||||
.DS_Store
|
||||
.Rprofile
|
||||
^CRAN-RELEASE$
|
||||
packrat/lib*/
|
||||
packrat/src/
|
||||
data-raw/taxa.txt
|
||||
data-raw/taxon.tab
|
||||
data-raw/DSMZ_bactnames.xlsx
|
||||
data-raw/country_analysis_url_token.R
|
||||
data-raw/country_analysis2.R
|
||||
data-raw/taxonomy.csv
|
||||
data-raw/WHONET
|
||||
@@ -0,0 +1,254 @@
|
||||
Metadata-Version: 2.4
|
||||
Name: AMR
|
||||
Version: 3.0.1.9091
|
||||
Summary: A Python wrapper for the AMR R package
|
||||
Home-page: https://github.com/msberends/AMR
|
||||
Author: Matthijs Berends
|
||||
Author-email: m.s.berends@umcg.nl
|
||||
License: GPL 2
|
||||
Project-URL: Bug Tracker, https://github.com/msberends/AMR/issues
|
||||
Classifier: Programming Language :: Python :: 3
|
||||
Classifier: Operating System :: OS Independent
|
||||
Requires-Python: >=3.6
|
||||
Description-Content-Type: text/markdown
|
||||
Requires-Dist: rpy2
|
||||
Requires-Dist: numpy
|
||||
Requires-Dist: pandas
|
||||
Dynamic: author
|
||||
Dynamic: author-email
|
||||
Dynamic: classifier
|
||||
Dynamic: description
|
||||
Dynamic: description-content-type
|
||||
Dynamic: home-page
|
||||
Dynamic: license
|
||||
Dynamic: project-url
|
||||
Dynamic: requires-dist
|
||||
Dynamic: requires-python
|
||||
Dynamic: summary
|
||||
|
||||
|
||||
The `AMR` package for R is a powerful tool for antimicrobial resistance (AMR) analysis. It provides extensive features for handling microbial and antimicrobial data. However, for those who work primarily in Python, we now have a more intuitive option available: the [`AMR` Python package](https://pypi.org/project/AMR/).
|
||||
|
||||
This Python package is a wrapper around the `AMR` R package. It uses the `rpy2` package internally. Despite the need to have R installed, Python users can now easily work with AMR data directly through Python code.
|
||||
|
||||
# Prerequisites
|
||||
|
||||
This package was only tested with a [virtual environment (venv)](https://docs.python.org/3/library/venv.html). You can set up such an environment by running:
|
||||
|
||||
```python
|
||||
# linux and macOS:
|
||||
python -m venv /path/to/new/virtual/environment
|
||||
|
||||
# Windows:
|
||||
python -m venv C:\path\to\new\virtual\environment
|
||||
```
|
||||
|
||||
Then you can [activate the environment](https://docs.python.org/3/library/venv.html#how-venvs-work), after which the venv is ready to work with.
|
||||
|
||||
# Install AMR
|
||||
|
||||
1. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
|
||||
|
||||
```bash
|
||||
pip install AMR
|
||||
```
|
||||
|
||||
2. Make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
|
||||
|
||||
For Linux:
|
||||
|
||||
```bash
|
||||
# Ubuntu / Debian
|
||||
sudo apt install r-base
|
||||
# Fedora:
|
||||
sudo dnf install R
|
||||
# CentOS/RHEL
|
||||
sudo yum install R
|
||||
```
|
||||
|
||||
For macOS (using [Homebrew](https://brew.sh)):
|
||||
|
||||
```bash
|
||||
brew install r
|
||||
```
|
||||
|
||||
For Windows, visit the [CRAN download page](https://cran.r-project.org) to download and install R.
|
||||
|
||||
# Examples of Usage
|
||||
|
||||
## Cleaning Taxonomy
|
||||
|
||||
Here’s an example that demonstrates how to clean microorganism and drug names using the `AMR` Python package:
|
||||
|
||||
```python
|
||||
import pandas as pd
|
||||
import AMR
|
||||
|
||||
# Sample data
|
||||
data = {
|
||||
"MOs": ['E. coli', 'ESCCOL', 'esco', 'Esche coli'],
|
||||
"Drug": ['Cipro', 'CIP', 'J01MA02', 'Ciproxin']
|
||||
}
|
||||
df = pd.DataFrame(data)
|
||||
|
||||
# Use AMR functions to clean microorganism and drug names
|
||||
df['MO_clean'] = AMR.mo_name(df['MOs'])
|
||||
df['Drug_clean'] = AMR.ab_name(df['Drug'])
|
||||
|
||||
# Display the results
|
||||
print(df)
|
||||
```
|
||||
|
||||
| MOs | Drug | MO_clean | Drug_clean |
|
||||
|-------------|-----------|--------------------|---------------|
|
||||
| E. coli | Cipro | Escherichia coli | Ciprofloxacin |
|
||||
| ESCCOL | CIP | Escherichia coli | Ciprofloxacin |
|
||||
| esco | J01MA02 | Escherichia coli | Ciprofloxacin |
|
||||
| Esche coli | Ciproxin | Escherichia coli | Ciprofloxacin |
|
||||
|
||||
### Explanation
|
||||
|
||||
* **mo_name:** This function standardises microorganism names. Here, different variations of *Escherichia coli* (such as "E. coli", "ESCCOL", "esco", and "Esche coli") are all converted into the correct, standardised form, "Escherichia coli".
|
||||
|
||||
* **ab_name**: Similarly, this function standardises antimicrobial names. The different representations of ciprofloxacin (e.g., "Cipro", "CIP", "J01MA02", and "Ciproxin") are all converted to the standard name, "Ciprofloxacin".
|
||||
|
||||
## Calculating AMR
|
||||
|
||||
```python
|
||||
import AMR
|
||||
import pandas as pd
|
||||
|
||||
df = AMR.example_isolates
|
||||
result = AMR.resistance(df["AMX"])
|
||||
print(result)
|
||||
```
|
||||
|
||||
```
|
||||
[0.59555556]
|
||||
```
|
||||
|
||||
## Generating Antibiograms
|
||||
|
||||
One of the core functions of the `AMR` package is generating an antibiogram, a table that summarises the antimicrobial susceptibility of bacterial isolates. Here’s how you can generate an antibiogram from Python:
|
||||
|
||||
```python
|
||||
result2a = AMR.antibiogram(df[["mo", "AMX", "CIP", "TZP"]])
|
||||
print(result2a)
|
||||
```
|
||||
|
||||
| Pathogen | Amoxicillin | Ciprofloxacin | Piperacillin/tazobactam |
|
||||
|-----------------|-----------------|-----------------|--------------------------|
|
||||
| CoNS | 7% (10/142) | 73% (183/252) | 30% (10/33) |
|
||||
| E. coli | 50% (196/392) | 88% (399/456) | 94% (393/416) |
|
||||
| K. pneumoniae | 0% (0/58) | 96% (53/55) | 89% (47/53) |
|
||||
| P. aeruginosa | 0% (0/30) | 100% (30/30) | None |
|
||||
| P. mirabilis | None | 94% (34/36) | None |
|
||||
| S. aureus | 6% (8/131) | 90% (171/191) | None |
|
||||
| S. epidermidis | 1% (1/91) | 64% (87/136) | None |
|
||||
| S. hominis | None | 80% (56/70) | None |
|
||||
| S. pneumoniae | 100% (112/112) | None | 100% (112/112) |
|
||||
|
||||
|
||||
```python
|
||||
result2b = AMR.antibiogram(df[["mo", "AMX", "CIP", "TZP"]], mo_transform = "gramstain")
|
||||
print(result2b)
|
||||
```
|
||||
|
||||
| Pathogen | Amoxicillin | Ciprofloxacin | Piperacillin/tazobactam |
|
||||
|----------------|-----------------|------------------|--------------------------|
|
||||
| Gram-negative | 36% (226/631) | 91% (621/684) | 88% (565/641) |
|
||||
| Gram-positive | 43% (305/703) | 77% (560/724) | 86% (296/345) |
|
||||
|
||||
|
||||
In this example, we generate an antibiogram by selecting various antibiotics.
|
||||
|
||||
## Taxonomic Data Sets Now in Python!
|
||||
|
||||
As a Python user, you might like that the most important data sets of the `AMR` R package, `microorganisms`, `antimicrobials`, `clinical_breakpoints`, and `example_isolates`, are now available as regular Python data frames:
|
||||
|
||||
```python
|
||||
AMR.microorganisms
|
||||
```
|
||||
|
||||
| mo | fullname | status | kingdom | gbif | gbif_parent | gbif_renamed_to | prevalence |
|
||||
|--------------|------------------------------------|----------|----------|-----------|-------------|-----------------|------------|
|
||||
| B_GRAMN | (unknown Gram-negatives) | unknown | Bacteria | None | None | None | 2.0 |
|
||||
| B_GRAMP | (unknown Gram-positives) | unknown | Bacteria | None | None | None | 2.0 |
|
||||
| B_ANAER-NEG | (unknown anaerobic Gram-negatives) | unknown | Bacteria | None | None | None | 2.0 |
|
||||
| B_ANAER-POS | (unknown anaerobic Gram-positives) | unknown | Bacteria | None | None | None | 2.0 |
|
||||
| B_ANAER | (unknown anaerobic bacteria) | unknown | Bacteria | None | None | None | 2.0 |
|
||||
| ... | ... | ... | ... | ... | ... | ... | ... |
|
||||
| B_ZYMMN_POMC | Zymomonas pomaceae | accepted | Bacteria | 10744418 | 3221412 | None | 2.0 |
|
||||
| B_ZYMPH | Zymophilus | synonym | Bacteria | None | 9475166 | None | 2.0 |
|
||||
| B_ZYMPH_PCVR | Zymophilus paucivorans | synonym | Bacteria | None | None | None | 2.0 |
|
||||
| B_ZYMPH_RFFN | Zymophilus raffinosivorans | synonym | Bacteria | None | None | None | 2.0 |
|
||||
| F_ZYZYG | Zyzygomyces | unknown | Fungi | None | 7581 | None | 2.0 |
|
||||
|
||||
```python
|
||||
AMR.antimicrobials
|
||||
```
|
||||
|
||||
| ab | cid | name | group | oral_ddd | oral_units | iv_ddd | iv_units |
|
||||
|-----|-------------|----------------------|----------------------------|----------|------------|--------|----------|
|
||||
| AMA | 4649.0 | 4-aminosalicylic acid| Antimycobacterials | 12.00 | g | NaN | None |
|
||||
| ACM | 6450012.0 | Acetylmidecamycin | Macrolides/lincosamides | NaN | None | NaN | None |
|
||||
| ASP | 49787020.0 | Acetylspiramycin | Macrolides/lincosamides | NaN | None | NaN | None |
|
||||
| ALS | 8954.0 | Aldesulfone sodium | Other antibacterials | 0.33 | g | NaN | None |
|
||||
| AMK | 37768.0 | Amikacin | Aminoglycosides | NaN | None | 1.0 | g |
|
||||
| ... | ... | ... | ... | ... | ... | ... | ... |
|
||||
| VIR | 11979535.0 | Virginiamycine | Other antibacterials | NaN | None | NaN | None |
|
||||
| VOR | 71616.0 | Voriconazole | Antifungals/antimycotics | 0.40 | g | 0.4 | g |
|
||||
| XBR | 72144.0 | Xibornol | Other antibacterials | NaN | None | NaN | None |
|
||||
| ZID | 77846445.0 | Zidebactam | Other antibacterials | NaN | None | NaN | None |
|
||||
| ZFD | NaN | Zoliflodacin | None | NaN | None | NaN | None |
|
||||
|
||||
|
||||
# Installation Channels
|
||||
|
||||
## Stable Release (CRAN)
|
||||
|
||||
The default `AMR` Python package uses the latest stable version of the `AMR` R package, published on CRAN. After running `pip install AMR`, import it as usual:
|
||||
|
||||
```python
|
||||
import AMR
|
||||
|
||||
AMR.example_isolates
|
||||
```
|
||||
|
||||
## Development Version (GitHub)
|
||||
|
||||
To use the latest development version of the `AMR` R package (sourced directly from GitHub), import the `beta` sub-package and alias it as `AMR`:
|
||||
|
||||
```python
|
||||
import AMR.beta as AMR
|
||||
|
||||
AMR.example_isolates
|
||||
```
|
||||
|
||||
Aliasing with `as AMR` keeps all downstream code identical to the stable import. Switching between the stable release and the development version requires changing only the import line — nothing else in your script needs to change.
|
||||
|
||||
# SIR Classification with `as_sir()`
|
||||
|
||||
## Using `enforce_method`
|
||||
|
||||
The `as_sir()` function in R uses S3 method dispatch to select the correct calculation method based on the input class: `<mic>` for MIC values and `<disk>` for disk diffusion values. Because Python objects do not carry R class attributes through the `rpy2` bridge, this automatic dispatch may not resolve correctly.
|
||||
|
||||
To explicitly specify the input type, use the `enforce_method` argument:
|
||||
|
||||
```python
|
||||
# Treat the column as MIC values — maps to R's as.sir.mic()
|
||||
AMR.as_sir(df["MIC_col"], mo="E. coli", ab="AMX", guideline="EUCAST", enforce_method="mic")
|
||||
|
||||
# Treat the column as disk diffusion values — maps to R's as.sir.disk()
|
||||
AMR.as_sir(df["disk_col"], mo="E. coli", ab="AMX", guideline="EUCAST", enforce_method="disk")
|
||||
```
|
||||
|
||||
Without `enforce_method`, R falls back to class-based dispatch on the raw Python input, which may fail or return unexpected results. Always supply `enforce_method` when calling `as_sir()` from Python.
|
||||
|
||||
# Conclusion
|
||||
|
||||
With the `AMR` Python package, Python users can now effortlessly call R functions from the `AMR` R package. This eliminates the need for complex `rpy2` configurations and provides a clean, easy-to-use interface for antimicrobial resistance analysis. The examples provided above demonstrate how this can be applied to typical workflows, such as standardising microorganism and antimicrobial names or calculating resistance.
|
||||
|
||||
By just running `import AMR`, users can seamlessly integrate the robust features of the R `AMR` package into Python workflows.
|
||||
|
||||
Whether you're cleaning data or analysing resistance patterns, the `AMR` Python package makes it easy to work with AMR data in Python.
|
||||
@@ -0,0 +1,12 @@
|
||||
README.md
|
||||
setup.py
|
||||
AMR/__init__.py
|
||||
AMR/_engine.py
|
||||
AMR/beta.py
|
||||
AMR/datasets.py
|
||||
AMR/functions.py
|
||||
AMR.egg-info/PKG-INFO
|
||||
AMR.egg-info/SOURCES.txt
|
||||
AMR.egg-info/dependency_links.txt
|
||||
AMR.egg-info/requires.txt
|
||||
AMR.egg-info/top_level.txt
|
||||
@@ -0,0 +1 @@
|
||||
|
||||
@@ -0,0 +1,3 @@
|
||||
rpy2
|
||||
numpy
|
||||
pandas
|
||||
@@ -0,0 +1 @@
|
||||
AMR
|
||||
+249
@@ -0,0 +1,249 @@
|
||||
import sys
|
||||
|
||||
_DATASETS = frozenset({
|
||||
'example_isolates', 'microorganisms',
|
||||
'antimicrobials', 'clinical_breakpoints'
|
||||
})
|
||||
|
||||
class _AMRModule(type(sys.modules[__name__])):
|
||||
"""Lazy-loading module: nothing runs until an attribute is accessed."""
|
||||
|
||||
def __getattr__(self, name):
|
||||
if name in _DATASETS:
|
||||
from .datasets import get
|
||||
return get(name, source="cran")
|
||||
try:
|
||||
from . import functions
|
||||
return getattr(functions, name)
|
||||
except AttributeError:
|
||||
raise AttributeError(
|
||||
f"module 'AMR' has no attribute '{name}'")
|
||||
|
||||
sys.modules[__name__].__class__ = _AMRModule
|
||||
from .functions import custom_eucast_rules
|
||||
from .functions import ab_class
|
||||
from .functions import ab_selector
|
||||
from .functions import ab_from_text
|
||||
from .functions import ab_name
|
||||
from .functions import ab_cid
|
||||
from .functions import ab_synonyms
|
||||
from .functions import ab_tradenames
|
||||
from .functions import ab_group
|
||||
from .functions import ab_atc
|
||||
from .functions import ab_atc_group1
|
||||
from .functions import ab_atc_group2
|
||||
from .functions import ab_loinc
|
||||
from .functions import ab_ddd
|
||||
from .functions import ab_ddd_units
|
||||
from .functions import ab_info
|
||||
from .functions import ab_url
|
||||
from .functions import ab_property
|
||||
from .functions import add_custom_antimicrobials
|
||||
from .functions import clear_custom_antimicrobials
|
||||
from .functions import add_custom_microorganisms
|
||||
from .functions import clear_custom_microorganisms
|
||||
from .functions import age
|
||||
from .functions import age_groups
|
||||
from .functions import all_sir
|
||||
from .functions import all_sir_predictors
|
||||
from .functions import all_mic
|
||||
from .functions import all_mic_predictors
|
||||
from .functions import all_disk
|
||||
from .functions import all_disk_predictors
|
||||
from .functions import step_mic_log2
|
||||
from .functions import step_sir_numeric
|
||||
from .functions import amr_course
|
||||
from .functions import wisca
|
||||
from .functions import antibiogram
|
||||
from .functions import retrieve_wisca_parameters
|
||||
from .functions import wisca_plot
|
||||
from .functions import aminoglycosides
|
||||
from .functions import aminopenicillins
|
||||
from .functions import antifungals
|
||||
from .functions import antimycobacterials
|
||||
from .functions import betalactams
|
||||
from .functions import betalactams_with_inhibitor
|
||||
from .functions import carbapenems
|
||||
from .functions import cephalosporins
|
||||
from .functions import cephalosporins_1st
|
||||
from .functions import cephalosporins_2nd
|
||||
from .functions import cephalosporins_3rd
|
||||
from .functions import cephalosporins_4th
|
||||
from .functions import cephalosporins_5th
|
||||
from .functions import fluoroquinolones
|
||||
from .functions import glycopeptides
|
||||
from .functions import ionophores
|
||||
from .functions import isoxazolylpenicillins
|
||||
from .functions import lincosamides
|
||||
from .functions import lipoglycopeptides
|
||||
from .functions import macrolides
|
||||
from .functions import monobactams
|
||||
from .functions import nitrofurans
|
||||
from .functions import oxazolidinones
|
||||
from .functions import penicillins
|
||||
from .functions import peptides
|
||||
from .functions import phenicols
|
||||
from .functions import phosphonics
|
||||
from .functions import polymyxins
|
||||
from .functions import quinolones
|
||||
from .functions import rifamycins
|
||||
from .functions import spiropyrimidinetriones
|
||||
from .functions import streptogramins
|
||||
from .functions import sulfonamides
|
||||
from .functions import tetracyclines
|
||||
from .functions import trimethoprims
|
||||
from .functions import ureidopenicillins
|
||||
from .functions import amr_class
|
||||
from .functions import amr_selector
|
||||
from .functions import administrable_per_os
|
||||
from .functions import administrable_iv
|
||||
from .functions import not_intrinsic_resistant
|
||||
from .functions import as_ab
|
||||
from .functions import is_ab
|
||||
from .functions import ab_reset_session
|
||||
from .functions import as_av
|
||||
from .functions import is_av
|
||||
from .functions import as_disk
|
||||
from .functions import is_disk
|
||||
from .functions import as_mic
|
||||
from .functions import is_mic
|
||||
from .functions import rescale_mic
|
||||
from .functions import mic_p50
|
||||
from .functions import mic_p90
|
||||
from .functions import as_mo
|
||||
from .functions import is_mo
|
||||
from .functions import mo_uncertainties
|
||||
from .functions import mo_renamed
|
||||
from .functions import mo_failures
|
||||
from .functions import mo_reset_session
|
||||
from .functions import mo_cleaning_regex
|
||||
from .functions import as_sir
|
||||
from .functions import is_sir
|
||||
from .functions import is_sir_eligible
|
||||
from .functions import sir_interpretation_history
|
||||
from .functions import atc_online_property
|
||||
from .functions import atc_online_groups
|
||||
from .functions import atc_online_ddd
|
||||
from .functions import atc_online_ddd_units
|
||||
from .functions import av_from_text
|
||||
from .functions import av_name
|
||||
from .functions import av_cid
|
||||
from .functions import av_synonyms
|
||||
from .functions import av_tradenames
|
||||
from .functions import av_group
|
||||
from .functions import av_atc
|
||||
from .functions import av_loinc
|
||||
from .functions import av_ddd
|
||||
from .functions import av_ddd_units
|
||||
from .functions import av_info
|
||||
from .functions import av_url
|
||||
from .functions import av_property
|
||||
from .functions import availability
|
||||
from .functions import bug_drug_combinations
|
||||
from .functions import count_resistant
|
||||
from .functions import count_susceptible
|
||||
from .functions import count_S
|
||||
from .functions import count_SI
|
||||
from .functions import count_I
|
||||
from .functions import count_IR
|
||||
from .functions import count_R
|
||||
from .functions import count_all
|
||||
from .functions import n_sir
|
||||
from .functions import count_df
|
||||
from .functions import custom_interpretive_rules
|
||||
from .functions import custom_mdro_guideline
|
||||
from .functions import export_ncbi_biosample
|
||||
from .functions import first_isolate
|
||||
from .functions import filter_first_isolate
|
||||
from .functions import g_test
|
||||
from .functions import is_new_episode
|
||||
from .functions import ggplot_pca
|
||||
from .functions import ggplot_sir
|
||||
from .functions import geom_sir
|
||||
from .functions import guess_ab_col
|
||||
from .functions import interpretive_rules
|
||||
from .functions import eucast_rules
|
||||
from .functions import clsi_rules
|
||||
from .functions import eucast_dosage
|
||||
from .functions import italicise_taxonomy
|
||||
from .functions import italicize_taxonomy
|
||||
from .functions import inner_join_microorganisms
|
||||
from .functions import left_join_microorganisms
|
||||
from .functions import right_join_microorganisms
|
||||
from .functions import full_join_microorganisms
|
||||
from .functions import semi_join_microorganisms
|
||||
from .functions import anti_join_microorganisms
|
||||
from .functions import key_antimicrobials
|
||||
from .functions import all_antimicrobials
|
||||
from .functions import kurtosis
|
||||
from .functions import like
|
||||
from .functions import mdro
|
||||
from .functions import brmo
|
||||
from .functions import mrgn
|
||||
from .functions import mdr_tb
|
||||
from .functions import mdr_cmi2012
|
||||
from .functions import eucast_exceptional_phenotypes
|
||||
from .functions import mean_amr_distance
|
||||
from .functions import amr_distance_from_row
|
||||
from .functions import mo_matching_score
|
||||
from .functions import mo_name
|
||||
from .functions import mo_fullname
|
||||
from .functions import mo_shortname
|
||||
from .functions import mo_subspecies
|
||||
from .functions import mo_species
|
||||
from .functions import mo_genus
|
||||
from .functions import mo_family
|
||||
from .functions import mo_order
|
||||
from .functions import mo_class
|
||||
from .functions import mo_phylum
|
||||
from .functions import mo_kingdom
|
||||
from .functions import mo_domain
|
||||
from .functions import mo_type
|
||||
from .functions import mo_status
|
||||
from .functions import mo_pathogenicity
|
||||
from .functions import mo_gramstain
|
||||
from .functions import mo_is_gram_negative
|
||||
from .functions import mo_is_gram_positive
|
||||
from .functions import mo_is_yeast
|
||||
from .functions import mo_is_intrinsic_resistant
|
||||
from .functions import mo_oxygen_tolerance
|
||||
from .functions import mo_is_anaerobic
|
||||
from .functions import mo_morphology
|
||||
from .functions import mo_snomed
|
||||
from .functions import mo_ref
|
||||
from .functions import mo_authors
|
||||
from .functions import mo_year
|
||||
from .functions import mo_lpsn
|
||||
from .functions import mo_mycobank
|
||||
from .functions import mo_gbif
|
||||
from .functions import mo_rank
|
||||
from .functions import mo_taxonomy
|
||||
from .functions import mo_synonyms
|
||||
from .functions import mo_current
|
||||
from .functions import mo_group_members
|
||||
from .functions import mo_info
|
||||
from .functions import mo_url
|
||||
from .functions import mo_property
|
||||
from .functions import pca
|
||||
from .functions import theme_sir
|
||||
from .functions import labels_sir_count
|
||||
from .functions import resistance
|
||||
from .functions import susceptibility
|
||||
from .functions import sir_confidence_interval
|
||||
from .functions import proportion_R
|
||||
from .functions import proportion_IR
|
||||
from .functions import proportion_I
|
||||
from .functions import proportion_SI
|
||||
from .functions import proportion_S
|
||||
from .functions import proportion_df
|
||||
from .functions import sir_df
|
||||
from .functions import random_mic
|
||||
from .functions import random_disk
|
||||
from .functions import random_sir
|
||||
from .functions import resistance_predict
|
||||
from .functions import sir_predict
|
||||
from .functions import ggplot_sir_predict
|
||||
from .functions import skewness
|
||||
from .functions import top_n_microorganisms
|
||||
from .functions import reset_AMR_locale
|
||||
from .functions import translate_AMR
|
||||
@@ -0,0 +1,93 @@
|
||||
import os
|
||||
import sys
|
||||
import importlib.metadata as metadata
|
||||
|
||||
# Get the path to the virtual environment
|
||||
venv_path = sys.prefix
|
||||
r_lib_path = os.path.join(venv_path, "R_libs")
|
||||
os.makedirs(r_lib_path, exist_ok=True)
|
||||
|
||||
# Set environment variable before importing rpy2
|
||||
os.environ['R_LIBS_SITE'] = r_lib_path
|
||||
|
||||
from rpy2 import robjects
|
||||
from rpy2.robjects.vectors import StrVector
|
||||
from rpy2.robjects.packages import importr, isinstalled
|
||||
|
||||
# Import base and utils once
|
||||
base = importr('base')
|
||||
utils = importr('utils')
|
||||
|
||||
# Silence R console output entirely
|
||||
robjects.r('suppressMessages(suppressWarnings(sink(tempfile())))')
|
||||
base._libPaths(r_lib_path)
|
||||
|
||||
_installed_source = None
|
||||
|
||||
def _r_version():
|
||||
"""Return the currently installed AMR R package version, or None."""
|
||||
try:
|
||||
return str(robjects.r(
|
||||
f'as.character(packageVersion("AMR", lib.loc = "{r_lib_path}"))')[0])
|
||||
except Exception:
|
||||
return None
|
||||
|
||||
def _py_version():
|
||||
"""Return the Python AMR package version from metadata, or empty string."""
|
||||
try:
|
||||
return str(metadata.version('AMR'))
|
||||
except metadata.PackageNotFoundError:
|
||||
return ''
|
||||
|
||||
def _install_cran():
|
||||
"""Install AMR from CRAN into the isolated library."""
|
||||
print("AMR: Installing from CRAN...", flush=True)
|
||||
utils.install_packages(
|
||||
'AMR',
|
||||
repos='https://cloud.r-project.org',
|
||||
lib=r_lib_path,
|
||||
quiet=True
|
||||
)
|
||||
|
||||
def _install_github():
|
||||
"""Install AMR development version from GitHub into the isolated library."""
|
||||
print("AMR: Installing development version from GitHub...", flush=True)
|
||||
utils.install_packages(
|
||||
StrVector(['remotes', 'desc']),
|
||||
repos='https://cloud.r-project.org',
|
||||
lib=r_lib_path,
|
||||
quiet=True
|
||||
)
|
||||
remotes = importr('remotes', lib_loc=r_lib_path)
|
||||
remotes.install_github('msberends/AMR', lib=r_lib_path, quiet=True)
|
||||
|
||||
def ensure_amr(source="cran"):
|
||||
"""Ensure AMR is installed from the requested source. Idempotent per source."""
|
||||
global _installed_source
|
||||
|
||||
if _installed_source == source:
|
||||
return
|
||||
|
||||
install_fn = _install_github if source == "github" else _install_cran
|
||||
|
||||
if not isinstalled('AMR', lib_loc=r_lib_path):
|
||||
install_fn()
|
||||
else:
|
||||
# Check for version mismatch and update if needed
|
||||
r_ver = _r_version()
|
||||
py_ver = _py_version()
|
||||
if r_ver != py_ver:
|
||||
try:
|
||||
install_fn()
|
||||
except Exception as e:
|
||||
print(f"AMR: Could not update ({e})", flush=True)
|
||||
|
||||
print(f"AMR: R package version {_r_version()} ready.", flush=True)
|
||||
_installed_source = source
|
||||
|
||||
def restore_sink():
|
||||
"""Restore R console output after setup is complete."""
|
||||
try:
|
||||
robjects.r('sink()')
|
||||
except Exception:
|
||||
pass
|
||||
+22
@@ -0,0 +1,22 @@
|
||||
import sys
|
||||
|
||||
_DATASETS = frozenset({
|
||||
'example_isolates', 'microorganisms',
|
||||
'antimicrobials', 'clinical_breakpoints'
|
||||
})
|
||||
|
||||
class _BetaModule(type(sys.modules[__name__])):
|
||||
"""Lazy-loading module: installs AMR from GitHub on first access."""
|
||||
|
||||
def __getattr__(self, name):
|
||||
if name in _DATASETS:
|
||||
from .datasets import get
|
||||
return get(name, source="github")
|
||||
try:
|
||||
from . import functions
|
||||
return getattr(functions, name)
|
||||
except AttributeError:
|
||||
raise AttributeError(
|
||||
f"module 'AMR.beta' has no attribute '{name}'")
|
||||
|
||||
sys.modules[__name__].__class__ = _BetaModule
|
||||
@@ -0,0 +1,54 @@
|
||||
import pandas as pd
|
||||
from rpy2 import robjects
|
||||
from rpy2.robjects.conversion import localconverter
|
||||
from rpy2.robjects import default_converter, numpy2ri, pandas2ri
|
||||
|
||||
from ._engine import ensure_amr, restore_sink
|
||||
|
||||
_cache = {}
|
||||
_loaded_source = None
|
||||
|
||||
def _load_datasets(source="cran"):
|
||||
"""Load all AMR datasets into the module cache."""
|
||||
global _loaded_source
|
||||
|
||||
if _cache and _loaded_source == source:
|
||||
return
|
||||
|
||||
if _cache and _loaded_source != source:
|
||||
_cache.clear()
|
||||
|
||||
ensure_amr(source)
|
||||
|
||||
with localconverter(default_converter + numpy2ri.converter + pandas2ri.converter):
|
||||
_cache['example_isolates'] = _load_example_isolates()
|
||||
_cache['microorganisms'] = robjects.r(
|
||||
'AMR::microorganisms[, !sapply(AMR::microorganisms, is.list)]')
|
||||
_cache['antimicrobials'] = robjects.r(
|
||||
'AMR::antimicrobials[, !sapply(AMR::antimicrobials, is.list)]')
|
||||
_cache['clinical_breakpoints'] = robjects.r(
|
||||
'AMR::clinical_breakpoints[, !sapply(AMR::clinical_breakpoints, is.list)]')
|
||||
|
||||
restore_sink()
|
||||
_loaded_source = source
|
||||
|
||||
def _load_example_isolates():
|
||||
df = robjects.r('''
|
||||
df <- AMR::example_isolates
|
||||
df[] <- lapply(df, function(x) {
|
||||
if (inherits(x, c("Date", "POSIXt", "factor"))) {
|
||||
as.character(x)
|
||||
} else {
|
||||
x
|
||||
}
|
||||
})
|
||||
df <- df[, !sapply(df, is.list)]
|
||||
df
|
||||
''')
|
||||
df['date'] = pd.to_datetime(df['date'])
|
||||
return df
|
||||
|
||||
def get(name, source="cran"):
|
||||
"""Retrieve a dataset by name, installing AMR if needed."""
|
||||
_load_datasets(source)
|
||||
return _cache[name]
|
||||
@@ -0,0 +1,984 @@
|
||||
import functools
|
||||
import rpy2.robjects as robjects
|
||||
from rpy2.robjects.packages import importr
|
||||
from rpy2.robjects.vectors import StrVector, FactorVector, IntVector, FloatVector, DataFrame
|
||||
from rpy2.robjects.conversion import localconverter
|
||||
from rpy2.robjects import default_converter, numpy2ri, pandas2ri
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
|
||||
from ._engine import ensure_amr
|
||||
|
||||
# Ensure AMR is available before importing it in R
|
||||
ensure_amr("cran")
|
||||
amr_r = importr('AMR')
|
||||
|
||||
def convert_to_r(value):
|
||||
"""Convert Python lists/tuples to typed R vectors.
|
||||
|
||||
rpy2's default_converter passes Python lists to R as R lists, not as
|
||||
character/numeric vectors. This causes element-wise type-check functions
|
||||
such as is.mic(), is.sir(), and is.disk() to return a logical vector
|
||||
rather than a single logical, breaking R's scalar && operator.
|
||||
|
||||
This helper converts Python lists and tuples to the appropriate R vector
|
||||
type based on the element types, so R always receives a proper vector."""
|
||||
if isinstance(value, (list, tuple)):
|
||||
if len(value) == 0:
|
||||
return StrVector([])
|
||||
# bool must be checked before int because bool is a subclass of int
|
||||
if all(isinstance(v, bool) for v in value):
|
||||
return robjects.vectors.BoolVector(value)
|
||||
if all(isinstance(v, int) for v in value):
|
||||
return IntVector(value)
|
||||
if all(isinstance(v, float) for v in value):
|
||||
return FloatVector(value)
|
||||
if all(isinstance(v, str) for v in value):
|
||||
return StrVector(value)
|
||||
# Mixed types: coerce all to string
|
||||
return StrVector([str(v) for v in value])
|
||||
return value
|
||||
|
||||
def convert_to_python(r_output):
|
||||
# Check if it's a StrVector (R character vector)
|
||||
if isinstance(r_output, StrVector):
|
||||
return list(r_output) # Convert to a Python list of strings
|
||||
|
||||
# Check if it's a FactorVector (R factor)
|
||||
elif isinstance(r_output, FactorVector):
|
||||
return list(r_output) # Convert to a list of integers (factor levels)
|
||||
|
||||
# Check if it's an IntVector or FloatVector (numeric R vectors)
|
||||
elif isinstance(r_output, (IntVector, FloatVector)):
|
||||
return list(r_output) # Convert to a Python list of integers or floats
|
||||
|
||||
# Check if it's a pandas-compatible R data frame
|
||||
elif isinstance(r_output, (pd.DataFrame, DataFrame)):
|
||||
return r_output # Return as pandas DataFrame (already converted by pandas2ri)
|
||||
|
||||
# Check if the input is a NumPy array and has a string data type
|
||||
if isinstance(r_output, np.ndarray) and np.issubdtype(r_output.dtype, np.str_):
|
||||
return r_output.tolist() # Convert to a regular Python list
|
||||
|
||||
# Fall-back
|
||||
return r_output
|
||||
|
||||
def r_to_python(r_func):
|
||||
"""Decorator that converts Python list/tuple inputs to typed R vectors,
|
||||
runs the rpy2 function under a localconverter, and converts the output
|
||||
to a Python type."""
|
||||
@functools.wraps(r_func)
|
||||
def wrapper(*args, **kwargs):
|
||||
args = tuple(convert_to_r(a) for a in args)
|
||||
kwargs = {k: convert_to_r(v) for k, v in kwargs.items()}
|
||||
with localconverter(default_converter + numpy2ri.converter + pandas2ri.converter):
|
||||
return convert_to_python(r_func(*args, **kwargs))
|
||||
return wrapper
|
||||
@r_to_python
|
||||
def custom_eucast_rules(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.custom_eucast_rules(*args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_class(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_class(*args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_selector(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_selector(*args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_from_text(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_from_text(*args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_name(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_name(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_cid(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_cid(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_synonyms(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_synonyms(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_tradenames(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_tradenames(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_group(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_group(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_atc(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_atc(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_atc_group1(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_atc_group1(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_atc_group2(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_atc_group2(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_loinc(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_loinc(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_ddd(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_ddd(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_ddd_units(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_ddd_units(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_info(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_info(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_url(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_url(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ab_property(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_property(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def add_custom_antimicrobials(x):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.add_custom_antimicrobials(x)
|
||||
@r_to_python
|
||||
def clear_custom_antimicrobials(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.clear_custom_antimicrobials(*args, **kwargs)
|
||||
@r_to_python
|
||||
def add_custom_microorganisms(x):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.add_custom_microorganisms(x)
|
||||
@r_to_python
|
||||
def clear_custom_microorganisms(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.clear_custom_microorganisms(*args, **kwargs)
|
||||
@r_to_python
|
||||
def age(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.age(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def age_groups(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.age_groups(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def all_sir(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.all_sir(*args, **kwargs)
|
||||
@r_to_python
|
||||
def all_sir_predictors(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.all_sir_predictors(*args, **kwargs)
|
||||
@r_to_python
|
||||
def all_mic(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.all_mic(*args, **kwargs)
|
||||
@r_to_python
|
||||
def all_mic_predictors(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.all_mic_predictors(*args, **kwargs)
|
||||
@r_to_python
|
||||
def all_disk(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.all_disk(*args, **kwargs)
|
||||
@r_to_python
|
||||
def all_disk_predictors(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.all_disk_predictors(*args, **kwargs)
|
||||
@r_to_python
|
||||
def step_mic_log2(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.step_mic_log2(*args, **kwargs)
|
||||
@r_to_python
|
||||
def step_sir_numeric(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.step_sir_numeric(*args, **kwargs)
|
||||
@r_to_python
|
||||
def amr_course(github_repo, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.amr_course(github_repo, *args, **kwargs)
|
||||
@r_to_python
|
||||
def wisca(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.wisca(*args, **kwargs)
|
||||
@r_to_python
|
||||
def antibiogram(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.antibiogram(*args, **kwargs)
|
||||
@r_to_python
|
||||
def retrieve_wisca_parameters(wisca_model, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.retrieve_wisca_parameters(wisca_model, *args, **kwargs)
|
||||
@r_to_python
|
||||
def wisca_plot(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.wisca_plot(*args, **kwargs)
|
||||
@r_to_python
|
||||
def aminoglycosides(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.aminoglycosides(*args, **kwargs)
|
||||
@r_to_python
|
||||
def aminopenicillins(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.aminopenicillins(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def antifungals(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.antifungals(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def antimycobacterials(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.antimycobacterials(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def betalactams(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.betalactams(*args, **kwargs)
|
||||
@r_to_python
|
||||
def betalactams_with_inhibitor(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.betalactams_with_inhibitor(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def carbapenems(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.carbapenems(*args, **kwargs)
|
||||
@r_to_python
|
||||
def cephalosporins(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.cephalosporins(*args, **kwargs)
|
||||
@r_to_python
|
||||
def cephalosporins_1st(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.cephalosporins_1st(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def cephalosporins_2nd(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.cephalosporins_2nd(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def cephalosporins_3rd(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.cephalosporins_3rd(*args, **kwargs)
|
||||
@r_to_python
|
||||
def cephalosporins_4th(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.cephalosporins_4th(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def cephalosporins_5th(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.cephalosporins_5th(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def fluoroquinolones(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.fluoroquinolones(*args, **kwargs)
|
||||
@r_to_python
|
||||
def glycopeptides(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.glycopeptides(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ionophores(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ionophores(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def isoxazolylpenicillins(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.isoxazolylpenicillins(*args, **kwargs)
|
||||
@r_to_python
|
||||
def lincosamides(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.lincosamides(*args, **kwargs)
|
||||
@r_to_python
|
||||
def lipoglycopeptides(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.lipoglycopeptides(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def macrolides(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.macrolides(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def monobactams(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.monobactams(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def nitrofurans(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.nitrofurans(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def oxazolidinones(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.oxazolidinones(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def penicillins(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.penicillins(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def peptides(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.peptides(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def phenicols(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.phenicols(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def phosphonics(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.phosphonics(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def polymyxins(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.polymyxins(*args, **kwargs)
|
||||
@r_to_python
|
||||
def quinolones(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.quinolones(*args, **kwargs)
|
||||
@r_to_python
|
||||
def rifamycins(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.rifamycins(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def spiropyrimidinetriones(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.spiropyrimidinetriones(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def streptogramins(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.streptogramins(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def sulfonamides(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.sulfonamides(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def tetracyclines(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.tetracyclines(*args, **kwargs)
|
||||
@r_to_python
|
||||
def trimethoprims(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.trimethoprims(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ureidopenicillins(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ureidopenicillins(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def amr_class(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.amr_class(*args, **kwargs)
|
||||
@r_to_python
|
||||
def amr_selector(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.amr_selector(*args, **kwargs)
|
||||
@r_to_python
|
||||
def administrable_per_os(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.administrable_per_os(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def administrable_iv(only_sir_columns = False, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.administrable_iv(only_sir_columns = False, *args, **kwargs)
|
||||
@r_to_python
|
||||
def not_intrinsic_resistant(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.not_intrinsic_resistant(*args, **kwargs)
|
||||
@r_to_python
|
||||
def as_ab(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.as_ab(*args, **kwargs)
|
||||
@r_to_python
|
||||
def is_ab(x):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.is_ab(x)
|
||||
@r_to_python
|
||||
def ab_reset_session(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ab_reset_session(*args, **kwargs)
|
||||
@r_to_python
|
||||
def as_av(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.as_av(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def is_av(x):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.is_av(x)
|
||||
@r_to_python
|
||||
def as_disk(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.as_disk(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def is_disk(x):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.is_disk(x)
|
||||
@r_to_python
|
||||
def as_mic(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.as_mic(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def is_mic(x):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.is_mic(x)
|
||||
@r_to_python
|
||||
def rescale_mic(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.rescale_mic(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mic_p50(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mic_p50(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def mic_p90(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mic_p90(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def as_mo(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.as_mo(*args, **kwargs)
|
||||
@r_to_python
|
||||
def is_mo(x):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.is_mo(x)
|
||||
@r_to_python
|
||||
def mo_uncertainties(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_uncertainties(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_renamed(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_renamed(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_failures(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_failures(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_reset_session(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_reset_session(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_cleaning_regex(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_cleaning_regex(*args, **kwargs)
|
||||
@r_to_python
|
||||
def as_sir(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.as_sir(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def is_sir(x):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.is_sir(x)
|
||||
@r_to_python
|
||||
def is_sir_eligible(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.is_sir_eligible(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def sir_interpretation_history(clean):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.sir_interpretation_history(clean)
|
||||
@r_to_python
|
||||
def atc_online_property(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.atc_online_property(*args, **kwargs)
|
||||
@r_to_python
|
||||
def atc_online_groups(atc_code, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.atc_online_groups(atc_code, *args, **kwargs)
|
||||
@r_to_python
|
||||
def atc_online_ddd(atc_code, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.atc_online_ddd(atc_code, *args, **kwargs)
|
||||
@r_to_python
|
||||
def atc_online_ddd_units(atc_code, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.atc_online_ddd_units(atc_code, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_from_text(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_from_text(*args, **kwargs)
|
||||
@r_to_python
|
||||
def av_name(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_name(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_cid(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_cid(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_synonyms(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_synonyms(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_tradenames(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_tradenames(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_group(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_group(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_atc(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_atc(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_loinc(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_loinc(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_ddd(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_ddd(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_ddd_units(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_ddd_units(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_info(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_info(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_url(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_url(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def av_property(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.av_property(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def availability(tbl, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.availability(tbl, *args, **kwargs)
|
||||
@r_to_python
|
||||
def bug_drug_combinations(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.bug_drug_combinations(*args, **kwargs)
|
||||
@r_to_python
|
||||
def count_resistant(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.count_resistant(*args, **kwargs)
|
||||
@r_to_python
|
||||
def count_susceptible(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.count_susceptible(*args, **kwargs)
|
||||
@r_to_python
|
||||
def count_S(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.count_S(*args, **kwargs)
|
||||
@r_to_python
|
||||
def count_SI(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.count_SI(*args, **kwargs)
|
||||
@r_to_python
|
||||
def count_I(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.count_I(*args, **kwargs)
|
||||
@r_to_python
|
||||
def count_IR(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.count_IR(*args, **kwargs)
|
||||
@r_to_python
|
||||
def count_R(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.count_R(*args, **kwargs)
|
||||
@r_to_python
|
||||
def count_all(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.count_all(*args, **kwargs)
|
||||
@r_to_python
|
||||
def n_sir(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.n_sir(*args, **kwargs)
|
||||
@r_to_python
|
||||
def count_df(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.count_df(*args, **kwargs)
|
||||
@r_to_python
|
||||
def custom_interpretive_rules(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.custom_interpretive_rules(*args, **kwargs)
|
||||
@r_to_python
|
||||
def custom_mdro_guideline(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.custom_mdro_guideline(*args, **kwargs)
|
||||
@r_to_python
|
||||
def export_ncbi_biosample(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.export_ncbi_biosample(*args, **kwargs)
|
||||
@r_to_python
|
||||
def first_isolate(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.first_isolate(*args, **kwargs)
|
||||
@r_to_python
|
||||
def filter_first_isolate(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.filter_first_isolate(*args, **kwargs)
|
||||
@r_to_python
|
||||
def g_test(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.g_test(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def is_new_episode(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.is_new_episode(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def ggplot_pca(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ggplot_pca(*args, **kwargs)
|
||||
@r_to_python
|
||||
def ggplot_sir(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ggplot_sir(*args, **kwargs)
|
||||
@r_to_python
|
||||
def geom_sir(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.geom_sir(*args, **kwargs)
|
||||
@r_to_python
|
||||
def guess_ab_col(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.guess_ab_col(*args, **kwargs)
|
||||
@r_to_python
|
||||
def interpretive_rules(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.interpretive_rules(*args, **kwargs)
|
||||
@r_to_python
|
||||
def eucast_rules(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.eucast_rules(*args, **kwargs)
|
||||
@r_to_python
|
||||
def clsi_rules(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.clsi_rules(*args, **kwargs)
|
||||
@r_to_python
|
||||
def eucast_dosage(ab, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.eucast_dosage(ab, *args, **kwargs)
|
||||
@r_to_python
|
||||
def italicise_taxonomy(string, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.italicise_taxonomy(string, *args, **kwargs)
|
||||
@r_to_python
|
||||
def italicize_taxonomy(string, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.italicize_taxonomy(string, *args, **kwargs)
|
||||
@r_to_python
|
||||
def inner_join_microorganisms(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.inner_join_microorganisms(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def left_join_microorganisms(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.left_join_microorganisms(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def right_join_microorganisms(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.right_join_microorganisms(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def full_join_microorganisms(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.full_join_microorganisms(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def semi_join_microorganisms(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.semi_join_microorganisms(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def anti_join_microorganisms(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.anti_join_microorganisms(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def key_antimicrobials(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.key_antimicrobials(*args, **kwargs)
|
||||
@r_to_python
|
||||
def all_antimicrobials(x = None, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.all_antimicrobials(x = None, *args, **kwargs)
|
||||
@r_to_python
|
||||
def kurtosis(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.kurtosis(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def like(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.like(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def mdro(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mdro(*args, **kwargs)
|
||||
@r_to_python
|
||||
def brmo(x = None, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.brmo(x = None, *args, **kwargs)
|
||||
@r_to_python
|
||||
def mrgn(x = None, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mrgn(x = None, *args, **kwargs)
|
||||
@r_to_python
|
||||
def mdr_tb(x = None, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mdr_tb(x = None, *args, **kwargs)
|
||||
@r_to_python
|
||||
def mdr_cmi2012(x = None, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mdr_cmi2012(x = None, *args, **kwargs)
|
||||
@r_to_python
|
||||
def eucast_exceptional_phenotypes(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.eucast_exceptional_phenotypes(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mean_amr_distance(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mean_amr_distance(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def amr_distance_from_row(amr_distance, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.amr_distance_from_row(amr_distance, *args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_matching_score(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_matching_score(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_name(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_name(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_fullname(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_fullname(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_shortname(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_shortname(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_subspecies(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_subspecies(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_species(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_species(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_genus(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_genus(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_family(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_family(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_order(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_order(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_class(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_class(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_phylum(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_phylum(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_kingdom(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_kingdom(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_domain(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_domain(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_type(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_type(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_status(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_status(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_pathogenicity(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_pathogenicity(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_gramstain(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_gramstain(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_is_gram_negative(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_is_gram_negative(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_is_gram_positive(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_is_gram_positive(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_is_yeast(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_is_yeast(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_is_intrinsic_resistant(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_is_intrinsic_resistant(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_oxygen_tolerance(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_oxygen_tolerance(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_is_anaerobic(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_is_anaerobic(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_morphology(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_morphology(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_snomed(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_snomed(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_ref(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_ref(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_authors(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_authors(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_year(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_year(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_lpsn(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_lpsn(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_mycobank(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_mycobank(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_gbif(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_gbif(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_rank(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_rank(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_taxonomy(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_taxonomy(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_synonyms(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_synonyms(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_current(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_current(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_group_members(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_group_members(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_info(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_info(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_url(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_url(*args, **kwargs)
|
||||
@r_to_python
|
||||
def mo_property(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.mo_property(*args, **kwargs)
|
||||
@r_to_python
|
||||
def pca(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.pca(*args, **kwargs)
|
||||
@r_to_python
|
||||
def theme_sir(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.theme_sir(*args, **kwargs)
|
||||
@r_to_python
|
||||
def labels_sir_count(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.labels_sir_count(*args, **kwargs)
|
||||
@r_to_python
|
||||
def resistance(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.resistance(*args, **kwargs)
|
||||
@r_to_python
|
||||
def susceptibility(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.susceptibility(*args, **kwargs)
|
||||
@r_to_python
|
||||
def sir_confidence_interval(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.sir_confidence_interval(*args, **kwargs)
|
||||
@r_to_python
|
||||
def proportion_R(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.proportion_R(*args, **kwargs)
|
||||
@r_to_python
|
||||
def proportion_IR(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.proportion_IR(*args, **kwargs)
|
||||
@r_to_python
|
||||
def proportion_I(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.proportion_I(*args, **kwargs)
|
||||
@r_to_python
|
||||
def proportion_SI(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.proportion_SI(*args, **kwargs)
|
||||
@r_to_python
|
||||
def proportion_S(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.proportion_S(*args, **kwargs)
|
||||
@r_to_python
|
||||
def proportion_df(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.proportion_df(*args, **kwargs)
|
||||
@r_to_python
|
||||
def sir_df(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.sir_df(*args, **kwargs)
|
||||
@r_to_python
|
||||
def random_mic(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.random_mic(*args, **kwargs)
|
||||
@r_to_python
|
||||
def random_disk(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.random_disk(*args, **kwargs)
|
||||
@r_to_python
|
||||
def random_sir(size = None, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.random_sir(size = None, *args, **kwargs)
|
||||
@r_to_python
|
||||
def resistance_predict(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.resistance_predict(*args, **kwargs)
|
||||
@r_to_python
|
||||
def sir_predict(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.sir_predict(*args, **kwargs)
|
||||
@r_to_python
|
||||
def ggplot_sir_predict(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.ggplot_sir_predict(*args, **kwargs)
|
||||
@r_to_python
|
||||
def skewness(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.skewness(x, *args, **kwargs)
|
||||
@r_to_python
|
||||
def top_n_microorganisms(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.top_n_microorganisms(*args, **kwargs)
|
||||
@r_to_python
|
||||
def reset_AMR_locale(*args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.reset_AMR_locale(*args, **kwargs)
|
||||
@r_to_python
|
||||
def translate_AMR(x, *args, **kwargs):
|
||||
"""Please see our website of the R package for the full manual: https://amr-for-r.org"""
|
||||
return amr_r.translate_AMR(x, *args, **kwargs)
|
||||
@@ -1,3 +0,0 @@
|
||||
Version: 1.8.1
|
||||
Date: 2022-03-16 18:22:51 UTC
|
||||
SHA: 7b0f1596bd65fbb72681a7e3a6a7e4e469a891e8
|
||||
-51
@@ -1,51 +0,0 @@
|
||||
Package: AMR
|
||||
Version: 1.8.1.9026
|
||||
Date: 2022-08-25
|
||||
Title: Antimicrobial Resistance Data Analysis
|
||||
Description: Functions to simplify and standardise antimicrobial resistance (AMR)
|
||||
data analysis and to work with microbial and antimicrobial properties by
|
||||
using evidence-based methods and reliable reference data such as LPSN
|
||||
<doi:10.1099/ijsem.0.004332>.
|
||||
Authors@R: c(
|
||||
person(c("Matthijs", "S."), "Berends", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7620-1800"), email = "m.berends@certe.nl"),
|
||||
person(c("Christian", "F."), "Luz", role = c("aut", "ctb"), comment = c(ORCID = "0000-0001-5809-5995")),
|
||||
person("Dennis", "Souverein", role = c("aut", "ctb"), comment = c(ORCID = "0000-0003-0455-0336")),
|
||||
person(c("Erwin", "E.", "A."), "Hassing", role = c("aut", "ctb")),
|
||||
person("Casper", "Albers", role = "ths", comment = c(ORCID = "0000-0002-9213-6743")),
|
||||
person("Peter", "Dutey-Magni", role = "ctb", comment = c(ORCID = "0000-0002-8942-9836")),
|
||||
person("Judith", "Fonville", role = "ctb"),
|
||||
person("Alex", "Friedrich", role = "ths", comment = c(ORCID = "0000-0003-4881-038X")),
|
||||
person("Corinna", "Glasner", role = "ths", comment = c(ORCID = "0000-0003-1241-1328")),
|
||||
person("Eric", "Hazenberg", role = "ctb"),
|
||||
person("Gwen", "Knight", role = "ctb", comment = c(ORCID = "0000-0002-7263-9896")),
|
||||
person("Annick", "Lenglet", role = "ctb", comment = c(ORCID = "0000-0003-2013-8405")),
|
||||
person("Bart", "Meijer", role = "ctb"),
|
||||
person("Anton", "Mymrikov", role = "ctb"),
|
||||
person("Sofia", "Ny", role = "ctb", comment = c(ORCID = "0000-0002-2017-1363")),
|
||||
person("Rogier", "Schade", role = "ctb"),
|
||||
person("Bhanu", "Sinha", role = "ths", comment = c(ORCID = "0000-0003-1634-0010")),
|
||||
person("Anthony", "Underwood", role = "ctb", comment = c(ORCID = "0000-0002-8547-4277")))
|
||||
Depends: R (>= 3.0.0)
|
||||
Enhances:
|
||||
cleaner,
|
||||
skimr,
|
||||
ggplot2,
|
||||
tidyselect
|
||||
Suggests:
|
||||
curl,
|
||||
dplyr,
|
||||
knitr,
|
||||
progress,
|
||||
readxl,
|
||||
rmarkdown,
|
||||
rvest,
|
||||
tinytest,
|
||||
xml2
|
||||
VignetteBuilder: knitr,rmarkdown
|
||||
URL: https://msberends.github.io/AMR/, https://github.com/msberends/AMR
|
||||
BugReports: https://github.com/msberends/AMR/issues
|
||||
License: GPL-2 | file LICENSE
|
||||
Encoding: UTF-8
|
||||
LazyData: true
|
||||
RoxygenNote: 7.2.1
|
||||
Roxygen: list(markdown = TRUE)
|
||||
@@ -1,248 +0,0 @@
|
||||
GNU GENERAL PUBLIC LICENSE
|
||||
Version 2, June 1991
|
||||
|
||||
Copyright (C) 1989, 1991 Free Software Foundation, Inc., <http://fsf.org/>
|
||||
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
|
||||
Everyone is permitted to copy and distribute verbatim copies
|
||||
of this license document, but changing it is not allowed.
|
||||
|
||||
A SUMMARY OF THIS LICENSE BY THE ORIGINAL AUTHORS OF THE AMR R PACKAGE
|
||||
|
||||
This R package, with package name 'AMR':
|
||||
- May be used for commercial purposes
|
||||
- May be used for private purposes
|
||||
- May NOT be used for patent purposes
|
||||
- May be modified, although:
|
||||
- Modifications MUST be released under the same license when distributing the package
|
||||
- Changes made to the code MUST be documented
|
||||
- May be distributed, although:
|
||||
- Source code MUST be made available when the package is distributed
|
||||
- A copy of the license and copyright notice MUST be included with the package.
|
||||
- Comes with a LIMITATION of liability
|
||||
- Comes with NO warranty
|
||||
|
||||
END OF THE SUMMARY
|
||||
|
||||
|
||||
GNU GENERAL PUBLIC LICENSE
|
||||
TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
|
||||
|
||||
0. This License applies to any program or other work which contains
|
||||
a notice placed by the copyright holder saying it may be distributed
|
||||
under the terms of this General Public License. The "Program", below,
|
||||
refers to any such program or work, and a "work based on the Program"
|
||||
means either the Program or any derivative work under copyright law:
|
||||
that is to say, a work containing the Program or a portion of it,
|
||||
either verbatim or with modifications and/or translated into another
|
||||
language. (Hereinafter, translation is included without limitation in
|
||||
the term "modification".) Each licensee is addressed as "you".
|
||||
|
||||
Activities other than copying, distribution and modification are not
|
||||
covered by this License; they are outside its scope. The act of
|
||||
running the Program is not restricted, and the output from the Program
|
||||
is covered only if its contents constitute a work based on the
|
||||
Program (independent of having been made by running the Program).
|
||||
Whether that is true depends on what the Program does.
|
||||
|
||||
1. You may copy and distribute verbatim copies of the Program's
|
||||
source code as you receive it, in any medium, provided that you
|
||||
conspicuously and appropriately publish on each copy an appropriate
|
||||
copyright notice and disclaimer of warranty; keep intact all the
|
||||
notices that refer to this License and to the absence of any warranty;
|
||||
and give any other recipients of the Program a copy of this License
|
||||
along with the Program.
|
||||
|
||||
You may charge a fee for the physical act of transferring a copy, and
|
||||
you may at your option offer warranty protection in exchange for a fee.
|
||||
|
||||
2. You may modify your copy or copies of the Program or any portion
|
||||
of it, thus forming a work based on the Program, and copy and
|
||||
distribute such modifications or work under the terms of Section 1
|
||||
above, provided that you also meet all of these conditions:
|
||||
|
||||
a) You must cause the modified files to carry prominent notices
|
||||
stating that you changed the files and the date of any change.
|
||||
|
||||
b) You must cause any work that you distribute or publish, that in
|
||||
whole or in part contains or is derived from the Program or any
|
||||
part thereof, to be licensed as a whole at no charge to all third
|
||||
parties under the terms of this License.
|
||||
|
||||
c) If the modified program normally reads commands interactively
|
||||
when run, you must cause it, when started running for such
|
||||
interactive use in the most ordinary way, to print or display an
|
||||
announcement including an appropriate copyright notice and a
|
||||
notice that there is no warranty (or else, saying that you provide
|
||||
a warranty) and that users may redistribute the program under
|
||||
these conditions, and telling the user how to view a copy of this
|
||||
License. (Exception: if the Program itself is interactive but
|
||||
does not normally print such an announcement, your work based on
|
||||
the Program is not required to print an announcement.)
|
||||
|
||||
These requirements apply to the modified work as a whole. If
|
||||
identifiable sections of that work are not derived from the Program,
|
||||
and can be reasonably considered independent and separate works in
|
||||
themselves, then this License, and its terms, do not apply to those
|
||||
sections when you distribute them as separate works. But when you
|
||||
distribute the same sections as part of a whole which is a work based
|
||||
on the Program, the distribution of the whole must be on the terms of
|
||||
this License, whose permissions for other licensees extend to the
|
||||
entire whole, and thus to each and every part regardless of who wrote it.
|
||||
|
||||
Thus, it is not the intent of this section to claim rights or contest
|
||||
your rights to work written entirely by you; rather, the intent is to
|
||||
exercise the right to control the distribution of derivative or
|
||||
collective works based on the Program.
|
||||
|
||||
In addition, mere aggregation of another work not based on the Program
|
||||
with the Program (or with a work based on the Program) on a volume of
|
||||
a storage or distribution medium does not bring the other work under
|
||||
the scope of this License.
|
||||
|
||||
3. You may copy and distribute the Program (or a work based on it,
|
||||
under Section 2) in object code or executable form under the terms of
|
||||
Sections 1 and 2 above provided that you also do one of the following:
|
||||
|
||||
a) Accompany it with the complete corresponding machine-readable
|
||||
source code, which must be distributed under the terms of Sections
|
||||
1 and 2 above on a medium customarily used for software interchange; or,
|
||||
|
||||
b) Accompany it with a written offer, valid for at least three
|
||||
years, to give any third party, for a charge no more than your
|
||||
cost of physically performing source distribution, a complete
|
||||
machine-readable copy of the corresponding source code, to be
|
||||
distributed under the terms of Sections 1 and 2 above on a medium
|
||||
customarily used for software interchange; or,
|
||||
|
||||
c) Accompany it with the information you received as to the offer
|
||||
to distribute corresponding source code. (This alternative is
|
||||
allowed only for noncommercial distribution and only if you
|
||||
received the program in object code or executable form with such
|
||||
an offer, in accord with Subsection b above.)
|
||||
|
||||
The source code for a work means the preferred form of the work for
|
||||
making modifications to it. For an executable work, complete source
|
||||
code means all the source code for all modules it contains, plus any
|
||||
associated interface definition files, plus the scripts used to
|
||||
control compilation and installation of the executable. However, as a
|
||||
special exception, the source code distributed need not include
|
||||
anything that is normally distributed (in either source or binary
|
||||
form) with the major components (compiler, kernel, and so on) of the
|
||||
operating system on which the executable runs, unless that component
|
||||
itself accompanies the executable.
|
||||
|
||||
If distribution of executable or object code is made by offering
|
||||
access to copy from a designated place, then offering equivalent
|
||||
access to copy the source code from the same place counts as
|
||||
distribution of the source code, even though third parties are not
|
||||
compelled to copy the source along with the object code.
|
||||
|
||||
4. You may not copy, modify, sublicense, or distribute the Program
|
||||
except as expressly provided under this License. Any attempt
|
||||
otherwise to copy, modify, sublicense or distribute the Program is
|
||||
void, and will automatically terminate your rights under this License.
|
||||
However, parties who have received copies, or rights, from you under
|
||||
this License will not have their licenses terminated so long as such
|
||||
parties remain in full compliance.
|
||||
|
||||
5. You are not required to accept this License, since you have not
|
||||
signed it. However, nothing else grants you permission to modify or
|
||||
distribute the Program or its derivative works. These actions are
|
||||
prohibited by law if you do not accept this License. Therefore, by
|
||||
modifying or distributing the Program (or any work based on the
|
||||
Program), you indicate your acceptance of this License to do so, and
|
||||
all its terms and conditions for copying, distributing or modifying
|
||||
the Program or works based on it.
|
||||
|
||||
6. Each time you redistribute the Program (or any work based on the
|
||||
Program), the recipient automatically receives a license from the
|
||||
original licensor to copy, distribute or modify the Program subject to
|
||||
these terms and conditions. You may not impose any further
|
||||
restrictions on the recipients' exercise of the rights granted herein.
|
||||
You are not responsible for enforcing compliance by third parties to
|
||||
this License.
|
||||
|
||||
7. If, as a consequence of a court judgment or allegation of patent
|
||||
infringement or for any other reason (not limited to patent issues),
|
||||
conditions are imposed on you (whether by court order, agreement or
|
||||
otherwise) that contradict the conditions of this License, they do not
|
||||
excuse you from the conditions of this License. If you cannot
|
||||
distribute so as to satisfy simultaneously your obligations under this
|
||||
License and any other pertinent obligations, then as a consequence you
|
||||
may not distribute the Program at all. For example, if a patent
|
||||
license would not permit royalty-free redistribution of the Program by
|
||||
all those who receive copies directly or indirectly through you, then
|
||||
the only way you could satisfy both it and this License would be to
|
||||
refrain entirely from distribution of the Program.
|
||||
|
||||
If any portion of this section is held invalid or unenforceable under
|
||||
any particular circumstance, the balance of the section is intended to
|
||||
apply and the section as a whole is intended to apply in other
|
||||
circumstances.
|
||||
|
||||
It is not the purpose of this section to induce you to infringe any
|
||||
patents or other property right claims or to contest validity of any
|
||||
such claims; this section has the sole purpose of protecting the
|
||||
integrity of the free software distribution system, which is
|
||||
implemented by public license practices. Many people have made
|
||||
generous contributions to the wide range of software distributed
|
||||
through that system in reliance on consistent application of that
|
||||
system; it is up to the author/donor to decide if he or she is willing
|
||||
to distribute software through any other system and a licensee cannot
|
||||
impose that choice.
|
||||
|
||||
This section is intended to make thoroughly clear what is believed to
|
||||
be a consequence of the rest of this License.
|
||||
|
||||
8. If the distribution and/or use of the Program is restricted in
|
||||
certain countries either by patents or by copyrighted interfaces, the
|
||||
original copyright holder who places the Program under this License
|
||||
may add an explicit geographical distribution limitation excluding
|
||||
those countries, so that distribution is permitted only in or among
|
||||
countries not thus excluded. In such case, this License incorporates
|
||||
the limitation as if written in the body of this License.
|
||||
|
||||
9. The Free Software Foundation may publish revised and/or new versions
|
||||
of the General Public License from time to time. Such new versions will
|
||||
be similar in spirit to the present version, but may differ in detail to
|
||||
address new problems or concerns.
|
||||
|
||||
Each version is given a distinguishing version number. If the Program
|
||||
specifies a version number of this License which applies to it and "any
|
||||
later version", you have the option of following the terms and conditions
|
||||
either of that version or of any later version published by the Free
|
||||
Software Foundation. If the Program does not specify a version number of
|
||||
this License, you may choose any version ever published by the Free Software
|
||||
Foundation.
|
||||
|
||||
10. If you wish to incorporate parts of the Program into other free
|
||||
programs whose distribution conditions are different, write to the author
|
||||
to ask for permission. For software which is copyrighted by the Free
|
||||
Software Foundation, write to the Free Software Foundation; we sometimes
|
||||
make exceptions for this. Our decision will be guided by the two goals
|
||||
of preserving the free status of all derivatives of our free software and
|
||||
of promoting the sharing and reuse of software generally.
|
||||
|
||||
NO WARRANTY
|
||||
|
||||
11. BECAUSE THE PROGRAM IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY
|
||||
FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN
|
||||
OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES
|
||||
PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED
|
||||
OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
|
||||
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS
|
||||
TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE
|
||||
PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING,
|
||||
REPAIR OR CORRECTION.
|
||||
|
||||
12. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
|
||||
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR
|
||||
REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES,
|
||||
INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING
|
||||
OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED
|
||||
TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY
|
||||
YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER
|
||||
PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE
|
||||
POSSIBILITY OF SUCH DAMAGES.
|
||||
|
||||
END OF TERMS AND CONDITIONS
|
||||
@@ -1,350 +0,0 @@
|
||||
# Generated by roxygen2: do not edit by hand
|
||||
|
||||
S3method("!",mic)
|
||||
S3method("!=",ab_selector)
|
||||
S3method("!=",mic)
|
||||
S3method("%%",mic)
|
||||
S3method("%/%",mic)
|
||||
S3method("&",ab_selector)
|
||||
S3method("&",mic)
|
||||
S3method("*",mic)
|
||||
S3method("+",mic)
|
||||
S3method("-",mic)
|
||||
S3method("/",mic)
|
||||
S3method("<",mic)
|
||||
S3method("<=",mic)
|
||||
S3method("==",ab_selector)
|
||||
S3method("==",mic)
|
||||
S3method(">",mic)
|
||||
S3method(">=",mic)
|
||||
S3method("[",ab)
|
||||
S3method("[",disk)
|
||||
S3method("[",mic)
|
||||
S3method("[",mo)
|
||||
S3method("[<-",ab)
|
||||
S3method("[<-",disk)
|
||||
S3method("[<-",mic)
|
||||
S3method("[<-",mo)
|
||||
S3method("[<-",rsi)
|
||||
S3method("[[",ab)
|
||||
S3method("[[",disk)
|
||||
S3method("[[",mic)
|
||||
S3method("[[",mo)
|
||||
S3method("[[<-",ab)
|
||||
S3method("[[<-",disk)
|
||||
S3method("[[<-",mic)
|
||||
S3method("[[<-",mo)
|
||||
S3method("[[<-",rsi)
|
||||
S3method("^",mic)
|
||||
S3method("|",ab_selector)
|
||||
S3method("|",mic)
|
||||
S3method(abs,mic)
|
||||
S3method(acos,mic)
|
||||
S3method(acosh,mic)
|
||||
S3method(all,ab_selector)
|
||||
S3method(all,ab_selector_any_all)
|
||||
S3method(all,mic)
|
||||
S3method(any,ab_selector)
|
||||
S3method(any,ab_selector_any_all)
|
||||
S3method(any,mic)
|
||||
S3method(as.data.frame,ab)
|
||||
S3method(as.data.frame,mo)
|
||||
S3method(as.double,mic)
|
||||
S3method(as.list,custom_eucast_rules)
|
||||
S3method(as.list,custom_mdro_guideline)
|
||||
S3method(as.matrix,mic)
|
||||
S3method(as.numeric,mic)
|
||||
S3method(as.rsi,data.frame)
|
||||
S3method(as.rsi,default)
|
||||
S3method(as.rsi,disk)
|
||||
S3method(as.rsi,mic)
|
||||
S3method(asin,mic)
|
||||
S3method(asinh,mic)
|
||||
S3method(atan,mic)
|
||||
S3method(atanh,mic)
|
||||
S3method(barplot,disk)
|
||||
S3method(barplot,mic)
|
||||
S3method(barplot,rsi)
|
||||
S3method(c,ab)
|
||||
S3method(c,ab_selector)
|
||||
S3method(c,custom_eucast_rules)
|
||||
S3method(c,custom_mdro_guideline)
|
||||
S3method(c,disk)
|
||||
S3method(c,mic)
|
||||
S3method(c,mo)
|
||||
S3method(c,rsi)
|
||||
S3method(ceiling,mic)
|
||||
S3method(close,progress_bar)
|
||||
S3method(cos,mic)
|
||||
S3method(cosh,mic)
|
||||
S3method(cospi,mic)
|
||||
S3method(cummax,mic)
|
||||
S3method(cummin,mic)
|
||||
S3method(cumprod,mic)
|
||||
S3method(cumsum,mic)
|
||||
S3method(digamma,mic)
|
||||
S3method(droplevels,mic)
|
||||
S3method(droplevels,rsi)
|
||||
S3method(exp,mic)
|
||||
S3method(expm1,mic)
|
||||
S3method(floor,mic)
|
||||
S3method(format,bug_drug_combinations)
|
||||
S3method(gamma,mic)
|
||||
S3method(hist,mic)
|
||||
S3method(kurtosis,data.frame)
|
||||
S3method(kurtosis,default)
|
||||
S3method(kurtosis,matrix)
|
||||
S3method(lgamma,mic)
|
||||
S3method(log,mic)
|
||||
S3method(log10,mic)
|
||||
S3method(log1p,mic)
|
||||
S3method(log2,mic)
|
||||
S3method(max,mic)
|
||||
S3method(mean,mic)
|
||||
S3method(median,mic)
|
||||
S3method(min,mic)
|
||||
S3method(plot,disk)
|
||||
S3method(plot,mic)
|
||||
S3method(plot,resistance_predict)
|
||||
S3method(plot,rsi)
|
||||
S3method(print,ab)
|
||||
S3method(print,bug_drug_combinations)
|
||||
S3method(print,catalogue_of_life_version)
|
||||
S3method(print,custom_eucast_rules)
|
||||
S3method(print,custom_mdro_guideline)
|
||||
S3method(print,disk)
|
||||
S3method(print,mic)
|
||||
S3method(print,mo)
|
||||
S3method(print,mo_renamed)
|
||||
S3method(print,mo_uncertainties)
|
||||
S3method(print,pca)
|
||||
S3method(print,rsi)
|
||||
S3method(prod,mic)
|
||||
S3method(quantile,mic)
|
||||
S3method(range,mic)
|
||||
S3method(rep,ab)
|
||||
S3method(rep,disk)
|
||||
S3method(rep,mic)
|
||||
S3method(rep,mo)
|
||||
S3method(rep,rsi)
|
||||
S3method(round,mic)
|
||||
S3method(sign,mic)
|
||||
S3method(signif,mic)
|
||||
S3method(sin,mic)
|
||||
S3method(sinh,mic)
|
||||
S3method(sinpi,mic)
|
||||
S3method(skewness,data.frame)
|
||||
S3method(skewness,default)
|
||||
S3method(skewness,matrix)
|
||||
S3method(sort,mic)
|
||||
S3method(sqrt,mic)
|
||||
S3method(sum,mic)
|
||||
S3method(summary,mic)
|
||||
S3method(summary,mo)
|
||||
S3method(summary,pca)
|
||||
S3method(summary,rsi)
|
||||
S3method(tan,mic)
|
||||
S3method(tanh,mic)
|
||||
S3method(tanpi,mic)
|
||||
S3method(trigamma,mic)
|
||||
S3method(trunc,mic)
|
||||
S3method(unique,ab)
|
||||
S3method(unique,disk)
|
||||
S3method(unique,mic)
|
||||
S3method(unique,mo)
|
||||
S3method(unique,rsi)
|
||||
export("%like%")
|
||||
export("%like_case%")
|
||||
export("%unlike%")
|
||||
export("%unlike_case%")
|
||||
export(NA_disk_)
|
||||
export(NA_mic_)
|
||||
export(NA_rsi_)
|
||||
export(ab_atc)
|
||||
export(ab_atc_group1)
|
||||
export(ab_atc_group2)
|
||||
export(ab_cid)
|
||||
export(ab_class)
|
||||
export(ab_ddd)
|
||||
export(ab_ddd_units)
|
||||
export(ab_from_text)
|
||||
export(ab_group)
|
||||
export(ab_info)
|
||||
export(ab_loinc)
|
||||
export(ab_name)
|
||||
export(ab_property)
|
||||
export(ab_selector)
|
||||
export(ab_synonyms)
|
||||
export(ab_tradenames)
|
||||
export(ab_url)
|
||||
export(administrable_iv)
|
||||
export(administrable_per_os)
|
||||
export(age)
|
||||
export(age_groups)
|
||||
export(all_antimicrobials)
|
||||
export(aminoglycosides)
|
||||
export(aminopenicillins)
|
||||
export(anti_join_microorganisms)
|
||||
export(antifungals)
|
||||
export(antimicrobials_equal)
|
||||
export(antimycobacterials)
|
||||
export(as.ab)
|
||||
export(as.disk)
|
||||
export(as.mic)
|
||||
export(as.mo)
|
||||
export(as.rsi)
|
||||
export(atc_online_ddd)
|
||||
export(atc_online_ddd_units)
|
||||
export(atc_online_groups)
|
||||
export(atc_online_property)
|
||||
export(availability)
|
||||
export(betalactams)
|
||||
export(brmo)
|
||||
export(bug_drug_combinations)
|
||||
export(carbapenems)
|
||||
export(catalogue_of_life_version)
|
||||
export(cephalosporins)
|
||||
export(cephalosporins_1st)
|
||||
export(cephalosporins_2nd)
|
||||
export(cephalosporins_3rd)
|
||||
export(cephalosporins_4th)
|
||||
export(cephalosporins_5th)
|
||||
export(count_I)
|
||||
export(count_IR)
|
||||
export(count_R)
|
||||
export(count_S)
|
||||
export(count_SI)
|
||||
export(count_all)
|
||||
export(count_df)
|
||||
export(count_resistant)
|
||||
export(count_susceptible)
|
||||
export(custom_eucast_rules)
|
||||
export(custom_mdro_guideline)
|
||||
export(eucast_dosage)
|
||||
export(eucast_exceptional_phenotypes)
|
||||
export(eucast_rules)
|
||||
export(facet_rsi)
|
||||
export(filter_first_isolate)
|
||||
export(first_isolate)
|
||||
export(fluoroquinolones)
|
||||
export(full_join_microorganisms)
|
||||
export(g.test)
|
||||
export(geom_rsi)
|
||||
export(get_AMR_locale)
|
||||
export(get_episode)
|
||||
export(get_mo_source)
|
||||
export(ggplot_pca)
|
||||
export(ggplot_rsi)
|
||||
export(ggplot_rsi_predict)
|
||||
export(glycopeptides)
|
||||
export(guess_ab_col)
|
||||
export(inner_join_microorganisms)
|
||||
export(is.ab)
|
||||
export(is.disk)
|
||||
export(is.mic)
|
||||
export(is.mo)
|
||||
export(is.rsi)
|
||||
export(is.rsi.eligible)
|
||||
export(is_new_episode)
|
||||
export(italicise_taxonomy)
|
||||
export(italicize_taxonomy)
|
||||
export(key_antimicrobials)
|
||||
export(kurtosis)
|
||||
export(labels_rsi_count)
|
||||
export(left_join_microorganisms)
|
||||
export(like)
|
||||
export(lincosamides)
|
||||
export(lipoglycopeptides)
|
||||
export(macrolides)
|
||||
export(mdr_cmi2012)
|
||||
export(mdr_tb)
|
||||
export(mdro)
|
||||
export(mo_authors)
|
||||
export(mo_class)
|
||||
export(mo_domain)
|
||||
export(mo_failures)
|
||||
export(mo_family)
|
||||
export(mo_fullname)
|
||||
export(mo_genus)
|
||||
export(mo_gramstain)
|
||||
export(mo_info)
|
||||
export(mo_is_gram_negative)
|
||||
export(mo_is_gram_positive)
|
||||
export(mo_is_intrinsic_resistant)
|
||||
export(mo_is_yeast)
|
||||
export(mo_kingdom)
|
||||
export(mo_lpsn)
|
||||
export(mo_matching_score)
|
||||
export(mo_name)
|
||||
export(mo_order)
|
||||
export(mo_phylum)
|
||||
export(mo_property)
|
||||
export(mo_rank)
|
||||
export(mo_ref)
|
||||
export(mo_renamed)
|
||||
export(mo_shortname)
|
||||
export(mo_snomed)
|
||||
export(mo_species)
|
||||
export(mo_subspecies)
|
||||
export(mo_synonyms)
|
||||
export(mo_taxonomy)
|
||||
export(mo_type)
|
||||
export(mo_uncertainties)
|
||||
export(mo_url)
|
||||
export(mo_year)
|
||||
export(mrgn)
|
||||
export(n_rsi)
|
||||
export(not_intrinsic_resistant)
|
||||
export(oxazolidinones)
|
||||
export(pca)
|
||||
export(penicillins)
|
||||
export(polymyxins)
|
||||
export(proportion_I)
|
||||
export(proportion_IR)
|
||||
export(proportion_R)
|
||||
export(proportion_S)
|
||||
export(proportion_SI)
|
||||
export(proportion_df)
|
||||
export(quinolones)
|
||||
export(random_disk)
|
||||
export(random_mic)
|
||||
export(random_rsi)
|
||||
export(reset_AMR_locale)
|
||||
export(resistance)
|
||||
export(resistance_predict)
|
||||
export(right_join_microorganisms)
|
||||
export(rsi_df)
|
||||
export(rsi_predict)
|
||||
export(scale_rsi_colours)
|
||||
export(scale_y_percent)
|
||||
export(semi_join_microorganisms)
|
||||
export(set_AMR_locale)
|
||||
export(set_ab_names)
|
||||
export(set_mo_source)
|
||||
export(skewness)
|
||||
export(streptogramins)
|
||||
export(susceptibility)
|
||||
export(tetracyclines)
|
||||
export(theme_rsi)
|
||||
export(translate_AMR)
|
||||
export(trimethoprims)
|
||||
export(ureidopenicillins)
|
||||
importFrom(graphics,arrows)
|
||||
importFrom(graphics,axis)
|
||||
importFrom(graphics,barplot)
|
||||
importFrom(graphics,hist)
|
||||
importFrom(graphics,legend)
|
||||
importFrom(graphics,mtext)
|
||||
importFrom(graphics,plot)
|
||||
importFrom(graphics,points)
|
||||
importFrom(graphics,text)
|
||||
importFrom(stats,complete.cases)
|
||||
importFrom(stats,glm)
|
||||
importFrom(stats,lm)
|
||||
importFrom(stats,median)
|
||||
importFrom(stats,pchisq)
|
||||
importFrom(stats,prcomp)
|
||||
importFrom(stats,predict)
|
||||
importFrom(stats,qchisq)
|
||||
importFrom(stats,quantile)
|
||||
importFrom(stats,var)
|
||||
-133
@@ -1,133 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
# add new version numbers here, and add the rules themselves to "data-raw/eucast_rules.tsv" and rsi_translation
|
||||
# (sourcing "data-raw/_internals.R" will process the TSV file)
|
||||
EUCAST_VERSION_BREAKPOINTS <- list("11.0" = list(version_txt = "v11.0",
|
||||
year = 2021,
|
||||
title = "'EUCAST Clinical Breakpoint Tables'",
|
||||
url = "https://www.eucast.org/clinical_breakpoints/"),
|
||||
"10.0" = list(version_txt = "v10.0",
|
||||
year = 2020,
|
||||
title = "'EUCAST Clinical Breakpoint Tables'",
|
||||
url = "https://www.eucast.org/ast_of_bacteria/previous_versions_of_documents/"))
|
||||
EUCAST_VERSION_EXPERT_RULES <- list("3.1" = list(version_txt = "v3.1",
|
||||
year = 2016,
|
||||
title = "'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes'",
|
||||
url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"),
|
||||
"3.2" = list(version_txt = "v3.2",
|
||||
year = 2020,
|
||||
title = "'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes'",
|
||||
url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"),
|
||||
"3.3" = list(version_txt = "v3.3",
|
||||
year = 2021,
|
||||
title = "'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes'",
|
||||
url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"))
|
||||
|
||||
SNOMED_VERSION <- list(title = "Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS)",
|
||||
current_source = "US Edition of SNOMED CT from 1 September 2020",
|
||||
current_version = 12,
|
||||
current_oid = "2.16.840.1.114222.4.11.1009",
|
||||
value_set_name = "Microorganism",
|
||||
url = "https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009")
|
||||
|
||||
CATALOGUE_OF_LIFE <- list(
|
||||
year = 2019,
|
||||
version = "Catalogue of Life: {year} Annual Checklist",
|
||||
url_CoL = "http://www.catalogueoflife.org",
|
||||
url_LPSN = "https://lpsn.dsmz.de",
|
||||
yearmonth_LPSN = "5 October 2021"
|
||||
)
|
||||
|
||||
globalVariables(c(".rowid",
|
||||
"ab",
|
||||
"ab_txt",
|
||||
"affect_ab_name",
|
||||
"affect_mo_name",
|
||||
"angle",
|
||||
"antibiotic",
|
||||
"antibiotics",
|
||||
"atc_group1",
|
||||
"atc_group2",
|
||||
"base_ab",
|
||||
"code",
|
||||
"cols",
|
||||
"count",
|
||||
"data",
|
||||
"disk",
|
||||
"dosage",
|
||||
"dose",
|
||||
"dose_times",
|
||||
"fullname",
|
||||
"fullname_lower",
|
||||
"g_species",
|
||||
"genus",
|
||||
"gr",
|
||||
"group",
|
||||
"guideline",
|
||||
"hjust",
|
||||
"input",
|
||||
"intrinsic_resistant",
|
||||
"isolates",
|
||||
"lang",
|
||||
"language",
|
||||
"lookup",
|
||||
"method",
|
||||
"mic",
|
||||
"mic ",
|
||||
"microorganism",
|
||||
"microorganisms",
|
||||
"microorganisms.codes",
|
||||
"microorganisms.old",
|
||||
"mo",
|
||||
"name",
|
||||
"new",
|
||||
"observations",
|
||||
"old",
|
||||
"old_name",
|
||||
"pattern",
|
||||
"R",
|
||||
"rank_index",
|
||||
"reference.rule",
|
||||
"reference.rule_group",
|
||||
"reference.version",
|
||||
"rowid",
|
||||
"rsi",
|
||||
"rsi_translation",
|
||||
"rule_group",
|
||||
"rule_name",
|
||||
"se_max",
|
||||
"se_min",
|
||||
"species",
|
||||
"species_id",
|
||||
"total",
|
||||
"txt",
|
||||
"type",
|
||||
"value",
|
||||
"varname",
|
||||
"xvar",
|
||||
"y",
|
||||
"year",
|
||||
"yvar"))
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@@ -1,591 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Transform Input to an Antibiotic ID
|
||||
#'
|
||||
#' Use this function to determine the antibiotic code of one or more antibiotics. The data set [antibiotics] will be searched for abbreviations, official names and synonyms (brand names).
|
||||
#' @param x a [character] vector to determine to antibiotic ID
|
||||
#' @param flag_multiple_results a [logical] to indicate whether a note should be printed to the console that probably more than one antibiotic code or name can be retrieved from a single input value.
|
||||
#' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
|
||||
#' @param ... arguments passed on to internal functions
|
||||
#' @rdname as.ab
|
||||
#' @inheritSection WHOCC WHOCC
|
||||
#' @details All entries in the [antibiotics] data set have three different identifiers: a human readable EARS-Net code (column `ab`, used by ECDC and WHONET), an ATC code (column `atc`, used by WHO), and a CID code (column `cid`, Compound ID, used by PubChem). The data set contains more than 5,000 official brand names from many different countries, as found in PubChem. Not that some drugs contain multiple ATC codes.
|
||||
#'
|
||||
#' All these properties will be searched for the user input. The [as.ab()] can correct for different forms of misspelling:
|
||||
#'
|
||||
#' * Wrong spelling of drug names (such as "tobramicin" or "gentamycin"), which corrects for most audible similarities such as f/ph, x/ks, c/z/s, t/th, etc.
|
||||
#' * Too few or too many vowels or consonants
|
||||
#' * Switching two characters (such as "mreopenem", often the case in clinical data, when doctors typed too fast)
|
||||
#' * Digitalised paper records, leaving artefacts like 0/o/O (zero and O's), B/8, n/r, etc.
|
||||
#'
|
||||
#' Use the [`ab_*`][ab_property()] functions to get properties based on the returned antibiotic ID, see *Examples*.
|
||||
#'
|
||||
#' Note: the [as.ab()] and [`ab_*`][ab_property()] functions may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems.
|
||||
#' @section Source:
|
||||
#' World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/}
|
||||
#'
|
||||
#' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm}
|
||||
#' @aliases ab
|
||||
#' @return A [character] [vector] with additional class [`ab`]
|
||||
#' @seealso
|
||||
#' * [antibiotics] for the [data.frame] that is being used to determine ATCs
|
||||
#' * [ab_from_text()] for a function to retrieve antimicrobial drugs from clinical text (from health care records)
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @export
|
||||
#' @examples
|
||||
#' # these examples all return "ERY", the ID of erythromycin:
|
||||
#' as.ab("J01FA01")
|
||||
#' as.ab("J 01 FA 01")
|
||||
#' as.ab("Erythromycin")
|
||||
#' as.ab("eryt")
|
||||
#' as.ab(" eryt 123")
|
||||
#' as.ab("ERYT")
|
||||
#' as.ab("ERY")
|
||||
#' as.ab("eritromicine") # spelled wrong, yet works
|
||||
#' as.ab("Erythrocin") # trade name
|
||||
#' as.ab("Romycin") # trade name
|
||||
#'
|
||||
#' # spelling from different languages and dyslexia are no problem
|
||||
#' ab_atc("ceftriaxon")
|
||||
#' ab_atc("cephtriaxone") # small spelling error
|
||||
#' ab_atc("cephthriaxone") # or a bit more severe
|
||||
#' ab_atc("seephthriaaksone") # and even this works
|
||||
#'
|
||||
#' # use ab_* functions to get a specific properties (see ?ab_property);
|
||||
#' # they use as.ab() internally:
|
||||
#' ab_name("J01FA01") # "Erythromycin"
|
||||
#' ab_name("eryt") # "Erythromycin"
|
||||
#' \donttest{
|
||||
#' if (require("dplyr")) {
|
||||
#'
|
||||
#' # you can quickly rename <rsi> columns using dplyr >= 1.0.0:
|
||||
#' example_isolates %>%
|
||||
#' rename_with(as.ab, where(is.rsi))
|
||||
#'
|
||||
#' }
|
||||
#' }
|
||||
as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
|
||||
meet_criteria(x, allow_class = c("character", "numeric", "integer", "factor"), allow_NA = TRUE)
|
||||
meet_criteria(flag_multiple_results, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(info, allow_class = "logical", has_length = 1)
|
||||
|
||||
check_dataset_integrity()
|
||||
|
||||
if (is.ab(x)) {
|
||||
return(x)
|
||||
}
|
||||
if (all(x %in% c(AB_lookup$ab, NA))) {
|
||||
# all valid AB codes, but not yet right class
|
||||
return(set_clean_class(x,
|
||||
new_class = c("ab", "character")))
|
||||
}
|
||||
|
||||
initial_search <- is.null(list(...)$initial_search)
|
||||
already_regex <- isTRUE(list(...)$already_regex)
|
||||
fast_mode <- isTRUE(list(...)$fast_mode)
|
||||
|
||||
x_bak <- x
|
||||
x <- toupper(x)
|
||||
x_nonNA <- x[!is.na(x)]
|
||||
|
||||
# remove diacritics
|
||||
x <- iconv(x, from = "UTF-8", to = "ASCII//TRANSLIT")
|
||||
x <- gsub('"', "", x, fixed = TRUE)
|
||||
x <- gsub("(specimen|specimen date|specimen_date|spec_date|gender|^dates?$)", "", x, ignore.case = TRUE, perl = TRUE)
|
||||
# penicillin is a special case: we call it so, but then mean benzylpenicillin
|
||||
x[x %like_case% "^PENICILLIN" & x %unlike_case% "[ /+-]"] <- "benzylpenicillin"
|
||||
x_bak_clean <- x
|
||||
if (already_regex == FALSE) {
|
||||
x_bak_clean <- generalise_antibiotic_name(x_bak_clean)
|
||||
}
|
||||
|
||||
x <- unique(x_bak_clean) # this means that every x is in fact generalise_antibiotic_name(x)
|
||||
x_new <- rep(NA_character_, length(x))
|
||||
x_unknown <- character(0)
|
||||
|
||||
note_if_more_than_one_found <- function(found, index, from_text) {
|
||||
if (initial_search == TRUE & isTRUE(length(from_text) > 1)) {
|
||||
abnames <- ab_name(from_text, tolower = TRUE, initial_search = FALSE)
|
||||
if (ab_name(found[1L], language = NULL) %like% "(clavulanic acid|avibactam)") {
|
||||
abnames <- abnames[!abnames %in% c("clavulanic acid", "avibactam")]
|
||||
}
|
||||
if (length(abnames) > 1) {
|
||||
message_("More than one result was found for item ", index, ": ",
|
||||
vector_and(abnames, quotes = FALSE))
|
||||
}
|
||||
}
|
||||
found[1L]
|
||||
}
|
||||
|
||||
# Fill in names, AB codes, CID codes and ATC codes directly (`x` is already clean and uppercase)
|
||||
known_names <- x %in% AB_lookup$generalised_name
|
||||
x_new[known_names] <- AB_lookup$ab[match(x[known_names], AB_lookup$generalised_name)]
|
||||
known_codes_ab <- x %in% AB_lookup$ab
|
||||
known_codes_atc <- vapply(FUN.VALUE = logical(1), x, function(x_) x_ %in% unlist(AB_lookup$atc), USE.NAMES = FALSE)
|
||||
known_codes_cid <- x %in% AB_lookup$cid
|
||||
x_new[known_codes_ab] <- AB_lookup$ab[match(x[known_codes_ab], AB_lookup$ab)]
|
||||
x_new[known_codes_atc] <- AB_lookup$ab[vapply(FUN.VALUE = integer(1),
|
||||
x[known_codes_atc],
|
||||
function(x_) which(vapply(FUN.VALUE = logical(1),
|
||||
AB_lookup$atc,
|
||||
function(atc) x_ %in% atc))[1L],
|
||||
USE.NAMES = FALSE)]
|
||||
x_new[known_codes_cid] <- AB_lookup$ab[match(x[known_codes_cid], AB_lookup$cid)]
|
||||
already_known <- known_names | known_codes_ab | known_codes_atc | known_codes_cid
|
||||
|
||||
if (initial_search == TRUE & sum(already_known) < length(x)) {
|
||||
progress <- progress_ticker(n = sum(!already_known), n_min = 25, print = info) # start if n >= 25
|
||||
on.exit(close(progress))
|
||||
}
|
||||
|
||||
for (i in which(!already_known)) {
|
||||
|
||||
if (initial_search == TRUE) {
|
||||
progress$tick()
|
||||
}
|
||||
|
||||
if (is.na(x[i]) | is.null(x[i])) {
|
||||
next
|
||||
}
|
||||
if (identical(x[i], "") |
|
||||
# prevent "bacteria" from coercing to TMP, since Bacterial is a brand name of it:
|
||||
identical(tolower(x[i]), "bacteria")) {
|
||||
x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
|
||||
next
|
||||
}
|
||||
|
||||
if (fast_mode == FALSE && flag_multiple_results == TRUE && x[i] %like% "[ ]") {
|
||||
from_text <- tryCatch(suppressWarnings(ab_from_text(x[i], initial_search = FALSE, translate_ab = FALSE)[[1]]),
|
||||
error = function(e) character(0))
|
||||
} else {
|
||||
from_text <- character(0)
|
||||
}
|
||||
|
||||
# old code for phenoxymethylpenicillin (Peni V)
|
||||
if (x[i] == "PNV") {
|
||||
x_new[i] <- "PHN"
|
||||
next
|
||||
}
|
||||
|
||||
# exact LOINC code
|
||||
loinc_found <- unlist(lapply(AB_lookup$generalised_loinc,
|
||||
function(s) x[i] %in% s))
|
||||
found <- antibiotics$ab[loinc_found == TRUE]
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
|
||||
# exact synonym
|
||||
synonym_found <- unlist(lapply(AB_lookup$generalised_synonyms,
|
||||
function(s) x[i] %in% s))
|
||||
found <- antibiotics$ab[synonym_found == TRUE]
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
|
||||
# exact abbreviation
|
||||
abbr_found <- unlist(lapply(AB_lookup$generalised_abbreviations,
|
||||
# require at least 2 characters for abbreviations
|
||||
function(s) x[i] %in% s & nchar(x[i]) >= 2))
|
||||
found <- antibiotics$ab[abbr_found == TRUE]
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
|
||||
# length of input is quite long, and Levenshtein distance is only max 2
|
||||
if (nchar(x[i]) >= 10) {
|
||||
levenshtein <- as.double(utils::adist(x[i], AB_lookup$generalised_name))
|
||||
if (any(levenshtein <= 2)) {
|
||||
found <- AB_lookup$ab[which(levenshtein <= 2)]
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
}
|
||||
|
||||
# allow characters that resemble others, but only continue when having more than 3 characters
|
||||
if (nchar(x[i]) <= 3) {
|
||||
x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
|
||||
next
|
||||
}
|
||||
x_spelling <- x[i]
|
||||
if (already_regex == FALSE) {
|
||||
|
||||
x_spelling <- gsub("[IY]+", "[IY]+", x_spelling, perl = TRUE)
|
||||
x_spelling <- gsub("(C|K|Q|QU|S|Z|X|KS)+", "(C|K|Q|QU|S|Z|X|KS)+", x_spelling, perl = TRUE)
|
||||
x_spelling <- gsub("(PH|F|V)+", "(PH|F|V)+", x_spelling, perl = TRUE)
|
||||
x_spelling <- gsub("(TH|T)+", "(TH|T)+", x_spelling, perl = TRUE)
|
||||
x_spelling <- gsub("A+", "A+", x_spelling, perl = TRUE)
|
||||
x_spelling <- gsub("E+", "E+", x_spelling, perl = TRUE)
|
||||
x_spelling <- gsub("O+", "O+", x_spelling, perl = TRUE)
|
||||
# allow any ending of -in/-ine and -im/-ime
|
||||
x_spelling <- gsub("(\\[IY\\]\\+(N|M)|\\[IY\\]\\+(N|M)E\\+?)$", "[IY]+(N|M)E*", x_spelling, perl = TRUE)
|
||||
# allow any ending of -ol/-ole
|
||||
x_spelling <- gsub("(O\\+L|O\\+LE\\+)$", "O+LE*", x_spelling, perl = TRUE)
|
||||
# allow any ending of -on/-one
|
||||
x_spelling <- gsub("(O\\+N|O\\+NE\\+)$", "O+NE*", x_spelling, perl = TRUE)
|
||||
# replace multiple same characters to single one with '+', like "ll" -> "l+"
|
||||
x_spelling <- gsub("(.)\\1+", "\\1+", x_spelling, perl = TRUE)
|
||||
# replace spaces and slashes with a possibility on both
|
||||
x_spelling <- gsub("[ /]", "( .*|.*/)", x_spelling, perl = TRUE)
|
||||
# correct for digital reading text (OCR)
|
||||
x_spelling <- gsub("[NRD8B]", "[NRD8B]", x_spelling, perl = TRUE)
|
||||
x_spelling <- gsub("(O|0)", "(O|0)+", x_spelling, perl = TRUE)
|
||||
x_spelling <- gsub("++", "+", x_spelling, fixed = TRUE)
|
||||
}
|
||||
|
||||
# try if name starts with it
|
||||
found <- antibiotics[which(AB_lookup$generalised_name %like% paste0("^", x_spelling)), ]$ab
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
# try if name ends with it
|
||||
found <- antibiotics[which(AB_lookup$generalised_name %like% paste0(x_spelling, "$")), ]$ab
|
||||
if (nchar(x[i]) >= 4 & length(found) > 0) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
|
||||
# and try if any synonym starts with it
|
||||
synonym_found <- unlist(lapply(AB_lookup$generalised_synonyms,
|
||||
function(s) any(s %like% paste0("^", x_spelling))))
|
||||
found <- antibiotics$ab[synonym_found == TRUE]
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
|
||||
# INITIAL SEARCH - More uncertain results ----
|
||||
|
||||
if (initial_search == TRUE && fast_mode == FALSE) {
|
||||
# only run on first try
|
||||
|
||||
# try by removing all spaces
|
||||
if (x[i] %like% " ") {
|
||||
found <- suppressWarnings(as.ab(gsub(" +", "", x[i], perl = TRUE), initial_search = FALSE))
|
||||
if (length(found) > 0 & !is.na(found)) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
}
|
||||
|
||||
# try by removing all spaces and numbers
|
||||
if (x[i] %like% " " | x[i] %like% "[0-9]") {
|
||||
found <- suppressWarnings(as.ab(gsub("[ 0-9]", "", x[i], perl = TRUE), initial_search = FALSE))
|
||||
if (length(found) > 0 & !is.na(found)) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
}
|
||||
|
||||
# transform back from other languages and try again
|
||||
x_translated <- paste(lapply(strsplit(x[i], "[^A-Z0-9]"),
|
||||
function(y) {
|
||||
for (i in seq_len(length(y))) {
|
||||
for (lang in LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED != "en"]) {
|
||||
y[i] <- ifelse(tolower(y[i]) %in% tolower(TRANSLATIONS[, lang, drop = TRUE]),
|
||||
TRANSLATIONS[which(tolower(TRANSLATIONS[, lang, drop = TRUE]) == tolower(y[i]) &
|
||||
!isFALSE(TRANSLATIONS$fixed)), "pattern"],
|
||||
y[i])
|
||||
}
|
||||
}
|
||||
generalise_antibiotic_name(y)
|
||||
})[[1]],
|
||||
collapse = "/")
|
||||
x_translated_guess <- suppressWarnings(as.ab(x_translated, initial_search = FALSE))
|
||||
if (!is.na(x_translated_guess)) {
|
||||
x_new[i] <- x_translated_guess
|
||||
next
|
||||
}
|
||||
|
||||
# now also try to coerce brandname combinations like "Amoxy/clavulanic acid"
|
||||
x_translated <- paste(lapply(strsplit(x_translated, "[^A-Z0-9 ]"),
|
||||
function(y) {
|
||||
for (i in seq_len(length(y))) {
|
||||
y_name <- suppressWarnings(ab_name(y[i], language = NULL, initial_search = FALSE))
|
||||
y[i] <- ifelse(!is.na(y_name),
|
||||
y_name,
|
||||
y[i])
|
||||
}
|
||||
generalise_antibiotic_name(y)
|
||||
})[[1]],
|
||||
collapse = "/")
|
||||
x_translated_guess <- suppressWarnings(as.ab(x_translated, initial_search = FALSE))
|
||||
if (!is.na(x_translated_guess)) {
|
||||
x_new[i] <- x_translated_guess
|
||||
next
|
||||
}
|
||||
|
||||
# try by removing all trailing capitals
|
||||
if (x[i] %like_case% "[a-z]+[A-Z]+$") {
|
||||
found <- suppressWarnings(as.ab(gsub("[A-Z]+$", "", x[i], perl = TRUE), initial_search = FALSE))
|
||||
if (!is.na(found)) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
}
|
||||
|
||||
# keep only letters
|
||||
found <- suppressWarnings(as.ab(gsub("[^A-Z]", "", x[i], perl = TRUE), initial_search = FALSE))
|
||||
if (!is.na(found)) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
|
||||
# try from a bigger text, like from a health care record, see ?ab_from_text
|
||||
# already calculated above if flag_multiple_results = TRUE
|
||||
if (flag_multiple_results == TRUE) {
|
||||
found <- from_text[1L]
|
||||
} else {
|
||||
found <- tryCatch(suppressWarnings(ab_from_text(x[i], initial_search = FALSE, translate_ab = FALSE)[[1]][1L]),
|
||||
error = function(e) NA_character_)
|
||||
}
|
||||
if (!is.na(found)) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
|
||||
# first 5 except for cephalosporins, then first 7 (those cephalosporins all start quite the same!)
|
||||
found <- suppressWarnings(as.ab(substr(x[i], 1, 5), initial_search = FALSE))
|
||||
if (!is.na(found) && ab_group(found, initial_search = FALSE) %unlike% "cephalosporins") {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
found <- suppressWarnings(as.ab(substr(x[i], 1, 7), initial_search = FALSE))
|
||||
if (!is.na(found)) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
|
||||
# make all consonants facultative
|
||||
search_str <- gsub("([BCDFGHJKLMNPQRSTVWXZ])", "\\1*", x[i], perl = TRUE)
|
||||
found <- suppressWarnings(as.ab(search_str, initial_search = FALSE, already_regex = TRUE))
|
||||
# keep at least 4 normal characters
|
||||
if (nchar(gsub(".\\*", "", search_str, perl = TRUE)) < 4) {
|
||||
found <- NA
|
||||
}
|
||||
if (!is.na(found)) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
|
||||
# make all vowels facultative
|
||||
search_str <- gsub("([AEIOUY])", "\\1*", x[i], perl = TRUE)
|
||||
found <- suppressWarnings(as.ab(search_str, initial_search = FALSE, already_regex = TRUE))
|
||||
# keep at least 5 normal characters
|
||||
if (nchar(gsub(".\\*", "", search_str, perl = TRUE)) < 5) {
|
||||
found <- NA
|
||||
}
|
||||
if (!is.na(found)) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
|
||||
# allow misspelling of vowels
|
||||
x_spelling <- gsub("A+", "[AEIOU]+", x_spelling, fixed = TRUE)
|
||||
x_spelling <- gsub("E+", "[AEIOU]+", x_spelling, fixed = TRUE)
|
||||
x_spelling <- gsub("I+", "[AEIOU]+", x_spelling, fixed = TRUE)
|
||||
x_spelling <- gsub("O+", "[AEIOU]+", x_spelling, fixed = TRUE)
|
||||
x_spelling <- gsub("U+", "[AEIOU]+", x_spelling, fixed = TRUE)
|
||||
found <- suppressWarnings(as.ab(x_spelling, initial_search = FALSE, already_regex = TRUE))
|
||||
if (!is.na(found)) {
|
||||
x_new[i] <- note_if_more_than_one_found(found, i, from_text)
|
||||
next
|
||||
}
|
||||
|
||||
# try with switched character, like "mreopenem"
|
||||
for (j in seq_len(nchar(x[i]))) {
|
||||
x_switched <- paste0(
|
||||
# beginning part:
|
||||
substr(x[i], 1, j - 1),
|
||||
# here is the switching of 2 characters:
|
||||
substr(x[i], j + 1, j + 1),
|
||||
substr(x[i], j, j),
|
||||
# ending part:
|
||||
substr(x[i], j + 2, nchar(x[i])))
|
||||
found <- suppressWarnings(as.ab(x_switched, initial_search = FALSE))
|
||||
if (!is.na(found)) {
|
||||
break
|
||||
}
|
||||
}
|
||||
if (!is.na(found)) {
|
||||
x_new[i] <- found[1L]
|
||||
next
|
||||
}
|
||||
|
||||
} # end of initial_search = TRUE
|
||||
|
||||
# not found
|
||||
x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
|
||||
}
|
||||
|
||||
if (initial_search == TRUE & sum(already_known) < length(x)) {
|
||||
close(progress)
|
||||
}
|
||||
|
||||
# take failed ATC codes apart from rest
|
||||
x_unknown_ATCs <- x_unknown[x_unknown %like% "[A-Z][0-9][0-9][A-Z][A-Z][0-9][0-9]"]
|
||||
x_unknown <- x_unknown[!x_unknown %in% x_unknown_ATCs]
|
||||
if (length(x_unknown_ATCs) > 0 & fast_mode == FALSE) {
|
||||
warning_("in `as.ab()`: these ATC codes are not (yet) in the antibiotics data set: ",
|
||||
vector_and(x_unknown_ATCs), ".")
|
||||
}
|
||||
|
||||
if (length(x_unknown) > 0 & fast_mode == FALSE) {
|
||||
warning_("in `as.ab()`: these values could not be coerced to a valid antimicrobial ID: ",
|
||||
vector_and(x_unknown), ".")
|
||||
}
|
||||
|
||||
x_result <- x_new[match(x_bak_clean, x)]
|
||||
if (length(x_result) == 0) {
|
||||
x_result <- NA_character_
|
||||
}
|
||||
|
||||
set_clean_class(x_result,
|
||||
new_class = c("ab", "character"))
|
||||
}
|
||||
|
||||
#' @rdname as.ab
|
||||
#' @export
|
||||
is.ab <- function(x) {
|
||||
inherits(x, "ab")
|
||||
}
|
||||
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
pillar_shaft.ab <- function(x, ...) {
|
||||
out <- trimws(format(x))
|
||||
out[is.na(x)] <- font_na(NA)
|
||||
create_pillar_column(out, align = "left", min_width = 4)
|
||||
}
|
||||
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
type_sum.ab <- function(x, ...) {
|
||||
"ab"
|
||||
}
|
||||
|
||||
#' @method print ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
print.ab <- function(x, ...) {
|
||||
cat("Class <ab>\n")
|
||||
print(as.character(x), quote = FALSE)
|
||||
}
|
||||
|
||||
#' @method as.data.frame ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
as.data.frame.ab <- function(x, ...) {
|
||||
nm <- deparse1(substitute(x))
|
||||
if (!"nm" %in% names(list(...))) {
|
||||
as.data.frame.vector(as.ab(x), ..., nm = nm)
|
||||
} else {
|
||||
as.data.frame.vector(as.ab(x), ...)
|
||||
}
|
||||
}
|
||||
#' @method [ ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[.ab" <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
#' @method [[ ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[[.ab" <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
#' @method [<- ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[<-.ab" <- function(i, j, ..., value) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(i)
|
||||
return_after_integrity_check(y, "antimicrobial code", antibiotics$ab)
|
||||
}
|
||||
#' @method [[<- ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[[<-.ab" <- function(i, j, ..., value) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(i)
|
||||
return_after_integrity_check(y, "antimicrobial code", antibiotics$ab)
|
||||
}
|
||||
#' @method c ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
c.ab <- function(...) {
|
||||
x <- list(...)[[1L]]
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
return_after_integrity_check(y, "antimicrobial code", antibiotics$ab)
|
||||
}
|
||||
|
||||
#' @method unique ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
unique.ab <- function(x, incomparables = FALSE, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
|
||||
#' @method rep ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
rep.ab <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
|
||||
generalise_antibiotic_name <- function(x) {
|
||||
x <- toupper(x)
|
||||
# remove suffices
|
||||
x <- gsub("_(MIC|RSI|DIS[CK])$", "", x, perl = TRUE)
|
||||
# remove disk concentrations, like LVX_NM -> LVX
|
||||
x <- gsub("_[A-Z]{2}[0-9_.]{0,3}$", "", x, perl = TRUE)
|
||||
# remove part between brackets if that's followed by another string
|
||||
x <- gsub("(.*)+ [(].*[)]", "\\1", x)
|
||||
# keep only max 1 space
|
||||
x <- trimws2(gsub(" +", " ", x, perl = TRUE))
|
||||
# non-character, space or number should be a slash
|
||||
x <- gsub("[^A-Z0-9 -]", "/", x, perl = TRUE)
|
||||
# spaces around non-characters must be removed: amox + clav -> amox/clav
|
||||
x <- gsub("(.*[A-Z0-9]) ([^A-Z0-9].*)", "\\1\\2", x, perl = TRUE)
|
||||
x <- gsub("(.*[^A-Z0-9]) ([A-Z0-9].*)", "\\1\\2", x, perl = TRUE)
|
||||
# remove hyphen after a starting "co"
|
||||
x <- gsub("^CO-", "CO", x, perl = TRUE)
|
||||
# replace operators with a space
|
||||
x <- gsub("(/| AND | WITH | W/|[+]|[-])+", " ", x, perl = TRUE)
|
||||
x
|
||||
}
|
||||
@@ -1,218 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Retrieve Antimicrobial Drug Names and Doses from Clinical Text
|
||||
#'
|
||||
#' Use this function on e.g. clinical texts from health care records. It returns a [list] with all antimicrobial drugs, doses and forms of administration found in the texts.
|
||||
#' @param text text to analyse
|
||||
#' @param type type of property to search for, either `"drug"`, `"dose"` or `"administration"`, see *Examples*
|
||||
#' @param collapse a [character] to pass on to `paste(, collapse = ...)` to only return one [character] per element of `text`, see *Examples*
|
||||
#' @param translate_ab if `type = "drug"`: a column name of the [antibiotics] data set to translate the antibiotic abbreviations to, using [ab_property()]. Defaults to `FALSE`. Using `TRUE` is equal to using "name".
|
||||
#' @param thorough_search a [logical] to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to `TRUE` will take considerably more time than when using `FALSE`. At default, it will turn `TRUE` when all input elements contain a maximum of three words.
|
||||
#' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
|
||||
#' @param ... arguments passed on to [as.ab()]
|
||||
#' @details This function is also internally used by [as.ab()], although it then only searches for the first drug name and will throw a note if more drug names could have been returned. Note: the [as.ab()] function may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems.
|
||||
#'
|
||||
#' ## Argument `type`
|
||||
#' At default, the function will search for antimicrobial drug names. All text elements will be searched for official names, ATC codes and brand names. As it uses [as.ab()] internally, it will correct for misspelling.
|
||||
#'
|
||||
#' With `type = "dose"` (or similar, like "dosing", "doses"), all text elements will be searched for [numeric] values that are higher than 100 and do not resemble years. The output will be [numeric]. It supports any unit (g, mg, IE, etc.) and multiple values in one clinical text, see *Examples*.
|
||||
#'
|
||||
#' With `type = "administration"` (or abbreviations, like "admin", "adm"), all text elements will be searched for a form of drug administration. It supports the following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal and vaginal. Abbreviations for oral (such as 'po', 'per os') will become "oral", all values for intravenous (such as 'iv', 'intraven') will become "iv". It supports multiple values in one clinical text, see *Examples*.
|
||||
#'
|
||||
#' ## Argument `collapse`
|
||||
#' Without using `collapse`, this function will return a [list]. This can be convenient to use e.g. inside a `mutate()`):\cr
|
||||
#' `df %>% mutate(abx = ab_from_text(clinical_text))`
|
||||
#'
|
||||
#' The returned AB codes can be transformed to official names, groups, etc. with all [`ab_*`][ab_property()] functions such as [ab_name()] and [ab_group()], or by using the `translate_ab` argument.
|
||||
#'
|
||||
#' With using `collapse`, this function will return a [character]:\cr
|
||||
#' `df %>% mutate(abx = ab_from_text(clinical_text, collapse = "|"))`
|
||||
#' @export
|
||||
#' @return A [list], or a [character] if `collapse` is not `NULL`
|
||||
#' @examples
|
||||
#' # mind the bad spelling of amoxicillin in this line,
|
||||
#' # straight from a true health care record:
|
||||
#' ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds")
|
||||
#'
|
||||
#' ab_from_text("500 mg amoxi po and 400mg cipro iv")
|
||||
#' ab_from_text("500 mg amoxi po and 400mg cipro iv", type = "dose")
|
||||
#' ab_from_text("500 mg amoxi po and 400mg cipro iv", type = "admin")
|
||||
#'
|
||||
#' ab_from_text("500 mg amoxi po and 400mg cipro iv", collapse = ", ")
|
||||
#' \donttest{
|
||||
#' # if you want to know which antibiotic groups were administered, do e.g.:
|
||||
#' abx <- ab_from_text("500 mg amoxi po and 400mg cipro iv")
|
||||
#' ab_group(abx[[1]])
|
||||
#'
|
||||
#' if (require("dplyr")) {
|
||||
#' tibble(clinical_text = c("given 400mg cipro and 500 mg amox",
|
||||
#' "started on doxy iv today")) %>%
|
||||
#' mutate(abx_codes = ab_from_text(clinical_text),
|
||||
#' abx_doses = ab_from_text(clinical_text, type = "doses"),
|
||||
#' abx_admin = ab_from_text(clinical_text, type = "admin"),
|
||||
#' abx_coll = ab_from_text(clinical_text, collapse = "|"),
|
||||
#' abx_coll_names = ab_from_text(clinical_text,
|
||||
#' collapse = "|",
|
||||
#' translate_ab = "name"),
|
||||
#' abx_coll_doses = ab_from_text(clinical_text,
|
||||
#' type = "doses",
|
||||
#' collapse = "|"),
|
||||
#' abx_coll_admin = ab_from_text(clinical_text,
|
||||
#' type = "admin",
|
||||
#' collapse = "|"))
|
||||
#'
|
||||
#' }
|
||||
#' }
|
||||
ab_from_text <- function(text,
|
||||
type = c("drug", "dose", "administration"),
|
||||
collapse = NULL,
|
||||
translate_ab = FALSE,
|
||||
thorough_search = NULL,
|
||||
info = interactive(),
|
||||
...) {
|
||||
if (missing(type)) {
|
||||
type <- type[1L]
|
||||
}
|
||||
|
||||
meet_criteria(text)
|
||||
meet_criteria(type, allow_class = "character", has_length = 1)
|
||||
meet_criteria(collapse, has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(translate_ab, allow_NULL = FALSE) # get_translate_ab() will be more informative about what's allowed
|
||||
meet_criteria(thorough_search, allow_class = "logical", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(info, allow_class = "logical", has_length = 1)
|
||||
|
||||
type <- tolower(trimws(type))
|
||||
|
||||
text <- tolower(as.character(text))
|
||||
text_split_all <- strsplit(text, "[ ;.,:\\|]")
|
||||
progress <- progress_ticker(n = length(text_split_all), n_min = 5, print = info)
|
||||
on.exit(close(progress))
|
||||
|
||||
if (type %like% "(drug|ab|anti)") {
|
||||
|
||||
translate_ab <- get_translate_ab(translate_ab)
|
||||
|
||||
if (isTRUE(thorough_search) |
|
||||
(isTRUE(is.null(thorough_search)) & max(vapply(FUN.VALUE = double(1), text_split_all, length), na.rm = TRUE) <= 3)) {
|
||||
text_split_all <- text_split_all[nchar(text_split_all) >= 4 & grepl("[a-z]+", text_split_all)]
|
||||
result <- lapply(text_split_all, function(text_split) {
|
||||
progress$tick()
|
||||
suppressWarnings(
|
||||
out <- as.ab(text_split, ...)
|
||||
)
|
||||
})
|
||||
|
||||
} else {
|
||||
# no thorough search
|
||||
abbr <- unlist(antibiotics$abbreviations)
|
||||
abbr <- abbr[nchar(abbr) >= 4]
|
||||
names_atc <- substr(c(antibiotics$name, antibiotics$atc), 1, 5)
|
||||
synonyms <- unlist(antibiotics$synonyms)
|
||||
synonyms <- synonyms[nchar(synonyms) >= 4]
|
||||
# regular expression must not be too long, so split synonyms in two:
|
||||
synonyms_part1 <- synonyms[seq_len(0.5 * length(synonyms))]
|
||||
synonyms_part2 <- synonyms[!synonyms %in% synonyms_part1]
|
||||
to_regex <- function(x) {
|
||||
paste0("^(",
|
||||
paste0(unique(gsub("[^a-z0-9]+", "", sort(tolower(x)))), collapse = "|"),
|
||||
").*")
|
||||
}
|
||||
result <- lapply(text_split_all, function(text_split) {
|
||||
progress$tick()
|
||||
suppressWarnings(
|
||||
out <- as.ab(unique(c(text_split[text_split %like_case% to_regex(abbr)],
|
||||
text_split[text_split %like_case% to_regex(names_atc)],
|
||||
text_split[text_split %like_case% to_regex(synonyms_part1)],
|
||||
text_split[text_split %like_case% to_regex(synonyms_part2)])
|
||||
),
|
||||
...)
|
||||
)
|
||||
})
|
||||
}
|
||||
|
||||
close(progress)
|
||||
|
||||
result <- lapply(result, function(out) {
|
||||
out <- out[!is.na(out)]
|
||||
if (length(out) == 0) {
|
||||
as.ab(NA)
|
||||
} else {
|
||||
if (!isFALSE(translate_ab)) {
|
||||
out <- ab_property(out, property = translate_ab, initial_search = FALSE)
|
||||
}
|
||||
out
|
||||
}
|
||||
|
||||
})
|
||||
|
||||
} else if (type %like% "dos") {
|
||||
text_split_all <- strsplit(text, " ")
|
||||
result <- lapply(text_split_all, function(text_split) {
|
||||
text_split <- text_split[text_split %like% "^[0-9]{2,}(/[0-9]+)?[a-z]*$"]
|
||||
# only left part of "/", like 500 in "500/125"
|
||||
text_split <- gsub("/.*", "", text_split)
|
||||
text_split <- gsub(",", ".", text_split, fixed = TRUE) # foreign system using comma as decimal sep
|
||||
text_split <- as.double(gsub("[^0-9.]", "", text_split))
|
||||
# minimal 100 units/mg and no years that unlikely doses
|
||||
text_split <- text_split[text_split >= 100 & !text_split %in% c(1951:1999, 2001:2049)]
|
||||
|
||||
if (length(text_split) > 0) {
|
||||
text_split
|
||||
} else {
|
||||
NA_real_
|
||||
}
|
||||
})
|
||||
|
||||
} else if (type %like% "adm") {
|
||||
result <- lapply(text_split_all, function(text_split) {
|
||||
text_split <- text_split[text_split %like% "(^iv$|intraven|^po$|per os|oral|implant|inhal|instill|nasal|paren|rectal|sublingual|buccal|trans.*dermal|vaginal)"]
|
||||
if (length(text_split) > 0) {
|
||||
text_split <- gsub("(^po$|.*per os.*)", "oral", text_split)
|
||||
text_split <- gsub("(^iv$|.*intraven.*)", "iv", text_split)
|
||||
text_split
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
})
|
||||
|
||||
} else {
|
||||
stop_("`type` must be either 'drug', 'dose' or 'administration'")
|
||||
}
|
||||
|
||||
# collapse text if needed
|
||||
if (!is.null(collapse)) {
|
||||
result <- vapply(FUN.VALUE = character(1), result, function(x) {
|
||||
if (length(x) == 1 & all(is.na(x))) {
|
||||
NA_character_
|
||||
} else {
|
||||
paste0(x, collapse = collapse)
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
result
|
||||
|
||||
}
|
||||
-451
@@ -1,451 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Get Properties of an Antibiotic
|
||||
#'
|
||||
#' Use these functions to return a specific property of an antibiotic from the [antibiotics] data set. All input values will be evaluated internally with [as.ab()].
|
||||
#' @param x any (vector of) text that can be coerced to a valid antibiotic code with [as.ab()]
|
||||
#' @param tolower a [logical] to indicate whether the first [character] of every output should be transformed to a lower case [character]. This will lead to e.g. "polymyxin B" and not "polymyxin b".
|
||||
#' @param property one of the column names of one of the [antibiotics] data set: `vector_or(colnames(antibiotics), sort = FALSE)`.
|
||||
#' @param language language of the returned text, defaults to system language (see [get_AMR_locale()]) and can also be set with `getOption("AMR_locale")`. Use `language = NULL` or `language = ""` to prevent translation.
|
||||
#' @param administration way of administration, either `"oral"` or `"iv"`
|
||||
#' @param open browse the URL using [utils::browseURL()]
|
||||
#' @param ... in case of [set_ab_names()] and `data` is a [data.frame]: variables to select (supports tidy selection such as `column1:column4`), otherwise other arguments passed on to [as.ab()]
|
||||
#' @param data a [data.frame] of which the columns need to be renamed, or a [character] vector of column names
|
||||
#' @param snake_case a [logical] to indicate whether the names should be in so-called [snake case](https://en.wikipedia.org/wiki/Snake_case): in lower case and all spaces/slashes replaced with an underscore (`_`)
|
||||
#' @param only_first a [logical] to indicate whether only the first ATC code must be returned, with giving preference to J0-codes (i.e., the antimicrobial drug group)
|
||||
#' @details All output [will be translated][translate] where possible.
|
||||
#'
|
||||
#' The function [ab_url()] will return the direct URL to the official WHO website. A warning will be returned if the required ATC code is not available.
|
||||
#'
|
||||
#' The function [set_ab_names()] is a special column renaming function for [data.frame]s. It renames columns names that resemble antimicrobial drugs. It always makes sure that the new column names are unique. If `property = "atc"` is set, preference is given to ATC codes from the J-group.
|
||||
#' @inheritSection as.ab Source
|
||||
#' @rdname ab_property
|
||||
#' @name ab_property
|
||||
#' @return
|
||||
#' - An [integer] in case of [ab_cid()]
|
||||
#' - A named [list] in case of [ab_info()] and multiple [ab_atc()]/[ab_synonyms()]/[ab_tradenames()]
|
||||
#' - A [double] in case of [ab_ddd()]
|
||||
#' - A [data.frame] in case of [set_ab_names()]
|
||||
#' - A [character] in all other cases
|
||||
#' @export
|
||||
#' @seealso [antibiotics]
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @examples
|
||||
#' # all properties:
|
||||
#' ab_name("AMX") # "Amoxicillin"
|
||||
#' ab_atc("AMX") # "J01CA04" (ATC code from the WHO)
|
||||
#' ab_cid("AMX") # 33613 (Compound ID from PubChem)
|
||||
#' ab_synonyms("AMX") # a list with brand names of amoxicillin
|
||||
#' ab_tradenames("AMX") # same
|
||||
#' ab_group("AMX") # "Beta-lactams/penicillins"
|
||||
#' ab_atc_group1("AMX") # "Beta-lactam antibacterials, penicillins"
|
||||
#' ab_atc_group2("AMX") # "Penicillins with extended spectrum"
|
||||
#' ab_url("AMX") # link to the official WHO page
|
||||
#'
|
||||
#' # smart lowercase tranformation
|
||||
#' ab_name(x = c("AMC", "PLB")) # "Amoxicillin/clavulanic acid" "Polymyxin B"
|
||||
#' ab_name(x = c("AMC", "PLB"),
|
||||
#' tolower = TRUE) # "amoxicillin/clavulanic acid" "polymyxin B"
|
||||
#'
|
||||
#' # defined daily doses (DDD)
|
||||
#' ab_ddd("AMX", "oral") # 1.5
|
||||
#' ab_ddd_units("AMX", "oral") # "g"
|
||||
#' ab_ddd("AMX", "iv") # 3
|
||||
#' ab_ddd_units("AMX", "iv") # "g"
|
||||
#'
|
||||
#' ab_info("AMX") # all properties as a list
|
||||
#'
|
||||
#' # all ab_* functions use as.ab() internally, so you can go from 'any' to 'any':
|
||||
#' ab_atc("AMP") # ATC code of AMP (ampicillin)
|
||||
#' ab_group("J01CA01") # Drug group of ampicillins ATC code
|
||||
#' ab_loinc("ampicillin") # LOINC codes of ampicillin
|
||||
#' ab_name("21066-6") # "Ampicillin" (using LOINC)
|
||||
#' ab_name(6249) # "Ampicillin" (using CID)
|
||||
#' ab_name("J01CA01") # "Ampicillin" (using ATC)
|
||||
#'
|
||||
#' # spelling from different languages and dyslexia are no problem
|
||||
#' ab_atc("ceftriaxon")
|
||||
#' ab_atc("cephtriaxone")
|
||||
#' ab_atc("cephthriaxone")
|
||||
#' ab_atc("seephthriaaksone")
|
||||
#'
|
||||
#' # use set_ab_names() for renaming columns
|
||||
#' colnames(example_isolates)
|
||||
#' colnames(set_ab_names(example_isolates))
|
||||
#' colnames(set_ab_names(example_isolates, NIT:VAN))
|
||||
#' \donttest{
|
||||
#' if (require("dplyr")) {
|
||||
#' example_isolates %>%
|
||||
#' set_ab_names() %>%
|
||||
#' head()
|
||||
#'
|
||||
#' # this does the same:
|
||||
#' example_isolates %>%
|
||||
#' rename_with(set_ab_names)%>%
|
||||
#' head()
|
||||
#'
|
||||
#' # set_ab_names() works with any AB property:
|
||||
#' example_isolates %>%
|
||||
#' set_ab_names(property = "atc")%>%
|
||||
#' head()
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' set_ab_names(where(is.rsi)) %>%
|
||||
#' colnames()
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' set_ab_names(NIT:VAN) %>%
|
||||
#' colnames()
|
||||
#' }
|
||||
#' }
|
||||
ab_name <- function(x, language = get_AMR_locale(), tolower = FALSE, ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(tolower, allow_class = "logical", has_length = 1)
|
||||
|
||||
x <- translate_into_language(ab_validate(x = x, property = "name", ...), language = language, only_affect_ab_names = TRUE)
|
||||
if (tolower == TRUE) {
|
||||
# use perl to only transform the first character
|
||||
# as we want "polymyxin B", not "polymyxin b"
|
||||
x <- gsub("^([A-Z])", "\\L\\1", x, perl = TRUE)
|
||||
}
|
||||
x
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_cid <- function(x, ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
ab_validate(x = x, property = "cid", ...)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_synonyms <- function(x, ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
syns <- ab_validate(x = x, property = "synonyms", ...)
|
||||
names(syns) <- x
|
||||
if (length(syns) == 1) {
|
||||
unname(unlist(syns))
|
||||
} else {
|
||||
syns
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_tradenames <- function(x, ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
ab_synonyms(x, ...)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_group <- function(x, language = get_AMR_locale(), ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
translate_into_language(ab_validate(x = x, property = "group", ...), language = language, only_affect_ab_names = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @aliases ATC
|
||||
#' @export
|
||||
ab_atc <- function(x, only_first = FALSE, ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(only_first, allow_class = "logical", has_length = 1)
|
||||
|
||||
atcs <- ab_validate(x = x, property = "atc", ...)
|
||||
|
||||
if (only_first == TRUE) {
|
||||
atcs <- vapply(FUN.VALUE = character(1),
|
||||
# get only the first ATC code
|
||||
atcs,
|
||||
function(x) {
|
||||
# try to get the J-group
|
||||
if (any(x %like% "^J")) {
|
||||
x[x %like% "^J"][1L]
|
||||
} else {
|
||||
as.character(x[1L])
|
||||
}
|
||||
})
|
||||
} else if (length(atcs) == 1) {
|
||||
atcs <- unname(unlist(atcs))
|
||||
} else {
|
||||
names(atcs) <- x
|
||||
}
|
||||
|
||||
atcs
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_atc_group1 <- function(x, language = get_AMR_locale(), ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
translate_into_language(ab_validate(x = x, property = "atc_group1", ...), language = language, only_affect_ab_names = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_atc_group2 <- function(x, language = get_AMR_locale(), ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
translate_into_language(ab_validate(x = x, property = "atc_group2", ...), language = language, only_affect_ab_names = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_loinc <- function(x, ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
loincs <- ab_validate(x = x, property = "loinc", ...)
|
||||
names(loincs) <- x
|
||||
if (length(loincs) == 1) {
|
||||
unname(unlist(loincs))
|
||||
} else {
|
||||
loincs
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_ddd <- function(x, administration = "oral", ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(administration, is_in = c("oral", "iv"), has_length = 1)
|
||||
|
||||
x <- as.ab(x, ...)
|
||||
ddd_prop <- administration
|
||||
# old behaviour
|
||||
units <- list(...)$units
|
||||
if (!is.null(units) && isTRUE(units)) {
|
||||
if (message_not_thrown_before("ab_ddd", entire_session = TRUE)) {
|
||||
warning_("in `ab_ddd()`: using `ab_ddd(..., units = TRUE)` is deprecated, use `ab_ddd_units()` to retrieve units instead.",
|
||||
"This warning will be shown once per session.")
|
||||
}
|
||||
ddd_prop <- paste0(ddd_prop, "_units")
|
||||
} else {
|
||||
ddd_prop <- paste0(ddd_prop, "_ddd")
|
||||
}
|
||||
out <- ab_validate(x = x, property = ddd_prop)
|
||||
|
||||
if (any(ab_name(x, language = NULL) %like% "/" & is.na(out))) {
|
||||
warning_("in `ab_ddd()`: DDDs of some combined products are available for different dose combinations and not (yet) part of the AMR package.",
|
||||
"Please refer to the WHOCC website:\n",
|
||||
"www.whocc.no/ddd/list_of_ddds_combined_products/")
|
||||
}
|
||||
out
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_ddd_units <- function(x, administration = "oral", ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(administration, is_in = c("oral", "iv"), has_length = 1)
|
||||
|
||||
x <- as.ab(x, ...)
|
||||
if (any(ab_name(x, language = NULL) %like% "/")) {
|
||||
warning_("in `ab_ddd_units()`: DDDs of combined products are available for different dose combinations and not (yet) part of the AMR package.",
|
||||
"Please refer to the WHOCC website:\n",
|
||||
"www.whocc.no/ddd/list_of_ddds_combined_products/")
|
||||
}
|
||||
|
||||
ddd_prop <- paste0(administration, "_units")
|
||||
ab_validate(x = x, property = ddd_prop)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_info <- function(x, language = get_AMR_locale(), ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x <- as.ab(x, ...)
|
||||
list(ab = as.character(x),
|
||||
cid = ab_cid(x),
|
||||
name = ab_name(x, language = language),
|
||||
group = ab_group(x, language = language),
|
||||
atc = ab_atc(x),
|
||||
atc_group1 = ab_atc_group1(x, language = language),
|
||||
atc_group2 = ab_atc_group2(x, language = language),
|
||||
tradenames = ab_tradenames(x),
|
||||
loinc = ab_loinc(x),
|
||||
ddd = list(oral = list(amount = ab_ddd(x, administration = "oral"),
|
||||
units = ab_ddd_units(x, administration = "oral")),
|
||||
iv = list(amount = ab_ddd(x, administration = "iv"),
|
||||
units = ab_ddd_units(x, administration = "iv"))))
|
||||
}
|
||||
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_url <- function(x, open = FALSE, ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(open, allow_class = "logical", has_length = 1)
|
||||
|
||||
ab <- as.ab(x = x, ...)
|
||||
atcs <- ab_atc(ab, only_first = TRUE)
|
||||
u <- paste0("https://www.whocc.no/atc_ddd_index/?code=", atcs, "&showdescription=no")
|
||||
u[is.na(atcs)] <- NA_character_
|
||||
names(u) <- ab_name(ab)
|
||||
|
||||
NAs <- ab_name(ab, tolower = TRUE, language = NULL)[!is.na(ab) & is.na(atcs)]
|
||||
if (length(NAs) > 0) {
|
||||
warning_("in `ab_url()`: no ATC code available for ", vector_and(NAs, quotes = FALSE), ".")
|
||||
}
|
||||
|
||||
if (open == TRUE) {
|
||||
if (length(u) > 1 & !is.na(u[1L])) {
|
||||
warning_("in `ab_url()`: only the first URL will be opened, as `browseURL()` only suports one string.")
|
||||
}
|
||||
if (!is.na(u[1L])) {
|
||||
utils::browseURL(u[1L])
|
||||
}
|
||||
}
|
||||
u
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_property <- function(x, property = "name", language = get_AMR_locale(), ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(property, is_in = colnames(antibiotics), has_length = 1)
|
||||
meet_criteria(language, is_in = c(LANGUAGES_SUPPORTED, ""), has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
||||
translate_into_language(ab_validate(x = x, property = property, ...), language = language)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @aliases ATC
|
||||
#' @export
|
||||
set_ab_names <- function(data, ..., property = "name", language = get_AMR_locale(), snake_case = NULL) {
|
||||
meet_criteria(data, allow_class = c("data.frame", "character"))
|
||||
meet_criteria(property, is_in = colnames(antibiotics), has_length = 1, ignore.case = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(snake_case, allow_class = "logical", has_length = 1, allow_NULL = TRUE)
|
||||
|
||||
x_deparsed <- deparse(substitute(data))
|
||||
if (length(x_deparsed) > 1 || any(x_deparsed %unlike% "[a-z]+")) {
|
||||
x_deparsed <- "your_data"
|
||||
}
|
||||
|
||||
property <- tolower(property)
|
||||
if (is.null(snake_case)) {
|
||||
snake_case <- property == "name"
|
||||
}
|
||||
|
||||
if (is.data.frame(data)) {
|
||||
if (tryCatch(length(list(...)) > 0, error = function(e) TRUE)) {
|
||||
df <- pm_select(data, ...)
|
||||
} else {
|
||||
df <- data
|
||||
}
|
||||
vars <- get_column_abx(df, info = FALSE, only_rsi_columns = FALSE, sort = FALSE, fn = "set_ab_names")
|
||||
if (length(vars) == 0) {
|
||||
message_("No columns with antibiotic results found for `set_ab_names()`, leaving names unchanged.")
|
||||
return(data)
|
||||
}
|
||||
} else {
|
||||
# quickly get antibiotic codes
|
||||
vars_ab <- as.ab(data, fast_mode = TRUE)
|
||||
vars <- data[!is.na(vars_ab)]
|
||||
}
|
||||
x <- vapply(FUN.VALUE = character(1),
|
||||
ab_property(vars, property = property, language = language),
|
||||
function(x) {
|
||||
if (property == "atc") {
|
||||
# try to get the J-group
|
||||
if (any(x %like% "^J")) {
|
||||
x[x %like% "^J"][1L]
|
||||
} else {
|
||||
as.character(x[1L])
|
||||
}
|
||||
} else {
|
||||
as.character(x[1L])
|
||||
}
|
||||
},
|
||||
USE.NAMES = FALSE)
|
||||
if (any(x %in% c("", NA))) {
|
||||
warning_("in `set_ab_names()`: no ", property, " found for column(s): ",
|
||||
vector_and(vars[x %in% c("", NA)], sort = FALSE))
|
||||
x[x %in% c("", NA)] <- vars[x %in% c("", NA)]
|
||||
}
|
||||
|
||||
if (snake_case == TRUE) {
|
||||
x <- tolower(gsub("[^a-zA-Z0-9]+", "_", x))
|
||||
}
|
||||
|
||||
if (any(duplicated(x))) {
|
||||
# very hacky way of adding the index to each duplicate
|
||||
# so "Amoxicillin", "Amoxicillin", "Amoxicillin"
|
||||
# will be "Amoxicillin", "Amoxicillin_2", "Amoxicillin_3"
|
||||
invisible(lapply(unique(x),
|
||||
function(u) {
|
||||
dups <- which(x == u)
|
||||
if (length(dups) > 1) {
|
||||
# there are duplicates
|
||||
dup_add_int <- dups[2:length(dups)]
|
||||
x[dup_add_int] <<- paste0(x[dup_add_int], "_", c(2:length(dups)))
|
||||
}
|
||||
}))
|
||||
}
|
||||
if (is.data.frame(data)) {
|
||||
colnames(data)[colnames(data) %in% vars] <- x
|
||||
data
|
||||
} else {
|
||||
data[which(!is.na(vars_ab))] <- x
|
||||
data
|
||||
}
|
||||
}
|
||||
|
||||
ab_validate <- function(x, property, ...) {
|
||||
|
||||
check_dataset_integrity()
|
||||
|
||||
if (tryCatch(all(x[!is.na(x)] %in% AB_lookup$ab), error = function(e) FALSE)) {
|
||||
# special case for ab_* functions where class is already <ab>
|
||||
x <- AB_lookup[match(x, AB_lookup$ab), property, drop = TRUE]
|
||||
|
||||
} else {
|
||||
# try to catch an error when inputting an invalid argument
|
||||
# so the 'call.' can be set to FALSE
|
||||
tryCatch(x[1L] %in% antibiotics[1, property],
|
||||
error = function(e) stop(e$message, call. = FALSE))
|
||||
|
||||
if (!all(x %in% AB_lookup[, property])) {
|
||||
x <- as.ab(x, ...)
|
||||
x <- AB_lookup[match(x, AB_lookup$ab), property, drop = TRUE]
|
||||
}
|
||||
}
|
||||
|
||||
if (property == "ab") {
|
||||
return(set_clean_class(x, new_class = c("ab", "character")))
|
||||
} else if (property == "cid") {
|
||||
return(as.integer(x))
|
||||
} else if (property %like% "ddd") {
|
||||
return(as.double(x))
|
||||
} else {
|
||||
x[is.na(x)] <- NA
|
||||
return(x)
|
||||
}
|
||||
}
|
||||
@@ -1,753 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Antibiotic Selectors
|
||||
#'
|
||||
#' These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class or group, without the need to define the columns or antibiotic abbreviations. In short, if you have a column name that resembles an antimicrobial agent, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "CZO" and "J01DB04" will all be picked up by [cephalosporins()].
|
||||
#' @param ab_class an antimicrobial class or a part of it, such as `"carba"` and `"carbapenems"`. The columns `group`, `atc_group1` and `atc_group2` of the [antibiotics] data set will be searched (case-insensitive) for this value.
|
||||
#' @param filter an [expression] to be evaluated in the [antibiotics] data set, such as `name %like% "trim"`
|
||||
#' @param only_rsi_columns a [logical] to indicate whether only columns of class `<rsi>` must be selected (defaults to `FALSE`), see [as.rsi()]
|
||||
#' @param only_treatable a [logical] to indicate whether agents that are only for laboratory tests should be excluded (defaults to `TRUE`), such as gentamicin-high (`GEH`) and imipenem/EDTA (`IPE`)
|
||||
#' @param ... ignored, only in place to allow future extensions
|
||||
#' @details
|
||||
#' These functions can be used in data set calls for selecting columns and filtering rows. They are heavily inspired by the [Tidyverse selection helpers][tidyselect::language] such as [`everything()`][tidyselect::everything()], but also work in base \R and not only in `dplyr` verbs. Nonetheless, they are very convenient to use with `dplyr` functions such as [`select()`][dplyr::select()], [`filter()`][dplyr::filter()] and [`summarise()`][dplyr::summarise()], see *Examples*.
|
||||
#'
|
||||
#' All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) according to the [antibiotics] data set. This means that a selector such as [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
|
||||
#'
|
||||
#' The [ab_class()] function can be used to filter/select on a manually defined antibiotic class. It searches for results in the [antibiotics] data set within the columns `group`, `atc_group1` and `atc_group2`.
|
||||
#' @section Full list of supported (antibiotic) classes:
|
||||
#'
|
||||
#' `r paste0(" * ", na.omit(sapply(DEFINED_AB_GROUPS, function(ab) ifelse(tolower(gsub("^AB_", "", ab)) %in% ls(envir = asNamespace("AMR")), paste0("[", tolower(gsub("^AB_", "", ab)), "()] can select: \\cr ", vector_and(paste0(ab_name(eval(parse(text = ab), envir = asNamespace("AMR")), language = NULL, tolower = TRUE), " (", eval(parse(text = ab), envir = asNamespace("AMR")), ")"), quotes = FALSE, sort = TRUE)), character(0)), USE.NAMES = FALSE)), "\n", collapse = "")`
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @name antibiotic_class_selectors
|
||||
#' @return (internally) a [character] vector of column names, with additional class `"ab_selector"`
|
||||
#' @export
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
|
||||
#' @examples
|
||||
#' # `example_isolates` is a data set available in the AMR package.
|
||||
#' # See ?example_isolates.
|
||||
#' df <- example_isolates[ , c("hospital_id", "mo",
|
||||
#' "AMP", "AMC", "TZP", "CXM", "CRO", "GEN",
|
||||
#' "TOB", "COL", "IPM", "MEM", "TEC", "VAN")]
|
||||
#'
|
||||
#' # base R ------------------------------------------------------------------
|
||||
#'
|
||||
#' # select columns 'IPM' (imipenem) and 'MEM' (meropenem)
|
||||
#' df[, carbapenems()]
|
||||
#'
|
||||
#' # select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
|
||||
#' df[, c("mo", aminoglycosides())]
|
||||
#'
|
||||
#' # select only antibiotic columns with DDDs for oral treatment
|
||||
#' df[, administrable_per_os()]
|
||||
#'
|
||||
#' # filter using any() or all()
|
||||
#' df[any(carbapenems() == "R"), ]
|
||||
#' subset(df, any(carbapenems() == "R"))
|
||||
#'
|
||||
#' # filter on any or all results in the carbapenem columns (i.e., IPM, MEM):
|
||||
#' df[any(carbapenems()), ]
|
||||
#' df[all(carbapenems()), ]
|
||||
#'
|
||||
#' # filter with multiple antibiotic selectors using c()
|
||||
#' df[all(c(carbapenems(), aminoglycosides()) == "R"), ]
|
||||
#'
|
||||
#' # filter + select in one go: get penicillins in carbapenems-resistant strains
|
||||
#' df[any(carbapenems() == "R"), penicillins()]
|
||||
#'
|
||||
#' # You can combine selectors with '&' to be more specific. For example,
|
||||
#' # penicillins() would select benzylpenicillin ('peni G') and
|
||||
#' # administrable_per_os() would select erythromycin. Yet, when combined these
|
||||
#' # drugs are both omitted since benzylpenicillin is not administrable per os
|
||||
#' # and erythromycin is not a penicillin:
|
||||
#' df[, penicillins() & administrable_per_os()]
|
||||
#'
|
||||
#' # ab_selector() applies a filter in the `antibiotics` data set and is thus very
|
||||
#' # flexible. For instance, to select antibiotic columns with an oral DDD of at
|
||||
#' # least 1 gram:
|
||||
#' df[, ab_selector(oral_ddd > 1 & oral_units == "g")]
|
||||
#'
|
||||
#' # dplyr -------------------------------------------------------------------
|
||||
#' \donttest{
|
||||
#' if (require("dplyr")) {
|
||||
#'
|
||||
#' # get AMR for all aminoglycosides e.g., per hospital:
|
||||
#' df %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(across(aminoglycosides(), resistance))
|
||||
#'
|
||||
#' # You can combine selectors with '&' to be more specific:
|
||||
#' df %>%
|
||||
#' select(penicillins() & administrable_per_os())
|
||||
#'
|
||||
#' # get AMR for only drugs that matter - no intrinsic resistance:
|
||||
#' df %>%
|
||||
#' filter(mo_genus() %in% c("Escherichia", "Klebsiella")) %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(across(not_intrinsic_resistant(), resistance))
|
||||
#'
|
||||
#' # get susceptibility for antibiotics whose name contains "trim":
|
||||
#' df %>%
|
||||
#' filter(first_isolate()) %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(across(ab_selector(name %like% "trim"), susceptibility))
|
||||
#'
|
||||
#' # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
|
||||
#' df %>%
|
||||
#' select(carbapenems())
|
||||
#'
|
||||
#' # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
|
||||
#' df %>%
|
||||
#' select(mo, aminoglycosides())
|
||||
#'
|
||||
#' # any() and all() work in dplyr's filter() too:
|
||||
#' df %>%
|
||||
#' filter(any(aminoglycosides() == "R"),
|
||||
#' all(cephalosporins_2nd() == "R"))
|
||||
#'
|
||||
#' # also works with c():
|
||||
#' df %>%
|
||||
#' filter(any(c(carbapenems(), aminoglycosides()) == "R"))
|
||||
#'
|
||||
#' # not setting any/all will automatically apply all():
|
||||
#' df %>%
|
||||
#' filter(aminoglycosides() == "R")
|
||||
#'
|
||||
#' # this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
|
||||
#' df %>%
|
||||
#' select(mo, ab_class("mycobact"))
|
||||
#'
|
||||
#' # get bug/drug combinations for only glycopeptides in Gram-positives:
|
||||
#' df %>%
|
||||
#' filter(mo_is_gram_positive()) %>%
|
||||
#' select(mo, glycopeptides()) %>%
|
||||
#' bug_drug_combinations() %>%
|
||||
#' format()
|
||||
#'
|
||||
#' data.frame(some_column = "some_value",
|
||||
#' J01CA01 = "S") %>% # ATC code of ampicillin
|
||||
#' select(penicillins()) # only the 'J01CA01' column will be selected
|
||||
#'
|
||||
#'
|
||||
#' # with recent versions of dplyr this is all equal:
|
||||
#' x <- df[carbapenems() == "R", ]
|
||||
#' y <- df %>% filter(carbapenems() == "R")
|
||||
#' z <- df %>% filter(if_all(carbapenems(), ~.x == "R"))
|
||||
#' identical(x, y)
|
||||
#' identical(y, z)
|
||||
#' }
|
||||
#' }
|
||||
ab_class <- function(ab_class,
|
||||
only_rsi_columns = FALSE,
|
||||
only_treatable = TRUE,
|
||||
...) {
|
||||
meet_criteria(ab_class, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec(NULL, only_rsi_columns = only_rsi_columns, ab_class_args = ab_class, only_treatable = only_treatable)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @details The [ab_selector()] function can be used to internally filter the [antibiotics] data set on any results, see *Examples*. It allows for filtering on a (part of) a certain name, and/or a group name or even a minimum of DDDs for oral treatment. This function yields the highest flexibility, but is also the least user-friendly, since it requires a hard-coded filter to set.
|
||||
#' @export
|
||||
ab_selector <- function(filter,
|
||||
only_rsi_columns = FALSE,
|
||||
only_treatable = TRUE,
|
||||
...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
|
||||
|
||||
# get_current_data() has to run each time, for cases where e.g., filter() and select() are used in same call
|
||||
# but it only takes a couple of milliseconds
|
||||
vars_df <- get_current_data(arg_name = NA, call = -2)
|
||||
# to improve speed, get_column_abx() will only run once when e.g. in a select or group call
|
||||
ab_in_data <- get_column_abx(vars_df, info = FALSE, only_rsi_columns = only_rsi_columns,
|
||||
sort = FALSE, fn = "ab_selector")
|
||||
call <- substitute(filter)
|
||||
agents <- tryCatch(AMR::antibiotics[which(eval(call, envir = AMR::antibiotics)), "ab", drop = TRUE],
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
agents <- ab_in_data[ab_in_data %in% agents]
|
||||
message_agent_names(function_name = "ab_selector",
|
||||
agents = agents,
|
||||
ab_group = NULL,
|
||||
examples = "",
|
||||
call = call)
|
||||
structure(unname(agents),
|
||||
class = c("ab_selector", "character"))
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
aminoglycosides <- function(only_rsi_columns = FALSE, only_treatable = TRUE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("aminoglycosides", only_rsi_columns = only_rsi_columns, only_treatable = only_treatable)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
aminopenicillins <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("aminopenicillins", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
antifungals <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("antifungals", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
antimycobacterials <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("antimycobacterials", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
betalactams <- function(only_rsi_columns = FALSE, only_treatable = TRUE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("betalactams", only_rsi_columns = only_rsi_columns, only_treatable = only_treatable)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
carbapenems <- function(only_rsi_columns = FALSE, only_treatable = TRUE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("carbapenems", only_rsi_columns = only_rsi_columns, only_treatable = only_treatable)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("cephalosporins", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins_1st <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("cephalosporins_1st", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins_2nd <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("cephalosporins_2nd", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins_3rd <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("cephalosporins_3rd", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins_4th <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("cephalosporins_4th", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins_5th <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("cephalosporins_5th", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
fluoroquinolones <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("fluoroquinolones", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
glycopeptides <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("glycopeptides", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
lincosamides <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("lincosamides", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
lipoglycopeptides <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("lipoglycopeptides", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
macrolides <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("macrolides", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
oxazolidinones <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("oxazolidinones", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
penicillins <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("penicillins", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
polymyxins <- function(only_rsi_columns = FALSE, only_treatable = TRUE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("polymyxins", only_rsi_columns = only_rsi_columns, only_treatable = only_treatable)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
streptogramins <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("streptogramins", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
quinolones <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("quinolones", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
tetracyclines <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("tetracyclines", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
trimethoprims <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("trimethoprims", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
ureidopenicillins <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_select_exec("ureidopenicillins", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @details The [administrable_per_os()] and [administrable_iv()] functions also rely on the [antibiotics] data set - antibiotic columns will be matched where a DDD (defined daily dose) for resp. oral and IV treatment is available in the [antibiotics] data set.
|
||||
#' @export
|
||||
administrable_per_os <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
# get_current_data() has to run each time, for cases where e.g., filter() and select() are used in same call
|
||||
# but it only takes a couple of milliseconds
|
||||
vars_df <- get_current_data(arg_name = NA, call = -2)
|
||||
# to improve speed, get_column_abx() will only run once when e.g. in a select or group call
|
||||
ab_in_data <- get_column_abx(vars_df, info = FALSE, only_rsi_columns = only_rsi_columns,
|
||||
sort = FALSE, fn = "administrable_per_os")
|
||||
agents_all <- antibiotics[which(!is.na(antibiotics$oral_ddd)), "ab", drop = TRUE]
|
||||
agents <- antibiotics[which(antibiotics$ab %in% ab_in_data & !is.na(antibiotics$oral_ddd)), "ab", drop = TRUE]
|
||||
agents <- ab_in_data[ab_in_data %in% agents]
|
||||
message_agent_names(function_name = "administrable_per_os",
|
||||
agents = agents,
|
||||
ab_group = "administrable_per_os",
|
||||
examples = paste0(" (such as ",
|
||||
vector_or(ab_name(sample(agents_all,
|
||||
size = min(5, length(agents_all)),
|
||||
replace = FALSE),
|
||||
tolower = TRUE,
|
||||
language = NULL),
|
||||
quotes = FALSE),
|
||||
")"))
|
||||
structure(unname(agents),
|
||||
class = c("ab_selector", "character"))
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
administrable_iv <- function(only_rsi_columns = FALSE, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
# get_current_data() has to run each time, for cases where e.g., filter() and select() are used in same call
|
||||
# but it only takes a couple of milliseconds
|
||||
vars_df <- get_current_data(arg_name = NA, call = -2)
|
||||
# to improve speed, get_column_abx() will only run once when e.g. in a select or group call
|
||||
ab_in_data <- get_column_abx(vars_df, info = FALSE, only_rsi_columns = only_rsi_columns,
|
||||
sort = FALSE, fn = "administrable_iv")
|
||||
agents_all <- antibiotics[which(!is.na(antibiotics$iv_ddd)), "ab", drop = TRUE]
|
||||
agents <- antibiotics[which(antibiotics$ab %in% ab_in_data & !is.na(antibiotics$iv_ddd)), "ab", drop = TRUE]
|
||||
agents <- ab_in_data[ab_in_data %in% agents]
|
||||
message_agent_names(function_name = "administrable_iv",
|
||||
agents = agents,
|
||||
ab_group = "administrable_iv",
|
||||
examples = "")
|
||||
structure(unname(agents),
|
||||
class = c("ab_selector", "character"))
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @inheritParams eucast_rules
|
||||
#' @details The [not_intrinsic_resistant()] function can be used to only select antibiotic columns that pose no intrinsic resistance for the microorganisms in the data set. For example, if a data set contains only microorganism codes or names of *E. coli* and *K. pneumoniae* and contains a column "vancomycin", this column will be removed (or rather, unselected) using this function. It currently applies `r format_eucast_version_nr(names(EUCAST_VERSION_EXPERT_RULES[length(EUCAST_VERSION_EXPERT_RULES)]))` to determine intrinsic resistance, using the [eucast_rules()] function internally. Because of this determination, this function is quite slow in terms of performance.
|
||||
#' @export
|
||||
not_intrinsic_resistant <- function(only_rsi_columns = FALSE, col_mo = NULL, version_expertrules = 3.3, ...) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
# get_current_data() has to run each time, for cases where e.g., filter() and select() are used in same call
|
||||
# but it only takes a couple of milliseconds
|
||||
vars_df <- get_current_data(arg_name = NA, call = -2)
|
||||
# to improve speed, get_column_abx() will only run once when e.g. in a select or group call
|
||||
ab_in_data <- get_column_abx(vars_df, info = FALSE, only_rsi_columns = only_rsi_columns,
|
||||
sort = FALSE, fn = "not_intrinsic_resistant")
|
||||
# intrinsic vars
|
||||
vars_df_R <- tryCatch(sapply(eucast_rules(vars_df,
|
||||
col_mo = col_mo,
|
||||
version_expertrules = version_expertrules,
|
||||
rules = "expert",
|
||||
info = FALSE),
|
||||
function(col) tryCatch(!any(is.na(col)) && all(col == "R"),
|
||||
error = function(e) FALSE)),
|
||||
error = function(e) stop_("in not_intrinsic_resistant(): ", e$message, call = FALSE))
|
||||
|
||||
agents <- ab_in_data[ab_in_data %in% names(vars_df_R[which(vars_df_R)])]
|
||||
if (length(agents) > 0 &&
|
||||
message_not_thrown_before("not_intrinsic_resistant", sort(agents))) {
|
||||
agents_formatted <- paste0("'", font_bold(agents, collapse = NULL), "'")
|
||||
agents_names <- ab_name(names(agents), tolower = TRUE, language = NULL)
|
||||
need_name <- generalise_antibiotic_name(agents) != generalise_antibiotic_name(agents_names)
|
||||
agents_formatted[need_name] <- paste0(agents_formatted[need_name], " (", agents_names[need_name], ")")
|
||||
message_("For `not_intrinsic_resistant()` removing ",
|
||||
ifelse(length(agents) == 1, "column ", "columns "),
|
||||
vector_and(agents_formatted, quotes = FALSE, sort = FALSE))
|
||||
}
|
||||
|
||||
vars_df_R <- names(vars_df_R)[which(!vars_df_R)]
|
||||
# find columns that are abx, but also intrinsic R
|
||||
out <- unname(intersect(ab_in_data, vars_df_R))
|
||||
structure(out,
|
||||
class = c("ab_selector", "character"))
|
||||
}
|
||||
|
||||
ab_select_exec <- function(function_name,
|
||||
only_rsi_columns = FALSE,
|
||||
only_treatable = FALSE,
|
||||
ab_class_args = NULL) {
|
||||
# get_current_data() has to run each time, for cases where e.g., filter() and select() are used in same call
|
||||
# but it only takes a couple of milliseconds
|
||||
vars_df <- get_current_data(arg_name = NA, call = -3)
|
||||
# to improve speed, get_column_abx() will only run once when e.g. in a select or group call
|
||||
ab_in_data <- get_column_abx(vars_df, info = FALSE, only_rsi_columns = only_rsi_columns,
|
||||
sort = FALSE, fn = function_name)
|
||||
# untreatable drugs
|
||||
if (only_treatable == TRUE) {
|
||||
untreatable <- antibiotics[which(antibiotics$name %like% "-high|EDTA|polysorbate|macromethod|screening|/nacubactam"), "ab", drop = TRUE]
|
||||
if (any(untreatable %in% names(ab_in_data))) {
|
||||
if (message_not_thrown_before(function_name, "ab_class", "untreatable", entire_session = TRUE)) {
|
||||
warning_("in `", function_name, "()`: some agents were ignored since they cannot be used for treating patients: ",
|
||||
vector_and(ab_name(names(ab_in_data)[names(ab_in_data) %in% untreatable],
|
||||
language = NULL,
|
||||
tolower = TRUE),
|
||||
quotes = FALSE,
|
||||
sort = TRUE), ". They can be included using `", function_name, "(only_treatable = FALSE)`. ",
|
||||
"This warning will be shown once per session.")
|
||||
}
|
||||
ab_in_data <- ab_in_data[!names(ab_in_data) %in% untreatable]
|
||||
}
|
||||
}
|
||||
|
||||
if (length(ab_in_data) == 0) {
|
||||
message_("No antimicrobial agents found in the data.")
|
||||
return(NULL)
|
||||
}
|
||||
|
||||
if (is.null(ab_class_args)) {
|
||||
# their upper case equivalent are vectors with class <ab>, created in data-raw/_internals.R
|
||||
# carbapenems() gets its codes from AMR:::AB_CARBAPENEMS
|
||||
abx <- get(paste0("AB_", toupper(function_name)), envir = asNamespace("AMR"))
|
||||
ab_group <- function_name
|
||||
examples <- paste0(" (such as ", vector_or(ab_name(sample(abx, size = min(2, length(abx)), replace = FALSE),
|
||||
tolower = TRUE,
|
||||
language = NULL),
|
||||
quotes = FALSE), ")")
|
||||
} else {
|
||||
# this for the 'manual' ab_class() function
|
||||
abx <- subset(AB_lookup,
|
||||
group %like% ab_class_args |
|
||||
atc_group1 %like% ab_class_args |
|
||||
atc_group2 %like% ab_class_args)$ab
|
||||
ab_group <- find_ab_group(ab_class_args)
|
||||
function_name <- "ab_class"
|
||||
examples <- paste0(" (such as ", find_ab_names(ab_class_args, 2), ")")
|
||||
}
|
||||
|
||||
# get the columns with a group names in the chosen ab class
|
||||
agents <- ab_in_data[names(ab_in_data) %in% abx]
|
||||
|
||||
message_agent_names(function_name = function_name,
|
||||
agents = agents,
|
||||
ab_group = ab_group,
|
||||
examples = examples,
|
||||
ab_class_args = ab_class_args)
|
||||
|
||||
structure(unname(agents),
|
||||
class = c("ab_selector", "character"))
|
||||
}
|
||||
|
||||
#' @method c ab_selector
|
||||
#' @export
|
||||
#' @noRd
|
||||
c.ab_selector <- function(...) {
|
||||
structure(unlist(lapply(list(...), as.character)),
|
||||
class = c("ab_selector", "character"))
|
||||
}
|
||||
|
||||
all_any_ab_selector <- function(type, ..., na.rm = TRUE) {
|
||||
cols_ab <- c(...)
|
||||
result <- cols_ab[toupper(cols_ab) %in% c("R", "S", "I")]
|
||||
if (length(result) == 0) {
|
||||
message_("Filtering ", type, " of columns ", vector_and(font_bold(cols_ab, collapse = NULL), quotes = "'"), ' to contain value "R", "S" or "I"')
|
||||
result <- c("R", "S", "I")
|
||||
}
|
||||
cols_ab <- cols_ab[!cols_ab %in% result]
|
||||
df <- get_current_data(arg_name = NA, call = -3)
|
||||
|
||||
if (type == "all") {
|
||||
scope_fn <- all
|
||||
} else {
|
||||
scope_fn <- any
|
||||
}
|
||||
|
||||
x_transposed <- as.list(as.data.frame(t(df[, cols_ab, drop = FALSE]), stringsAsFactors = FALSE))
|
||||
vapply(FUN.VALUE = logical(1),
|
||||
X = x_transposed,
|
||||
FUN = function(y) scope_fn(y %in% result, na.rm = na.rm),
|
||||
USE.NAMES = FALSE)
|
||||
}
|
||||
|
||||
#' @method all ab_selector
|
||||
#' @export
|
||||
#' @noRd
|
||||
all.ab_selector <- function(..., na.rm = FALSE) {
|
||||
all_any_ab_selector("all", ..., na.rm = na.rm)
|
||||
}
|
||||
|
||||
#' @method any ab_selector
|
||||
#' @export
|
||||
#' @noRd
|
||||
any.ab_selector <- function(..., na.rm = FALSE) {
|
||||
all_any_ab_selector("any", ..., na.rm = na.rm)
|
||||
}
|
||||
|
||||
|
||||
#' @method all ab_selector_any_all
|
||||
#' @export
|
||||
#' @noRd
|
||||
all.ab_selector_any_all <- function(..., na.rm = FALSE) {
|
||||
# this is all() on a logical vector from `==.ab_selector` or `!=.ab_selector`
|
||||
# e.g., example_isolates %>% filter(all(carbapenems() == "R"))
|
||||
# so just return the vector as is, only correcting for na.rm
|
||||
out <- unclass(c(...))
|
||||
if (na.rm == TRUE) {
|
||||
out <- out[!is.na(out)]
|
||||
}
|
||||
out
|
||||
}
|
||||
|
||||
#' @method any ab_selector_any_all
|
||||
#' @export
|
||||
#' @noRd
|
||||
any.ab_selector_any_all <- function(..., na.rm = FALSE) {
|
||||
# this is any() on a logical vector from `==.ab_selector` or `!=.ab_selector`
|
||||
# e.g., example_isolates %>% filter(any(carbapenems() == "R"))
|
||||
# so just return the vector as is, only correcting for na.rm
|
||||
out <- unclass(c(...))
|
||||
if (na.rm == TRUE) {
|
||||
out <- out[!is.na(out)]
|
||||
}
|
||||
out
|
||||
}
|
||||
|
||||
#' @method == ab_selector
|
||||
#' @export
|
||||
#' @noRd
|
||||
`==.ab_selector` <- function(e1, e2) {
|
||||
calls <- as.character(match.call())
|
||||
fn_name <- calls[2]
|
||||
fn_name <- gsub("^(c\\()(.*)(\\))$", "\\2", fn_name)
|
||||
if (is_any(fn_name)) {
|
||||
type <- "any"
|
||||
} else if (is_all(fn_name)) {
|
||||
type <- "all"
|
||||
} else {
|
||||
type <- "all"
|
||||
if (length(e1) > 1) {
|
||||
message_("Assuming a filter on ", type, " ", length(e1), " ", gsub("[\\(\\)]", "", fn_name),
|
||||
". Wrap around `all()` or `any()` to prevent this note.")
|
||||
}
|
||||
}
|
||||
structure(all_any_ab_selector(type = type, e1, e2),
|
||||
class = c("ab_selector_any_all", "logical"))
|
||||
}
|
||||
|
||||
#' @method != ab_selector
|
||||
#' @export
|
||||
#' @noRd
|
||||
`!=.ab_selector` <- function(e1, e2) {
|
||||
calls <- as.character(match.call())
|
||||
fn_name <- calls[2]
|
||||
fn_name <- gsub("^(c\\()(.*)(\\))$", "\\2", fn_name)
|
||||
if (is_any(fn_name)) {
|
||||
type <- "any"
|
||||
} else if (is_all(fn_name)) {
|
||||
type <- "all"
|
||||
} else {
|
||||
type <- "all"
|
||||
if (length(e1) > 1) {
|
||||
message_("Assuming a filter on ", type, " ", length(e1), " ", gsub("[\\(\\)]", "", fn_name),
|
||||
". Wrap around `all()` or `any()` to prevent this note.")
|
||||
}
|
||||
}
|
||||
# this is `!=`, so turn around the values
|
||||
rsi <- c("R", "S", "I")
|
||||
e2 <- rsi[rsi != e2]
|
||||
structure(all_any_ab_selector(type = type, e1, e2),
|
||||
class = c("ab_selector_any_all", "logical"))
|
||||
}
|
||||
|
||||
#' @method & ab_selector
|
||||
#' @export
|
||||
#' @noRd
|
||||
`&.ab_selector` <- function(e1, e2) {
|
||||
# this is only required for base R, since tidyselect has already implemented this
|
||||
# e.g., for: example_isolates[, penicillins() & administrable_per_os()]
|
||||
structure(intersect(unclass(e1), unclass(e2)),
|
||||
class = c("ab_selector", "character"))
|
||||
}
|
||||
#' @method | ab_selector
|
||||
#' @export
|
||||
#' @noRd
|
||||
`|.ab_selector` <- function(e1, e2) {
|
||||
# this is only required for base R, since tidyselect has already implemented this
|
||||
# e.g., for: example_isolates[, penicillins() | administrable_per_os()]
|
||||
structure(union(unclass(e1), unclass(e2)),
|
||||
class = c("ab_selector", "character"))
|
||||
}
|
||||
|
||||
is_any <- function(el1) {
|
||||
syscalls <- paste0(trimws(deparse(sys.calls())), collapse = " ")
|
||||
el1 <- gsub("(.*),.*", "\\1", el1)
|
||||
syscalls %like% paste0("[^_a-zA-Z0-9]any\\(", "(c\\()?", el1)
|
||||
}
|
||||
is_all <- function(el1) {
|
||||
syscalls <- paste0(trimws(deparse(sys.calls())), collapse = " ")
|
||||
el1 <- gsub("(.*),.*", "\\1", el1)
|
||||
syscalls %like% paste0("[^_a-zA-Z0-9]all\\(", "(c\\()?", el1)
|
||||
}
|
||||
|
||||
find_ab_group <- function(ab_class_args) {
|
||||
ab_class_args <- gsub("[^a-zA-Z0-9]", ".*", ab_class_args)
|
||||
AB_lookup %pm>%
|
||||
subset(group %like% ab_class_args |
|
||||
atc_group1 %like% ab_class_args |
|
||||
atc_group2 %like% ab_class_args) %pm>%
|
||||
pm_pull(group) %pm>%
|
||||
unique() %pm>%
|
||||
tolower() %pm>%
|
||||
sort() %pm>%
|
||||
paste(collapse = "/")
|
||||
}
|
||||
|
||||
find_ab_names <- function(ab_group, n = 3) {
|
||||
ab_group <- gsub("[^a-zA-Z|0-9]", ".*", ab_group)
|
||||
|
||||
# try popular first, they have DDDs
|
||||
drugs <- antibiotics[which((!is.na(antibiotics$iv_ddd) | !is.na(antibiotics$oral_ddd)) &
|
||||
antibiotics$name %unlike% " " &
|
||||
antibiotics$group %like% ab_group &
|
||||
antibiotics$ab %unlike% "[0-9]$"), ]$name
|
||||
if (length(drugs) < n) {
|
||||
# now try it all
|
||||
drugs <- antibiotics[which((antibiotics$group %like% ab_group |
|
||||
antibiotics$atc_group1 %like% ab_group |
|
||||
antibiotics$atc_group2 %like% ab_group) &
|
||||
antibiotics$ab %unlike% "[0-9]$"), ]$name
|
||||
}
|
||||
if (length(drugs) == 0) {
|
||||
return("??")
|
||||
}
|
||||
vector_or(ab_name(sample(drugs, size = min(n, length(drugs)), replace = FALSE),
|
||||
tolower = TRUE,
|
||||
language = NULL),
|
||||
quotes = FALSE)
|
||||
}
|
||||
|
||||
message_agent_names <- function(function_name, agents, ab_group = NULL, examples = "", ab_class_args = NULL, call = NULL) {
|
||||
if (message_not_thrown_before(function_name, sort(agents))) {
|
||||
if (length(agents) == 0) {
|
||||
if (is.null(ab_group)) {
|
||||
message_("For `", function_name, "()` no antimicrobial agents found", examples, ".")
|
||||
} else if (ab_group == "administrable_per_os") {
|
||||
message_("No orally administrable agents found", examples, ".")
|
||||
} else if (ab_group == "administrable_iv") {
|
||||
message_("No IV administrable agents found", examples, ".")
|
||||
} else {
|
||||
message_("No antimicrobial agents of class '", ab_group, "' found", examples, ".")
|
||||
}
|
||||
} else {
|
||||
agents_formatted <- paste0("'", font_bold(agents, collapse = NULL), "'")
|
||||
agents_names <- ab_name(names(agents), tolower = TRUE, language = NULL)
|
||||
need_name <- generalise_antibiotic_name(agents) != generalise_antibiotic_name(agents_names)
|
||||
agents_formatted[need_name] <- paste0(agents_formatted[need_name], " (", agents_names[need_name], ")")
|
||||
message_("For `", function_name, "(",
|
||||
ifelse(function_name == "ab_class",
|
||||
paste0("\"", ab_class_args, "\""),
|
||||
ifelse(!is.null(call),
|
||||
paste0(deparse(call), collapse = " "),
|
||||
"")),
|
||||
")` using ",
|
||||
ifelse(length(agents) == 1, "column ", "columns "),
|
||||
vector_and(agents_formatted, quotes = FALSE, sort = FALSE))
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,220 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Age in Years of Individuals
|
||||
#'
|
||||
#' Calculates age in years based on a reference date, which is the system date at default.
|
||||
#' @param x date(s), [character] (vectors) will be coerced with [as.POSIXlt()]
|
||||
#' @param reference reference date(s) (defaults to today), [character] (vectors) will be coerced with [as.POSIXlt()]
|
||||
#' @param exact a [logical] to indicate whether age calculation should be exact, i.e. with decimals. It divides the number of days of [year-to-date](https://en.wikipedia.org/wiki/Year-to-date) (YTD) of `x` by the number of days in the year of `reference` (either 365 or 366).
|
||||
#' @param na.rm a [logical] to indicate whether missing values should be removed
|
||||
#' @param ... arguments passed on to [as.POSIXlt()], such as `origin`
|
||||
#' @details Ages below 0 will be returned as `NA` with a warning. Ages above 120 will only give a warning.
|
||||
#'
|
||||
#' This function vectorises over both `x` and `reference`, meaning that either can have a length of 1 while the other argument has a larger length.
|
||||
#' @return An [integer] (no decimals) if `exact = FALSE`, a [double] (with decimals) otherwise
|
||||
#' @seealso To split ages into groups, use the [age_groups()] function.
|
||||
#' @export
|
||||
#' @examples
|
||||
#' # 10 random pre-Y2K birth dates
|
||||
#' df <- data.frame(birth_date = as.Date("2000-01-01") - runif(10) * 25000)
|
||||
#'
|
||||
#' # add ages
|
||||
#' df$age <- age(df$birth_date)
|
||||
#'
|
||||
#' # add exact ages
|
||||
#' df$age_exact <- age(df$birth_date, exact = TRUE)
|
||||
#'
|
||||
#' # add age at millenium switch
|
||||
#' df$age_at_y2k <- age(df$birth_date, "2000-01-01")
|
||||
#'
|
||||
#' df
|
||||
age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
|
||||
meet_criteria(x, allow_class = c("character", "Date", "POSIXt"))
|
||||
meet_criteria(reference, allow_class = c("character", "Date", "POSIXt"))
|
||||
meet_criteria(exact, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
|
||||
if (length(x) != length(reference)) {
|
||||
if (length(x) == 1) {
|
||||
x <- rep(x, length(reference))
|
||||
} else if (length(reference) == 1) {
|
||||
reference <- rep(reference, length(x))
|
||||
} else {
|
||||
stop_("`x` and `reference` must be of same length, or `reference` must be of length 1.")
|
||||
}
|
||||
}
|
||||
x <- as.POSIXlt(x, ...)
|
||||
reference <- as.POSIXlt(reference, ...)
|
||||
|
||||
# from https://stackoverflow.com/a/25450756/4575331
|
||||
years_gap <- reference$year - x$year
|
||||
ages <- ifelse(reference$mon < x$mon | (reference$mon == x$mon & reference$mday < x$mday),
|
||||
as.integer(years_gap - 1),
|
||||
as.integer(years_gap))
|
||||
|
||||
# add decimals
|
||||
if (exact == TRUE) {
|
||||
# get dates of `x` when `x` would have the year of `reference`
|
||||
x_in_reference_year <- as.POSIXlt(paste0(format(as.Date(reference), "%Y"),
|
||||
format(as.Date(x), "-%m-%d")),
|
||||
format = "%Y-%m-%d")
|
||||
# get differences in days
|
||||
n_days_x_rest <- as.double(difftime(as.Date(reference),
|
||||
as.Date(x_in_reference_year),
|
||||
units = "days"))
|
||||
# get numbers of days the years of `reference` has for a reliable denominator
|
||||
n_days_reference_year <- as.POSIXlt(paste0(format(as.Date(reference), "%Y"), "-12-31"),
|
||||
format = "%Y-%m-%d")$yday + 1
|
||||
# add decimal parts of year
|
||||
mod <- n_days_x_rest / n_days_reference_year
|
||||
# negative mods are cases where `x_in_reference_year` > `reference` - so 'add' a year
|
||||
mod[!is.na(mod) & mod < 0] <- mod[!is.na(mod) & mod < 0] + 1
|
||||
# and finally add to ages
|
||||
ages <- ages + mod
|
||||
}
|
||||
|
||||
if (any(ages < 0, na.rm = TRUE)) {
|
||||
ages[!is.na(ages) & ages < 0] <- NA
|
||||
warning_("in `age()`: NAs introduced for ages below 0.")
|
||||
}
|
||||
if (any(ages > 120, na.rm = TRUE)) {
|
||||
warning_("in `age()`: some ages are above 120.")
|
||||
}
|
||||
|
||||
if (isTRUE(na.rm)) {
|
||||
ages <- ages[!is.na(ages)]
|
||||
}
|
||||
|
||||
if (exact == TRUE) {
|
||||
as.double(ages)
|
||||
} else {
|
||||
as.integer(ages)
|
||||
}
|
||||
}
|
||||
|
||||
#' Split Ages into Age Groups
|
||||
#'
|
||||
#' Split ages into age groups defined by the `split` argument. This allows for easier demographic (antimicrobial resistance) analysis.
|
||||
#' @param x age, e.g. calculated with [age()]
|
||||
#' @param split_at values to split `x` at, defaults to age groups 0-11, 12-24, 25-54, 55-74 and 75+. See *Details*.
|
||||
#' @param na.rm a [logical] to indicate whether missing values should be removed
|
||||
#' @details To split ages, the input for the `split_at` argument can be:
|
||||
#'
|
||||
#' * A [numeric] vector. A value of e.g. `c(10, 20)` will split `x` on 0-9, 10-19 and 20+. A value of only `50` will split `x` on 0-49 and 50+.
|
||||
#' The default is to split on young children (0-11), youth (12-24), young adults (25-54), middle-aged adults (55-74) and elderly (75+).
|
||||
#' * A character:
|
||||
#' - `"children"` or `"kids"`, equivalent of: `c(0, 1, 2, 4, 6, 13, 18)`. This will split on 0, 1, 2-3, 4-5, 6-12, 13-17 and 18+.
|
||||
#' - `"elderly"` or `"seniors"`, equivalent of: `c(65, 75, 85)`. This will split on 0-64, 65-74, 75-84, 85+.
|
||||
#' - `"fives"`, equivalent of: `1:20 * 5`. This will split on 0-4, 5-9, ..., 95-99, 100+.
|
||||
#' - `"tens"`, equivalent of: `1:10 * 10`. This will split on 0-9, 10-19, ..., 90-99, 100+.
|
||||
#' @return Ordered [factor]
|
||||
#' @seealso To determine ages, based on one or more reference dates, use the [age()] function.
|
||||
#' @export
|
||||
|
||||
#' @examples
|
||||
#' ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)
|
||||
#'
|
||||
#' # split into 0-49 and 50+
|
||||
#' age_groups(ages, 50)
|
||||
#'
|
||||
#' # split into 0-19, 20-49 and 50+
|
||||
#' age_groups(ages, c(20, 50))
|
||||
#'
|
||||
#' # split into groups of ten years
|
||||
#' age_groups(ages, 1:10 * 10)
|
||||
#' age_groups(ages, split_at = "tens")
|
||||
#'
|
||||
#' # split into groups of five years
|
||||
#' age_groups(ages, 1:20 * 5)
|
||||
#' age_groups(ages, split_at = "fives")
|
||||
#'
|
||||
#' # split specifically for children
|
||||
#' age_groups(ages, c(1, 2, 4, 6, 13, 18))
|
||||
#' age_groups(ages, "children")
|
||||
#'
|
||||
#' \donttest{
|
||||
#' # resistance of ciprofloxacin per age group
|
||||
#' if (require("dplyr")) {
|
||||
#' example_isolates %>%
|
||||
#' filter_first_isolate() %>%
|
||||
#' filter(mo == as.mo("E. coli")) %>%
|
||||
#' group_by(age_group = age_groups(age)) %>%
|
||||
#' select(age_group, CIP) %>%
|
||||
#' ggplot_rsi(x = "age_group",
|
||||
#' minimum = 0,
|
||||
#' x.title = "Age Group",
|
||||
#' title = "Ciprofloxacin resistance per age group")
|
||||
#' }
|
||||
#' }
|
||||
age_groups <- function(x, split_at = c(12, 25, 55, 75), na.rm = FALSE) {
|
||||
meet_criteria(x, allow_class = c("numeric", "integer"), is_positive_or_zero = TRUE, is_finite = TRUE)
|
||||
meet_criteria(split_at, allow_class = c("numeric", "integer", "character"), is_positive_or_zero = TRUE, is_finite = TRUE)
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
|
||||
if (any(x < 0, na.rm = TRUE)) {
|
||||
x[x < 0] <- NA
|
||||
warning_("in `age_groups()`: NAs introduced for ages below 0.")
|
||||
}
|
||||
if (is.character(split_at)) {
|
||||
split_at <- split_at[1L]
|
||||
if (split_at %like% "^(child|kid|junior)") {
|
||||
split_at <- c(0, 1, 2, 4, 6, 13, 18)
|
||||
} else if (split_at %like% "^(elder|senior)") {
|
||||
split_at <- c(65, 75, 85)
|
||||
} else if (split_at %like% "^five") {
|
||||
split_at <- 1:20 * 5
|
||||
} else if (split_at %like% "^ten") {
|
||||
split_at <- 1:10 * 10
|
||||
}
|
||||
}
|
||||
split_at <- sort(unique(as.integer(split_at)))
|
||||
if (!split_at[1] == 0) {
|
||||
# add base number 0
|
||||
split_at <- c(0, split_at)
|
||||
}
|
||||
split_at <- split_at[!is.na(split_at)]
|
||||
stop_if(length(split_at) == 1, "invalid value for `split_at`") # only 0 is available
|
||||
|
||||
# turn input values to 'split_at' indices
|
||||
y <- x
|
||||
lbls <- split_at
|
||||
for (i in seq_len(length(split_at))) {
|
||||
y[x >= split_at[i]] <- i
|
||||
# create labels
|
||||
lbls[i - 1] <- paste0(unique(c(split_at[i - 1], split_at[i] - 1)), collapse = "-")
|
||||
}
|
||||
|
||||
# last category
|
||||
lbls[length(lbls)] <- paste0(split_at[length(split_at)], "+")
|
||||
|
||||
agegroups <- factor(lbls[y], levels = lbls, ordered = TRUE)
|
||||
|
||||
if (isTRUE(na.rm)) {
|
||||
agegroups <- agegroups[!is.na(agegroups)]
|
||||
}
|
||||
|
||||
agegroups
|
||||
}
|
||||
@@ -1,75 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' The `AMR` Package
|
||||
#'
|
||||
#' Welcome to the `AMR` package.
|
||||
#' @details
|
||||
#' `AMR` is a free, open-source and independent \R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
|
||||
#'
|
||||
#' After installing this package, \R knows `r format_included_data_number(microorganisms)` distinct microbial species and all `r format_included_data_number(rbind(antibiotics[, "atc", drop = FALSE], antivirals[, "atc", drop = FALSE]))` antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.
|
||||
#'
|
||||
#' This package is fully independent of any other \R package and works on Windows, macOS and Linux with all versions of \R since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This \R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation.
|
||||
#'
|
||||
#' This package can be used for:
|
||||
#' - Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the Catalogue of Life and List of Prokaryotic names with Standing in Nomenclature
|
||||
#' - Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines
|
||||
#' - Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records
|
||||
#' - Determining first isolates to be used for AMR data analysis
|
||||
#' - Calculating antimicrobial resistance
|
||||
#' - Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO)
|
||||
#' - Calculating (empirical) susceptibility of both mono therapy and combination therapies
|
||||
#' - Predicting future antimicrobial resistance using regression models
|
||||
#' - Getting properties for any microorganism (such as Gram stain, species, genus or family)
|
||||
#' - Getting properties for any antibiotic (such as name, code of EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)
|
||||
#' - Plotting antimicrobial resistance
|
||||
#' - Applying EUCAST expert rules
|
||||
#' - Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code
|
||||
#' - Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code
|
||||
#' - Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI
|
||||
#' - Principal component analysis for AMR
|
||||
#'
|
||||
#' @section Reference Data Publicly Available:
|
||||
#' All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this `AMR` package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find [all download links on our website](https://msberends.github.io/AMR/articles/datasets.html), which is automatically updated with every code change.
|
||||
#' @section Read more on Our Website!:
|
||||
#' On our website <https://msberends.github.io/AMR/> you can find [a comprehensive tutorial](https://msberends.github.io/AMR/articles/AMR.html) about how to conduct AMR data analysis, the [complete documentation of all functions](https://msberends.github.io/AMR/reference/) and [an example analysis using WHONET data](https://msberends.github.io/AMR/articles/WHONET.html).
|
||||
#' @section Contact Us:
|
||||
#' For suggestions, comments or questions, please contact us at:
|
||||
#'
|
||||
#' Matthijs S. Berends \cr
|
||||
#' m.s.berends \[at\] umcg \[dot\] nl \cr
|
||||
#' University of Groningen
|
||||
#' Department of Medical Microbiology and Infection Prevention \cr
|
||||
#' University Medical Center Groningen \cr
|
||||
#' Post Office Box 30001 \cr
|
||||
#' 9700 RB Groningen \cr
|
||||
#' The Netherlands
|
||||
#' <https://msberends.github.io/AMR/>
|
||||
#'
|
||||
#' If you have found a bug, please file a new issue at: \cr
|
||||
#' <https://github.com/msberends/AMR/issues>
|
||||
#' @name AMR
|
||||
#' @rdname AMR
|
||||
NULL
|
||||
-225
@@ -1,225 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Get ATC Properties from WHOCC Website
|
||||
#'
|
||||
#' Gets data from the WHOCC website to determine properties of an Anatomical Therapeutic Chemical (ATC) (e.g. an antibiotic), such as the name, defined daily dose (DDD) or standard unit.
|
||||
#' @param atc_code a [character] (vector) with ATC code(s) of antibiotics, will be coerced with [as.ab()] and [ab_atc()] internally if not a valid ATC code
|
||||
#' @param property property of an ATC code. Valid values are `"ATC"`, `"Name"`, `"DDD"`, `"U"` (`"unit"`), `"Adm.R"`, `"Note"` and `groups`. For this last option, all hierarchical groups of an ATC code will be returned, see *Examples*.
|
||||
#' @param administration type of administration when using `property = "Adm.R"`, see *Details*
|
||||
#' @param url url of website of the WHOCC. The sign `%s` can be used as a placeholder for ATC codes.
|
||||
#' @param url_vet url of website of the WHOCC for veterinary medicine. The sign `%s` can be used as a placeholder for ATC_vet codes (that all start with "Q").
|
||||
#' @param ... arguments to pass on to `atc_property`
|
||||
#' @details
|
||||
#' Options for argument `administration`:
|
||||
#'
|
||||
#' - `"Implant"` = Implant
|
||||
#' - `"Inhal"` = Inhalation
|
||||
#' - `"Instill"` = Instillation
|
||||
#' - `"N"` = nasal
|
||||
#' - `"O"` = oral
|
||||
#' - `"P"` = parenteral
|
||||
#' - `"R"` = rectal
|
||||
#' - `"SL"` = sublingual/buccal
|
||||
#' - `"TD"` = transdermal
|
||||
#' - `"V"` = vaginal
|
||||
#'
|
||||
#' Abbreviations of return values when using `property = "U"` (unit):
|
||||
#'
|
||||
#' - `"g"` = gram
|
||||
#' - `"mg"` = milligram
|
||||
#' - `"mcg"` = microgram
|
||||
#' - `"U"` = unit
|
||||
#' - `"TU"` = thousand units
|
||||
#' - `"MU"` = million units
|
||||
#' - `"mmol"` = millimole
|
||||
#' - `"ml"` = millilitre (e.g. eyedrops)
|
||||
#'
|
||||
#' **N.B. This function requires an internet connection and only works if the following packages are installed: `curl`, `rvest`, `xml2`.**
|
||||
#' @export
|
||||
#' @rdname atc_online
|
||||
#' @source <https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/>
|
||||
#' @examples
|
||||
#' \donttest{
|
||||
#' if (requireNamespace("curl") && requireNamespace("rvest") && requireNamespace("xml2")) {
|
||||
#' # oral DDD (Defined Daily Dose) of amoxicillin
|
||||
#' atc_online_property("J01CA04", "DDD", "O")
|
||||
#' atc_online_ddd(ab_atc("amox"))
|
||||
#'
|
||||
#' # parenteral DDD (Defined Daily Dose) of amoxicillin
|
||||
#' atc_online_property("J01CA04", "DDD", "P")
|
||||
#'
|
||||
#' atc_online_property("J01CA04", property = "groups") # search hierarchical groups of amoxicillin
|
||||
#' }
|
||||
#' }
|
||||
atc_online_property <- function(atc_code,
|
||||
property,
|
||||
administration = "O",
|
||||
url = "https://www.whocc.no/atc_ddd_index/?code=%s&showdescription=no",
|
||||
url_vet = "https://www.whocc.no/atcvet/atcvet_index/?code=%s&showdescription=no") {
|
||||
meet_criteria(atc_code, allow_class = "character")
|
||||
meet_criteria(property, allow_class = "character", has_length = 1, is_in = c("ATC", "Name", "DDD", "U", "unit", "Adm.R", "Note", "groups"), ignore.case = TRUE)
|
||||
meet_criteria(administration, allow_class = "character", has_length = 1)
|
||||
meet_criteria(url, allow_class = "character", has_length = 1, looks_like = "https?://")
|
||||
meet_criteria(url_vet, allow_class = "character", has_length = 1, looks_like = "https?://")
|
||||
|
||||
has_internet <- import_fn("has_internet", "curl")
|
||||
html_attr <- import_fn("html_attr", "rvest")
|
||||
html_children <- import_fn("html_children", "rvest")
|
||||
html_node <- import_fn("html_node", "rvest")
|
||||
html_nodes <- import_fn("html_nodes", "rvest")
|
||||
html_table <- import_fn("html_table", "rvest")
|
||||
html_text <- import_fn("html_text", "rvest")
|
||||
read_html <- import_fn("read_html", "xml2")
|
||||
|
||||
check_dataset_integrity()
|
||||
|
||||
if (!all(atc_code %in% unlist(antibiotics$atc))) {
|
||||
atc_code <- as.character(ab_atc(atc_code, only_first = TRUE))
|
||||
}
|
||||
|
||||
if (!has_internet()) {
|
||||
message_("There appears to be no internet connection, returning NA.",
|
||||
add_fn = font_red,
|
||||
as_note = FALSE)
|
||||
return(rep(NA, length(atc_code)))
|
||||
}
|
||||
|
||||
property <- tolower(property)
|
||||
# also allow unit as property
|
||||
if (property == "unit") {
|
||||
property <- "u"
|
||||
}
|
||||
if (property == "ddd") {
|
||||
returnvalue <- rep(NA_real_, length(atc_code))
|
||||
} else if (property == "groups") {
|
||||
returnvalue <- list()
|
||||
} else {
|
||||
returnvalue <- rep(NA_character_, length(atc_code))
|
||||
}
|
||||
|
||||
progress <- progress_ticker(n = length(atc_code), 3)
|
||||
on.exit(close(progress))
|
||||
|
||||
for (i in seq_len(length(atc_code))) {
|
||||
|
||||
progress$tick()
|
||||
|
||||
if (atc_code[i] %like% "^Q") {
|
||||
# veterinary drugs, ATC_vet codes start with a "Q"
|
||||
atc_url <- url_vet
|
||||
} else {
|
||||
atc_url <- url
|
||||
}
|
||||
atc_url <- sub("%s", atc_code[i], atc_url, fixed = TRUE)
|
||||
|
||||
if (property == "groups") {
|
||||
out <- tryCatch(
|
||||
read_html(atc_url) %pm>%
|
||||
html_node("#content") %pm>%
|
||||
html_children() %pm>%
|
||||
html_node("a"),
|
||||
error = function(e) NULL)
|
||||
if (is.null(out)) {
|
||||
message_("Connection to ", atc_url, " failed.")
|
||||
return(rep(NA, length(atc_code)))
|
||||
}
|
||||
|
||||
# get URLS of items
|
||||
hrefs <- out %pm>% html_attr("href")
|
||||
# get text of items
|
||||
texts <- out %pm>% html_text()
|
||||
# select only text items where URL like "code="
|
||||
texts <- texts[grepl("?code=", tolower(hrefs), fixed = TRUE)]
|
||||
# last one is antibiotics, skip it
|
||||
texts <- texts[seq_len(length(texts)) - 1]
|
||||
returnvalue <- c(list(texts), returnvalue)
|
||||
|
||||
} else {
|
||||
out <- tryCatch(
|
||||
read_html(atc_url) %pm>%
|
||||
html_nodes("table") %pm>%
|
||||
html_table(header = TRUE) %pm>%
|
||||
as.data.frame(stringsAsFactors = FALSE),
|
||||
error = function(e) NULL)
|
||||
if (is.null(out)) {
|
||||
message_("Connection to ", atc_url, " failed.")
|
||||
return(rep(NA, length(atc_code)))
|
||||
}
|
||||
|
||||
# case insensitive column names
|
||||
colnames(out) <- gsub("^atc.*", "atc", tolower(colnames(out)))
|
||||
|
||||
if (length(out) == 0) {
|
||||
warning_("in `atc_online_property()`: ATC not found: ", atc_code[i], ". Please check ", atc_url, ".")
|
||||
returnvalue[i] <- NA
|
||||
next
|
||||
}
|
||||
|
||||
if (property %in% c("atc", "name")) {
|
||||
# ATC and name are only in first row
|
||||
returnvalue[i] <- out[1, property]
|
||||
} else {
|
||||
if (!"adm.r" %in% colnames(out) | is.na(out[1, "adm.r"])) {
|
||||
returnvalue[i] <- NA
|
||||
next
|
||||
} else {
|
||||
for (j in seq_len(nrow(out))) {
|
||||
if (out[j, "adm.r"] == administration) {
|
||||
returnvalue[i] <- out[j, property]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (property == "groups" & length(returnvalue) == 1) {
|
||||
returnvalue <- returnvalue[[1]]
|
||||
}
|
||||
|
||||
returnvalue
|
||||
}
|
||||
|
||||
#' @rdname atc_online
|
||||
#' @export
|
||||
atc_online_groups <- function(atc_code, ...) {
|
||||
meet_criteria(atc_code, allow_class = "character")
|
||||
atc_online_property(atc_code = atc_code, property = "groups", ...)
|
||||
}
|
||||
|
||||
#' @rdname atc_online
|
||||
#' @export
|
||||
atc_online_ddd <- function(atc_code, ...) {
|
||||
meet_criteria(atc_code, allow_class = "character")
|
||||
atc_online_property(atc_code = atc_code, property = "ddd", ...)
|
||||
}
|
||||
|
||||
#' @rdname atc_online
|
||||
#' @export
|
||||
atc_online_ddd_units <- function(atc_code, ...) {
|
||||
meet_criteria(atc_code, allow_class = "character")
|
||||
atc_online_property(atc_code = atc_code, property = "unit", ...)
|
||||
}
|
||||
@@ -1,94 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Check Availability of Columns
|
||||
#'
|
||||
#' Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. [susceptibility()] and [resistance()].
|
||||
#' @param tbl a [data.frame] or [list]
|
||||
#' @param width number of characters to present the visual availability, defaults to filling the width of the console
|
||||
#' @details The function returns a [data.frame] with columns `"resistant"` and `"visual_resistance"`. The values in that columns are calculated with [resistance()].
|
||||
#' @return [data.frame] with column names of `tbl` as row names
|
||||
#' @export
|
||||
#' @examples
|
||||
#' availability(example_isolates)
|
||||
#' \donttest{
|
||||
#' if (require("dplyr")) {
|
||||
#' example_isolates %>%
|
||||
#' filter(mo == as.mo("E. coli")) %>%
|
||||
#' select_if(is.rsi) %>%
|
||||
#' availability()
|
||||
#' }
|
||||
#' }
|
||||
availability <- function(tbl, width = NULL) {
|
||||
meet_criteria(tbl, allow_class = "data.frame")
|
||||
meet_criteria(width, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
|
||||
|
||||
x <- vapply(FUN.VALUE = double(1), tbl, function(x) {
|
||||
1 - sum(is.na(x)) / length(x)
|
||||
})
|
||||
n <- vapply(FUN.VALUE = double(1), tbl, function(x) length(x[!is.na(x)]))
|
||||
R <- vapply(FUN.VALUE = double(1), tbl, function(x) ifelse(is.rsi(x), resistance(x, minimum = 0), NA_real_))
|
||||
R_print <- character(length(R))
|
||||
R_print[!is.na(R)] <- percentage(R[!is.na(R)])
|
||||
R_print[is.na(R)] <- ""
|
||||
|
||||
if (is.null(width)) {
|
||||
width <- options()$width -
|
||||
(max(nchar(colnames(tbl))) +
|
||||
# count col
|
||||
8 +
|
||||
# available % column
|
||||
10 +
|
||||
# resistant % column
|
||||
10 +
|
||||
# extra margin
|
||||
5)
|
||||
width <- width / 2
|
||||
}
|
||||
|
||||
if (length(R[is.na(R)]) == ncol(tbl)) {
|
||||
width <- width * 2 + 10
|
||||
}
|
||||
|
||||
x_chars_R <- strrep("#", round(width * R, digits = 2))
|
||||
x_chars_SI <- strrep("-", width - nchar(x_chars_R))
|
||||
vis_resistance <- paste0("|", x_chars_R, x_chars_SI, "|")
|
||||
vis_resistance[is.na(R)] <- ""
|
||||
|
||||
x_chars <- strrep("#", round(x, digits = 2) / (1 / width))
|
||||
x_chars_empty <- strrep("-", width - nchar(x_chars))
|
||||
|
||||
df <- data.frame(count = n,
|
||||
available = percentage(x),
|
||||
visual_availabilty = paste0("|", x_chars, x_chars_empty, "|"),
|
||||
resistant = R_print,
|
||||
visual_resistance = vis_resistance,
|
||||
stringsAsFactors = FALSE)
|
||||
if (length(R[is.na(R)]) == ncol(tbl)) {
|
||||
df[, 1:3]
|
||||
} else {
|
||||
df
|
||||
}
|
||||
}
|
||||
@@ -1,315 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Determine Bug-Drug Combinations
|
||||
#'
|
||||
#' Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use [format()] on the result to prettify it to a publishable/printable format, see *Examples*.
|
||||
#' @inheritParams eucast_rules
|
||||
#' @param combine_IR a [logical] to indicate whether values R and I should be summed
|
||||
#' @param add_ab_group a [logical] to indicate where the group of the antimicrobials must be included as a first column
|
||||
#' @param remove_intrinsic_resistant [logical] to indicate that rows and columns with 100% resistance for all tested antimicrobials must be removed from the table
|
||||
#' @param FUN the function to call on the `mo` column to transform the microorganism codes, defaults to [mo_shortname()]
|
||||
#' @param translate_ab a [character] of length 1 containing column names of the [antibiotics] data set
|
||||
#' @param ... arguments passed on to `FUN`
|
||||
#' @inheritParams rsi_df
|
||||
#' @inheritParams base::formatC
|
||||
#' @details The function [format()] calculates the resistance per bug-drug combination. Use `combine_IR = FALSE` (default) to test R vs. S+I and `combine_IR = TRUE` to test R+I vs. S.
|
||||
#' @export
|
||||
#' @rdname bug_drug_combinations
|
||||
#' @return The function [bug_drug_combinations()] returns a [data.frame] with columns "mo", "ab", "S", "I", "R" and "total".
|
||||
#' @source \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, *Clinical and Laboratory Standards Institute (CLSI)*. <https://clsi.org/standards/products/microbiology/documents/m39/>.
|
||||
#' @examples
|
||||
#' \donttest{
|
||||
#' x <- bug_drug_combinations(example_isolates)
|
||||
#' head(x)
|
||||
#' format(x, translate_ab = "name (atc)")
|
||||
#'
|
||||
#' # Use FUN to change to transformation of microorganism codes
|
||||
#' bug_drug_combinations(example_isolates,
|
||||
#' FUN = mo_gramstain)
|
||||
#'
|
||||
#' bug_drug_combinations(example_isolates,
|
||||
#' FUN = function(x) ifelse(x == as.mo("E. coli"),
|
||||
#' "E. coli",
|
||||
#' "Others"))
|
||||
#' }
|
||||
bug_drug_combinations <- function(x,
|
||||
col_mo = NULL,
|
||||
FUN = mo_shortname,
|
||||
...) {
|
||||
meet_criteria(x, allow_class = "data.frame", contains_column_class = "rsi")
|
||||
meet_criteria(col_mo, allow_class = "character", is_in = colnames(x), has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(FUN, allow_class = "function", has_length = 1)
|
||||
|
||||
# try to find columns based on type
|
||||
# -- mo
|
||||
if (is.null(col_mo)) {
|
||||
col_mo <- search_type_in_df(x = x, type = "mo")
|
||||
stop_if(is.null(col_mo), "`col_mo` must be set")
|
||||
} else {
|
||||
stop_ifnot(col_mo %in% colnames(x), "column '", col_mo, "' (`col_mo`) not found")
|
||||
}
|
||||
|
||||
x.bak <- x
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
||||
x[, col_mo] <- FUN(x[, col_mo, drop = TRUE], ...)
|
||||
|
||||
unique_mo <- sort(unique(x[, col_mo, drop = TRUE]))
|
||||
|
||||
# select only groups and antibiotics
|
||||
if (is_null_or_grouped_tbl(x.bak)) {
|
||||
data_has_groups <- TRUE
|
||||
groups <- setdiff(names(attributes(x.bak)$groups), ".rows")
|
||||
x <- x[, c(groups, col_mo, colnames(x)[vapply(FUN.VALUE = logical(1), x, is.rsi)]), drop = FALSE]
|
||||
} else {
|
||||
data_has_groups <- FALSE
|
||||
x <- x[, c(col_mo, names(which(vapply(FUN.VALUE = logical(1), x, is.rsi)))), drop = FALSE]
|
||||
}
|
||||
|
||||
run_it <- function(x) {
|
||||
out <- data.frame(mo = character(0),
|
||||
ab = character(0),
|
||||
S = integer(0),
|
||||
I = integer(0),
|
||||
R = integer(0),
|
||||
total = integer(0),
|
||||
stringsAsFactors = FALSE)
|
||||
if (data_has_groups) {
|
||||
group_values <- unique(x[, which(colnames(x) %in% groups), drop = FALSE])
|
||||
rownames(group_values) <- NULL
|
||||
x <- x[, which(!colnames(x) %in% groups), drop = FALSE]
|
||||
}
|
||||
|
||||
for (i in seq_len(length(unique_mo))) {
|
||||
# filter on MO group and only select R/SI columns
|
||||
x_mo_filter <- x[which(x[, col_mo, drop = TRUE] == unique_mo[i]), names(which(vapply(FUN.VALUE = logical(1), x, is.rsi))), drop = FALSE]
|
||||
# turn and merge everything
|
||||
pivot <- lapply(x_mo_filter, function(x) {
|
||||
m <- as.matrix(table(x))
|
||||
data.frame(S = m["S", ], I = m["I", ], R = m["R", ], stringsAsFactors = FALSE)
|
||||
})
|
||||
merged <- do.call(rbind, pivot)
|
||||
out_group <- data.frame(mo = rep(unique_mo[i], NROW(merged)),
|
||||
ab = rownames(merged),
|
||||
S = merged$S,
|
||||
I = merged$I,
|
||||
R = merged$R,
|
||||
total = merged$S + merged$I + merged$R,
|
||||
stringsAsFactors = FALSE)
|
||||
if (data_has_groups) {
|
||||
if (nrow(group_values) < nrow(out_group)) {
|
||||
# repeat group_values for the number of rows in out_group
|
||||
repeated <- rep(seq_len(nrow(group_values)),
|
||||
each = nrow(out_group) / nrow(group_values))
|
||||
group_values <- group_values[repeated, , drop = FALSE]
|
||||
}
|
||||
out_group <- cbind(group_values, out_group)
|
||||
}
|
||||
out <- rbind(out, out_group, stringsAsFactors = FALSE)
|
||||
}
|
||||
out
|
||||
}
|
||||
# based on pm_apply_grouped_function
|
||||
apply_group <- function(.data, fn, groups, drop = FALSE, ...) {
|
||||
grouped <- pm_split_into_groups(.data, groups, drop)
|
||||
res <- do.call(rbind, unname(lapply(grouped, fn, ...)))
|
||||
if (any(groups %in% colnames(res))) {
|
||||
class(res) <- c("grouped_data", class(res))
|
||||
res <- pm_set_groups(res, groups[groups %in% colnames(res)])
|
||||
}
|
||||
res
|
||||
}
|
||||
|
||||
if (data_has_groups) {
|
||||
out <- apply_group(x, "run_it", groups)
|
||||
rownames(out) <- NULL
|
||||
set_clean_class(out,
|
||||
new_class = c("grouped", "bug_drug_combinations", "data.frame"))
|
||||
} else {
|
||||
out <- run_it(x)
|
||||
rownames(out) <- NULL
|
||||
set_clean_class(out,
|
||||
new_class = c("bug_drug_combinations", "data.frame"))
|
||||
}
|
||||
}
|
||||
|
||||
#' @method format bug_drug_combinations
|
||||
#' @export
|
||||
#' @rdname bug_drug_combinations
|
||||
format.bug_drug_combinations <- function(x,
|
||||
translate_ab = "name (ab, atc)",
|
||||
language = get_AMR_locale(),
|
||||
minimum = 30,
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE,
|
||||
add_ab_group = TRUE,
|
||||
remove_intrinsic_resistant = FALSE,
|
||||
decimal.mark = getOption("OutDec"),
|
||||
big.mark = ifelse(decimal.mark == ",", ".", ","),
|
||||
...) {
|
||||
meet_criteria(x, allow_class = "data.frame")
|
||||
meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(combine_IR, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(add_ab_group, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(remove_intrinsic_resistant, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(decimal.mark, allow_class = "character", has_length = 1)
|
||||
meet_criteria(big.mark, allow_class = "character", has_length = 1)
|
||||
|
||||
if (inherits(x, "grouped")) {
|
||||
# bug_drug_combinations() has been run on groups, so de-group here
|
||||
warning_("in `format()`: formatting the output of `bug_drug_combinations()` does not support grouped variables, they were ignored")
|
||||
idx <- split(seq_len(nrow(x)), paste0(x$mo, "%%", x$ab))
|
||||
x <- data.frame(mo = gsub("(.*)%%(.*)", "\\1", names(idx)),
|
||||
ab = gsub("(.*)%%(.*)", "\\2", names(idx)),
|
||||
S = sapply(idx, function(i) sum(y$S[i], na.rm = TRUE)),
|
||||
I = sapply(idx, function(i) sum(y$I[i], na.rm = TRUE)),
|
||||
R = sapply(idx, function(i) sum(y$R[i], na.rm = TRUE)),
|
||||
total = sapply(idx, function(i) sum(y$S[i], na.rm = TRUE) +
|
||||
sum(y$I[i], na.rm = TRUE) +
|
||||
sum(y$R[i], na.rm = TRUE)),
|
||||
stringsAsFactors = FALSE)
|
||||
}
|
||||
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
||||
x <- subset(x, total >= minimum)
|
||||
|
||||
if (remove_intrinsic_resistant == TRUE) {
|
||||
x <- subset(x, R != total)
|
||||
}
|
||||
if (combine_SI == TRUE | combine_IR == FALSE) {
|
||||
x$isolates <- x$R
|
||||
} else {
|
||||
x$isolates <- x$R + x$I
|
||||
}
|
||||
|
||||
give_ab_name <- function(ab, format, language) {
|
||||
format <- tolower(format)
|
||||
ab_txt <- rep(format, length(ab))
|
||||
for (i in seq_len(length(ab_txt))) {
|
||||
ab_txt[i] <- gsub("ab", as.character(as.ab(ab[i])), ab_txt[i])
|
||||
ab_txt[i] <- gsub("cid", ab_cid(ab[i]), ab_txt[i])
|
||||
ab_txt[i] <- gsub("group", ab_group(ab[i], language = language), ab_txt[i])
|
||||
ab_txt[i] <- gsub("atc_group1", ab_atc_group1(ab[i], language = language), ab_txt[i])
|
||||
ab_txt[i] <- gsub("atc_group2", ab_atc_group2(ab[i], language = language), ab_txt[i])
|
||||
ab_txt[i] <- gsub("atc", ab_atc(ab[i], only_first = TRUE), ab_txt[i])
|
||||
ab_txt[i] <- gsub("name", ab_name(ab[i], language = language), ab_txt[i])
|
||||
ab_txt[i]
|
||||
}
|
||||
ab_txt
|
||||
}
|
||||
|
||||
remove_NAs <- function(.data) {
|
||||
cols <- colnames(.data)
|
||||
.data <- as.data.frame(lapply(.data, function(x) ifelse(is.na(x), "", x)),
|
||||
stringsAsFactors = FALSE)
|
||||
colnames(.data) <- cols
|
||||
.data
|
||||
}
|
||||
|
||||
create_var <- function(.data, ...) {
|
||||
dots <- list(...)
|
||||
for (i in seq_len(length(dots))) {
|
||||
.data[, names(dots)[i]] <- dots[[i]]
|
||||
}
|
||||
.data
|
||||
}
|
||||
|
||||
y <- x %pm>%
|
||||
create_var(ab = as.ab(x$ab),
|
||||
ab_txt = give_ab_name(ab = x$ab, format = translate_ab, language = language)) %pm>%
|
||||
pm_group_by(ab, ab_txt, mo) %pm>%
|
||||
pm_summarise(isolates = sum(isolates, na.rm = TRUE),
|
||||
total = sum(total, na.rm = TRUE)) %pm>%
|
||||
pm_ungroup()
|
||||
|
||||
y <- y %pm>%
|
||||
create_var(txt = paste0(percentage(y$isolates / y$total, decimal.mark = decimal.mark, big.mark = big.mark),
|
||||
" (", trimws(format(y$isolates, big.mark = big.mark)), "/",
|
||||
trimws(format(y$total, big.mark = big.mark)), ")")) %pm>%
|
||||
pm_select(ab, ab_txt, mo, txt) %pm>%
|
||||
pm_arrange(mo)
|
||||
|
||||
# replace tidyr::pivot_wider() from here
|
||||
for (i in unique(y$mo)) {
|
||||
mo_group <- y[which(y$mo == i), c("ab", "txt")]
|
||||
colnames(mo_group) <- c("ab", i)
|
||||
rownames(mo_group) <- NULL
|
||||
y <- y %pm>%
|
||||
pm_left_join(mo_group, by = "ab")
|
||||
}
|
||||
y <- y %pm>%
|
||||
pm_distinct(ab, .keep_all = TRUE) %pm>%
|
||||
pm_select(-mo, -txt) %pm>%
|
||||
# replace tidyr::pivot_wider() until here
|
||||
remove_NAs()
|
||||
|
||||
select_ab_vars <- function(.data) {
|
||||
.data[, c("ab_group", "ab_txt", colnames(.data)[!colnames(.data) %in% c("ab_group", "ab_txt", "ab")])]
|
||||
}
|
||||
|
||||
y <- y %pm>%
|
||||
create_var(ab_group = ab_group(y$ab, language = language)) %pm>%
|
||||
select_ab_vars() %pm>%
|
||||
pm_arrange(ab_group, ab_txt)
|
||||
y <- y %pm>%
|
||||
create_var(ab_group = ifelse(y$ab_group != pm_lag(y$ab_group) | is.na(pm_lag(y$ab_group)), y$ab_group, ""))
|
||||
|
||||
if (add_ab_group == FALSE) {
|
||||
y <- y %pm>%
|
||||
pm_select(-ab_group) %pm>%
|
||||
pm_rename("Drug" = ab_txt)
|
||||
colnames(y)[1] <- translate_into_language(colnames(y)[1], language, only_unknown = FALSE)
|
||||
} else {
|
||||
y <- y %pm>%
|
||||
pm_rename("Group" = ab_group,
|
||||
"Drug" = ab_txt)
|
||||
}
|
||||
|
||||
if (!is.null(language)) {
|
||||
colnames(y) <- translate_into_language(colnames(y), language, only_unknown = FALSE)
|
||||
}
|
||||
|
||||
if (remove_intrinsic_resistant == TRUE) {
|
||||
y <- y[, !vapply(FUN.VALUE = logical(1), y, function(col) all(col %like% "100", na.rm = TRUE) & !any(is.na(col))), drop = FALSE]
|
||||
}
|
||||
|
||||
rownames(y) <- NULL
|
||||
y
|
||||
}
|
||||
|
||||
#' @method print bug_drug_combinations
|
||||
#' @export
|
||||
print.bug_drug_combinations <- function(x, ...) {
|
||||
x_class <- class(x)
|
||||
print(set_clean_class(x,
|
||||
new_class = x_class[!x_class %in% c("bug_drug_combinations", "grouped")]),
|
||||
...)
|
||||
message_("Use 'format()' on this result to get a publishable/printable format.",
|
||||
ifelse(inherits(x, "grouped"), " Note: The grouping variable(s) will be ignored.", ""),
|
||||
as_note = FALSE)
|
||||
}
|
||||
@@ -1,134 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
format_included_data_number <- function(data) {
|
||||
if (is.data.frame(data)) {
|
||||
n <- nrow(data)
|
||||
} else {
|
||||
n <- length(unique(data))
|
||||
}
|
||||
if (n > 10000) {
|
||||
rounder <- -3 # round on thousands
|
||||
} else if (n > 1000) {
|
||||
rounder <- -2 # round on hundreds
|
||||
} else {
|
||||
rounder <- -1 # round on tens
|
||||
}
|
||||
paste0("~", format(round(n, rounder), decimal.mark = ".", big.mark = ","))
|
||||
}
|
||||
|
||||
#' The Catalogue of Life
|
||||
#'
|
||||
#' This package contains the complete taxonomic tree (last updated: `r CATALOGUE_OF_LIFE$yearmonth_LPSN`) of almost all microorganisms from the authoritative and comprehensive Catalogue of Life (CoL), supplemented with data from the List of Prokaryotic names with Standing in Nomenclature (LPSN).
|
||||
#' @section Catalogue of Life:
|
||||
#' \if{html}{\figure{logo_col.png}{options: height="40" style=margin-bottom:"5"} \cr}
|
||||
#' This package contains the complete taxonomic tree of almost all microorganisms (`r format_included_data_number(microorganisms)` species) from the authoritative and comprehensive Catalogue of Life (CoL, <http://www.catalogueoflife.org>). The CoL is the most comprehensive and authoritative global index of species currently available. Nonetheless, we supplemented the CoL data with data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, [lpsn.dsmz.de](https://lpsn.dsmz.de)). This supplementation is needed until the [CoL+ project](https://github.com/CatalogueOfLife/general) is finished, which we await.
|
||||
#'
|
||||
#' [Click here][catalogue_of_life] for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with [catalogue_of_life_version()].
|
||||
#' @section Included Taxa:
|
||||
#' Included are:
|
||||
#' - All `r format_included_data_number(microorganisms[which(microorganisms$kingdom %in% c("Archeae", "Bacteria", "Chromista", "Protozoa")), ])` (sub)species from the kingdoms of Archaea, Bacteria, Chromista and Protozoa
|
||||
#' - All `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Fungi" & microorganisms$order %in% c("Eurotiales", "Microascales", "Mucorales", "Onygenales", "Pneumocystales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales")), ])` (sub)species from these orders of the kingdom of Fungi: Eurotiales, Microascales, Mucorales, Onygenales, Pneumocystales, Saccharomycetales, Schizosaccharomycetales and Tremellales, as well as `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Fungi" & !microorganisms$order %in% c("Eurotiales", "Microascales", "Mucorales", "Onygenales", "Pneumocystales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales")), ])` other fungal (sub)species. The kingdom of Fungi is a very large taxon with almost 300,000 different (sub)species, of which most are not microbial (but rather macroscopic, like mushrooms). Because of this, not all fungi fit the scope of this package and including everything would tremendously slow down our algorithms too. By only including the aforementioned taxonomic orders, the most relevant fungi are covered (such as all species of *Aspergillus*, *Candida*, *Cryptococcus*, *Histplasma*, *Pneumocystis*, *Saccharomyces* and *Trichophyton*).
|
||||
#' - All `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Animalia"), ])` (sub)species from `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Animalia"), "genus"])` other relevant genera from the kingdom of Animalia (such as *Strongyloides* and *Taenia*)
|
||||
#' - All `r format_included_data_number(microorganisms.old)` previously accepted names of all included (sub)species (these were taxonomically renamed)
|
||||
#' - The complete taxonomic tree of all included (sub)species: from kingdom to subspecies
|
||||
#' - The responsible author(s) and year of scientific publication
|
||||
#'
|
||||
#' The Catalogue of Life (<http://www.catalogueoflife.org>) is the most comprehensive and authoritative global index of species currently available. It holds essential information on the names, relationships and distributions of over 1.9 million species. The Catalogue of Life is used to support the major biodiversity and conservation information services such as the Global Biodiversity Information Facility (GBIF), Encyclopedia of Life (EoL) and the International Union for Conservation of Nature Red List. It is recognised by the Convention on Biological Diversity as a significant component of the Global Taxonomy Initiative and a contribution to Target 1 of the Global Strategy for Plant Conservation.
|
||||
#'
|
||||
#' The syntax used to transform the original data to a cleansed \R format, can be found here: <https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R>.
|
||||
#' @name catalogue_of_life
|
||||
#' @rdname catalogue_of_life
|
||||
#' @seealso Data set [microorganisms] for the actual data. \cr
|
||||
#' Function [as.mo()] to use the data for intelligent determination of microorganisms.
|
||||
#' @examples
|
||||
#' # Get version info of included data set
|
||||
#' catalogue_of_life_version()
|
||||
#'
|
||||
#'
|
||||
#' # Get a note when a species was renamed
|
||||
#' mo_shortname("Chlamydophila psittaci")
|
||||
#'
|
||||
#' # Get any property from the entire taxonomic tree for all included species
|
||||
#' mo_class("E. coli")
|
||||
#'
|
||||
#' mo_family("E. coli")
|
||||
#'
|
||||
#' mo_gramstain("E. coli") # based on kingdom and phylum, see ?mo_gramstain
|
||||
#'
|
||||
#' mo_ref("E. coli")
|
||||
#'
|
||||
#' # Do not get mistaken - this package is about microorganisms
|
||||
#' mo_kingdom("C. elegans")
|
||||
#' mo_name("C. elegans")
|
||||
NULL
|
||||
|
||||
#' Version info of included Catalogue of Life
|
||||
#'
|
||||
#' This function returns information about the included data from the Catalogue of Life.
|
||||
#' @seealso [microorganisms]
|
||||
#' @details For LPSN, see [microorganisms].
|
||||
#' @return a [list], which prints in pretty format
|
||||
#' @inheritSection catalogue_of_life Catalogue of Life
|
||||
#' @export
|
||||
catalogue_of_life_version <- function() {
|
||||
|
||||
check_dataset_integrity()
|
||||
|
||||
# see the `CATALOGUE_OF_LIFE` list in R/globals.R
|
||||
lst <- list(CoL =
|
||||
list(version = gsub("{year}", CATALOGUE_OF_LIFE$year, CATALOGUE_OF_LIFE$version, fixed = TRUE),
|
||||
url = gsub("{year}", CATALOGUE_OF_LIFE$year, CATALOGUE_OF_LIFE$url_CoL, fixed = TRUE),
|
||||
n = nrow(pm_filter(microorganisms, source == "CoL"))),
|
||||
LPSN =
|
||||
list(version = "List of Prokaryotic names with Standing in Nomenclature",
|
||||
url = CATALOGUE_OF_LIFE$url_LPSN,
|
||||
yearmonth = CATALOGUE_OF_LIFE$yearmonth_LPSN,
|
||||
n = nrow(pm_filter(microorganisms, source == "LPSN"))),
|
||||
total_included =
|
||||
list(
|
||||
n_total_species = nrow(microorganisms),
|
||||
n_total_synonyms = nrow(microorganisms.old)))
|
||||
|
||||
set_clean_class(lst,
|
||||
new_class = c("catalogue_of_life_version", "list"))
|
||||
}
|
||||
|
||||
#' @method print catalogue_of_life_version
|
||||
#' @export
|
||||
#' @noRd
|
||||
print.catalogue_of_life_version <- function(x, ...) {
|
||||
cat(paste0(font_bold("Included in this AMR package (v", utils::packageDescription("AMR")$Version, ") are:\n\n", collapse = ""),
|
||||
font_underline(x$CoL$version), "\n",
|
||||
" Available at: ", font_blue(x$CoL$url), "\n",
|
||||
" Number of included microbial species: ", format(x$CoL$n, big.mark = ","), "\n",
|
||||
font_underline(paste0(x$LPSN$version, " (",
|
||||
x$LPSN$yearmonth, ")")), "\n",
|
||||
" Available at: ", font_blue(x$LPSN$url), "\n",
|
||||
" Number of included bacterial species: ", format(x$LPSN$n, big.mark = ","), "\n\n",
|
||||
"=> Total number of species included: ", format(x$total_included$n_total_species, big.mark = ","), "\n",
|
||||
"=> Total number of synonyms included: ", format(x$total_included$n_total_synonyms, big.mark = ","), "\n\n",
|
||||
"See for more info ", font_grey_bg("`?microorganisms`"), " and ", font_grey_bg("`?catalogue_of_life`"), ".\n"))
|
||||
}
|
||||
@@ -1,228 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Count Available Isolates
|
||||
#'
|
||||
#' @description These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in `summarise()` from the `dplyr` package and also support grouped variables, see *Examples*.
|
||||
#'
|
||||
#' [count_resistant()] should be used to count resistant isolates, [count_susceptible()] should be used to count susceptible isolates.
|
||||
#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with [as.rsi()] if needed.
|
||||
#' @inheritParams proportion
|
||||
#' @inheritSection as.rsi Interpretation of R and S/I
|
||||
#' @details These functions are meant to count isolates. Use the [resistance()]/[susceptibility()] functions to calculate microbial resistance/susceptibility.
|
||||
#'
|
||||
#' The function [count_resistant()] is equal to the function [count_R()]. The function [count_susceptible()] is equal to the function [count_SI()].
|
||||
#'
|
||||
#' The function [n_rsi()] is an alias of [count_all()]. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to `n_distinct()`. Their function is equal to `count_susceptible(...) + count_resistant(...)`.
|
||||
#'
|
||||
#' The function [count_df()] takes any variable from `data` that has an [`rsi`] class (created with [as.rsi()]) and counts the number of S's, I's and R's. It also supports grouped variables. The function [rsi_df()] works exactly like [count_df()], but adds the percentage of S, I and R.
|
||||
#' @inheritSection proportion Combination Therapy
|
||||
#' @seealso [`proportion_*`][proportion] to calculate microbial resistance and susceptibility.
|
||||
#' @return An [integer]
|
||||
#' @rdname count
|
||||
#' @name count
|
||||
#' @export
|
||||
#' @examples
|
||||
#' # example_isolates is a data set available in the AMR package.
|
||||
#' # run ?example_isolates for more info.
|
||||
#'
|
||||
#' # base R ------------------------------------------------------------
|
||||
#' count_resistant(example_isolates$AMX) # counts "R"
|
||||
#' count_susceptible(example_isolates$AMX) # counts "S" and "I"
|
||||
#' count_all(example_isolates$AMX) # counts "S", "I" and "R"
|
||||
#'
|
||||
#' # be more specific
|
||||
#' count_S(example_isolates$AMX)
|
||||
#' count_SI(example_isolates$AMX)
|
||||
#' count_I(example_isolates$AMX)
|
||||
#' count_IR(example_isolates$AMX)
|
||||
#' count_R(example_isolates$AMX)
|
||||
#'
|
||||
#' # Count all available isolates
|
||||
#' count_all(example_isolates$AMX)
|
||||
#' n_rsi(example_isolates$AMX)
|
||||
#'
|
||||
#' # n_rsi() is an alias of count_all().
|
||||
#' # Since it counts all available isolates, you can
|
||||
#' # calculate back to count e.g. susceptible isolates.
|
||||
#' # These results are the same:
|
||||
#' count_susceptible(example_isolates$AMX)
|
||||
#' susceptibility(example_isolates$AMX) * n_rsi(example_isolates$AMX)
|
||||
#'
|
||||
#' # dplyr -------------------------------------------------------------
|
||||
#' \donttest{
|
||||
#' if (require("dplyr")) {
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(R = count_R(CIP),
|
||||
#' I = count_I(CIP),
|
||||
#' S = count_S(CIP),
|
||||
#' n1 = count_all(CIP), # the actual total; sum of all three
|
||||
#' n2 = n_rsi(CIP), # same - analogous to n_distinct
|
||||
#' total = n()) # NOT the number of tested isolates!
|
||||
#'
|
||||
#' # Number of available isolates for a whole antibiotic class
|
||||
#' # (i.e., in this data set columns GEN, TOB, AMK, KAN)
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(across(aminoglycosides(), n_rsi))
|
||||
#'
|
||||
#' # Count co-resistance between amoxicillin/clav acid and gentamicin,
|
||||
#' # so we can see that combination therapy does a lot more than mono therapy.
|
||||
#' # Please mind that `susceptibility()` calculates percentages right away instead.
|
||||
#' example_isolates %>% count_susceptible(AMC) # 1433
|
||||
#' example_isolates %>% count_all(AMC) # 1879
|
||||
#'
|
||||
#' example_isolates %>% count_susceptible(GEN) # 1399
|
||||
#' example_isolates %>% count_all(GEN) # 1855
|
||||
#'
|
||||
#' example_isolates %>% count_susceptible(AMC, GEN) # 1764
|
||||
#' example_isolates %>% count_all(AMC, GEN) # 1936
|
||||
#'
|
||||
#' # Get number of S+I vs. R immediately of selected columns
|
||||
#' example_isolates %>%
|
||||
#' select(AMX, CIP) %>%
|
||||
#' count_df(translate = FALSE)
|
||||
#'
|
||||
#' # It also supports grouping variables
|
||||
#' example_isolates %>%
|
||||
#' select(hospital_id, AMX, CIP) %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' count_df(translate = FALSE)
|
||||
#' }
|
||||
#' }
|
||||
count_resistant <- function(..., only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_susceptible <- function(..., only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_R <- function(..., only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_IR <- function(..., only_all_tested = FALSE) {
|
||||
if (message_not_thrown_before("count_IR", entire_session = TRUE)) {
|
||||
message_("Using `count_IR()` is discouraged; use `count_resistant()` instead to not consider \"I\" being resistant. This note will be shown once for this session.", as_note = FALSE)
|
||||
}
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("I", "R"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_I <- function(..., only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "I",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_SI <- function(..., only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_S <- function(..., only_all_tested = FALSE) {
|
||||
if (message_not_thrown_before("count_S", entire_session = TRUE)) {
|
||||
message_("Using `count_S()` is discouraged; use `count_susceptible()` instead to also consider \"I\" being susceptible. This note will be shown once for this session.", as_note = FALSE)
|
||||
}
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "S",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_all <- function(..., only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I", "R"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
n_rsi <- count_all
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_df <- function(data,
|
||||
translate_ab = "name",
|
||||
language = get_AMR_locale(),
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc_df(type = "count",
|
||||
data = data,
|
||||
translate_ab = translate_ab,
|
||||
language = language,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR,
|
||||
combine_SI_missing = missing(combine_SI)),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
@@ -1,240 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Define Custom EUCAST Rules
|
||||
#'
|
||||
#' Define custom EUCAST rules for your organisation or specific analysis and use the output of this function in [eucast_rules()].
|
||||
#' @param ... rules in [formula][`~`()] notation, see *Examples*
|
||||
#' @details
|
||||
#' Some organisations have their own adoption of EUCAST rules. This function can be used to define custom EUCAST rules to be used in the [eucast_rules()] function.
|
||||
#' @section How it works:
|
||||
#'
|
||||
#' ### Basics
|
||||
#'
|
||||
#' If you are familiar with the [`case_when()`][dplyr::case_when()] function of the `dplyr` package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written *before* the tilde (`~`) and the consequence of the rule is written *after* the tilde:
|
||||
#'
|
||||
#' ```{r}
|
||||
#' x <- custom_eucast_rules(TZP == "S" ~ aminopenicillins == "S",
|
||||
#' TZP == "R" ~ aminopenicillins == "R")
|
||||
#' ```
|
||||
#'
|
||||
#' These are two custom EUCAST rules: if TZP (piperacillin/tazobactam) is "S", all aminopenicillins (ampicillin and amoxicillin) must be made "S", and if TZP is "R", aminopenicillins must be made "R". These rules can also be printed to the console, so it is immediately clear how they work:
|
||||
#'
|
||||
#' ```{r}
|
||||
#' x
|
||||
#' ```
|
||||
#'
|
||||
#' The rules (the part *before* the tilde, in above example `TZP == "S"` and `TZP == "R"`) must be evaluable in your data set: it should be able to run as a filter in your data set without errors. This means for the above example that the column `TZP` must exist. We will create a sample data set and test the rules set:
|
||||
#'
|
||||
#' ```{r}
|
||||
#' df <- data.frame(mo = c("Escherichia coli", "Klebsiella pneumoniae"),
|
||||
#' TZP = as.rsi("R"),
|
||||
#' ampi = as.rsi("S"),
|
||||
#' cipro = as.rsi("S"))
|
||||
#' df
|
||||
#'
|
||||
#' eucast_rules(df, rules = "custom", custom_rules = x, info = FALSE)
|
||||
#' ```
|
||||
#'
|
||||
#' ### Using taxonomic properties in rules
|
||||
#'
|
||||
#' There is one exception in variables used for the rules: all column names of the [microorganisms] data set can also be used, but do not have to exist in the data set. These column names are: `r vector_and(colnames(microorganisms), sort = FALSE)`. Thus, this next example will work as well, despite the fact that the `df` data set does not contain a column `genus`:
|
||||
#'
|
||||
#' ```{r}
|
||||
#' y <- custom_eucast_rules(TZP == "S" & genus == "Klebsiella" ~ aminopenicillins == "S",
|
||||
#' TZP == "R" & genus == "Klebsiella" ~ aminopenicillins == "R")
|
||||
#'
|
||||
#' eucast_rules(df, rules = "custom", custom_rules = y, info = FALSE)
|
||||
#' ```
|
||||
#'
|
||||
#' ### Usage of antibiotic group names
|
||||
#'
|
||||
#' It is possible to define antibiotic groups instead of single antibiotics for the rule consequence, the part *after* the tilde. In above examples, the antibiotic group `aminopenicillins` is used to include ampicillin and amoxicillin. The following groups are allowed (case-insensitive). Within parentheses are the agents that will be matched when running the rule.
|
||||
#'
|
||||
#' `r paste0(" * ", sapply(DEFINED_AB_GROUPS, function(x) paste0("\"", tolower(gsub("^AB_", "", x)), "\"\\cr(", vector_and(ab_name(eval(parse(text = x), envir = asNamespace("AMR")), language = NULL, tolower = TRUE), quotes = FALSE), ")"), USE.NAMES = FALSE), "\n", collapse = "")`
|
||||
#' @returns A [list] containing the custom rules
|
||||
#' @export
|
||||
#' @examples
|
||||
#' x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
|
||||
#' AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
|
||||
#' x
|
||||
#'
|
||||
#' # run the custom rule set (verbose = TRUE will return a logbook instead of the data set):
|
||||
#' eucast_rules(example_isolates,
|
||||
#' rules = "custom",
|
||||
#' custom_rules = x,
|
||||
#' info = FALSE,
|
||||
#' verbose = TRUE)
|
||||
#'
|
||||
#' # combine rule sets
|
||||
#' x2 <- c(x,
|
||||
#' custom_eucast_rules(TZP == "R" ~ carbapenems == "R"))
|
||||
#' x2
|
||||
custom_eucast_rules <- function(...) {
|
||||
|
||||
dots <- tryCatch(list(...),
|
||||
error = function(e) "error")
|
||||
stop_if(identical(dots, "error"),
|
||||
"rules must be a valid formula inputs (e.g., using '~'), see `?custom_eucast_rules`")
|
||||
n_dots <- length(dots)
|
||||
stop_if(n_dots == 0, "no custom rules were set. Please read the documentation using `?custom_eucast_rules`.")
|
||||
out <- vector("list", n_dots)
|
||||
for (i in seq_len(n_dots)) {
|
||||
stop_ifnot(inherits(dots[[i]], "formula"),
|
||||
"rule ", i, " must be a valid formula input (e.g., using '~'), see `?custom_eucast_rules`")
|
||||
|
||||
# Query
|
||||
qry <- dots[[i]][[2]]
|
||||
if (inherits(qry, "call")) {
|
||||
qry <- as.expression(qry)
|
||||
}
|
||||
qry <- as.character(qry)
|
||||
# these will prevent vectorisation, so replace them:
|
||||
qry <- gsub("&&", "&", qry, fixed = TRUE)
|
||||
qry <- gsub("||", "|", qry, fixed = TRUE)
|
||||
# format nicely, setting spaces around operators
|
||||
qry <- gsub(" *([&|+-/*^><==]+) *", " \\1 ", qry)
|
||||
qry <- gsub(" ?, ?", ", ", qry)
|
||||
qry <- gsub("'", "\"", qry, fixed = TRUE)
|
||||
out[[i]]$query <- as.expression(qry)
|
||||
|
||||
# Resulting rule
|
||||
result <- dots[[i]][[3]]
|
||||
stop_ifnot(deparse(result) %like% "==",
|
||||
"the result of rule ", i, " (the part after the `~`) must contain `==`, such as in `... ~ ampicillin == \"R\"`, see `?custom_eucast_rules`")
|
||||
result_group <- as.character(result)[[2]]
|
||||
if (paste0("AB_", toupper(result_group), "S") %in% DEFINED_AB_GROUPS) {
|
||||
# support for e.g. 'aminopenicillin' if user meant 'aminopenicillins'
|
||||
result_group <- paste0(result_group, "s")
|
||||
}
|
||||
if (paste0("AB_", toupper(result_group)) %in% DEFINED_AB_GROUPS) {
|
||||
result_group <- eval(parse(text = paste0("AB_", toupper(result_group))), envir = asNamespace("AMR"))
|
||||
} else {
|
||||
result_group <- tryCatch(
|
||||
suppressWarnings(as.ab(result_group,
|
||||
fast_mode = TRUE,
|
||||
flag_multiple_results = FALSE)),
|
||||
error = function(e) NA_character_)
|
||||
}
|
||||
|
||||
stop_if(any(is.na(result_group)),
|
||||
"this result of rule ", i, " could not be translated to a single antimicrobial agent/group: \"",
|
||||
as.character(result)[[2]], "\".\n\nThe input can be a name or code of an antimicrobial agent, or be one of: ",
|
||||
vector_or(tolower(gsub("AB_", "", DEFINED_AB_GROUPS)), quotes = FALSE), ".")
|
||||
result_value <- as.character(result)[[3]]
|
||||
result_value[result_value == "NA"] <- NA
|
||||
stop_ifnot(result_value %in% c("R", "S", "I", NA),
|
||||
"the resulting value of rule ", i, " must be either \"R\", \"S\", \"I\" or NA")
|
||||
result_value <- as.rsi(result_value)
|
||||
|
||||
out[[i]]$result_group <- result_group
|
||||
out[[i]]$result_value <- result_value
|
||||
}
|
||||
|
||||
names(out) <- paste0("rule", seq_len(n_dots))
|
||||
set_clean_class(out, new_class = c("custom_eucast_rules", "list"))
|
||||
}
|
||||
|
||||
#' @method c custom_eucast_rules
|
||||
#' @noRd
|
||||
#' @export
|
||||
c.custom_eucast_rules <- function(x, ...) {
|
||||
if (length(list(...)) == 0) {
|
||||
return(x)
|
||||
}
|
||||
out <- unclass(x)
|
||||
for (e in list(...)) {
|
||||
out <- c(out, unclass(e))
|
||||
}
|
||||
names(out) <- paste0("rule", seq_len(length(out)))
|
||||
set_clean_class(out, new_class = c("custom_eucast_rules", "list"))
|
||||
}
|
||||
|
||||
#' @method as.list custom_eucast_rules
|
||||
#' @noRd
|
||||
#' @export
|
||||
as.list.custom_eucast_rules <- function(x, ...) {
|
||||
c(x, ...)
|
||||
}
|
||||
|
||||
#' @method print custom_eucast_rules
|
||||
#' @export
|
||||
#' @noRd
|
||||
print.custom_eucast_rules <- function(x, ...) {
|
||||
cat("A set of custom EUCAST rules:\n")
|
||||
for (i in seq_len(length(x))) {
|
||||
rule <- x[[i]]
|
||||
rule$query <- format_custom_query_rule(rule$query)
|
||||
if (is.na(rule$result_value)) {
|
||||
val <- font_red("<NA>")
|
||||
} else if (rule$result_value == "R") {
|
||||
val <- font_rsi_R_bg(font_black(" R "))
|
||||
} else if (rule$result_value == "S") {
|
||||
val <- font_rsi_S_bg(font_black(" S "))
|
||||
} else {
|
||||
val <- font_rsi_I_bg(font_black(" I "))
|
||||
}
|
||||
agents <- paste0(font_blue(ab_name(rule$result_group, language = NULL, tolower = TRUE),
|
||||
collapse = NULL),
|
||||
" (", rule$result_group, ")")
|
||||
agents <- sort(agents)
|
||||
rule_if <- word_wrap(paste0(i, ". ", font_bold("If "), font_blue(rule$query), font_bold(" then "),
|
||||
"set to {result}:"),
|
||||
extra_indent = 5)
|
||||
rule_if <- gsub("{result}", val, rule_if, fixed = TRUE)
|
||||
rule_then <- paste0(" ", word_wrap(paste0(agents, collapse = ", "), extra_indent = 5))
|
||||
cat("\n ", rule_if, "\n", rule_then, "\n", sep = "")
|
||||
}
|
||||
}
|
||||
|
||||
format_custom_query_rule <- function(query, colours = has_colour()) {
|
||||
query <- gsub(" & ", font_black(font_bold(" and ")), query, fixed = TRUE)
|
||||
query <- gsub(" | ", font_black(" or "), query, fixed = TRUE)
|
||||
query <- gsub(" + ", font_black(" plus "), query, fixed = TRUE)
|
||||
query <- gsub(" - ", font_black(" minus "), query, fixed = TRUE)
|
||||
query <- gsub(" / ", font_black(" divided by "), query, fixed = TRUE)
|
||||
query <- gsub(" * ", font_black(" times "), query, fixed = TRUE)
|
||||
query <- gsub(" == ", font_black(" is "), query, fixed = TRUE)
|
||||
query <- gsub(" > ", font_black(" is higher than "), query, fixed = TRUE)
|
||||
query <- gsub(" < ", font_black(" is lower than "), query, fixed = TRUE)
|
||||
query <- gsub(" >= ", font_black(" is higher than or equal to "), query, fixed = TRUE)
|
||||
query <- gsub(" <= ", font_black(" is lower than or equal to "), query, fixed = TRUE)
|
||||
query <- gsub(" ^ ", font_black(" to the power of "), query, fixed = TRUE)
|
||||
query <- gsub(" %in% ", font_black(" is one of "), query, fixed = TRUE)
|
||||
query <- gsub(" %like% ", font_black(" resembles "), query, fixed = TRUE)
|
||||
if (colours == TRUE) {
|
||||
query <- gsub('"R"', font_rsi_R_bg(font_black(" R ")), query, fixed = TRUE)
|
||||
query <- gsub('"S"', font_rsi_S_bg(font_black(" S ")), query, fixed = TRUE)
|
||||
query <- gsub('"I"', font_rsi_I_bg(font_black(" I ")), query, fixed = TRUE)
|
||||
}
|
||||
# replace the black colour 'stops' with blue colour 'starts'
|
||||
query <- gsub("\033[39m", "\033[34m", as.character(query), fixed = TRUE)
|
||||
# start with blue
|
||||
query <- paste0("\033[34m", query)
|
||||
if (colours == FALSE) {
|
||||
query <- font_stripstyle(query)
|
||||
}
|
||||
query
|
||||
}
|
||||
@@ -1,299 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Data Sets with `r format(nrow(antibiotics) + nrow(antivirals), big.mark = ",")` Antimicrobial Drugs
|
||||
#'
|
||||
#' Two data sets containing all antibiotics/antimycotics and antivirals. Use [as.ab()] or one of the [`ab_*`][ab_property()] functions to retrieve values from the [antibiotics] data set. Three identifiers are included in this data set: an antibiotic ID (`ab`, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (`atc`) as defined by the WHO, and a Compound ID (`cid`) as found in PubChem. Other properties in this data set are derived from one or more of these codes. Note that some drugs have multiple ATC codes.
|
||||
#' @format
|
||||
#' ## For the [antibiotics] data set: a [data.frame] with `r nrow(antibiotics)` observations and `r ncol(antibiotics)` variables:
|
||||
#' - `ab`\cr Antibiotic ID as used in this package (such as `AMC`), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
|
||||
#' - `cid`\cr Compound ID as found in PubChem
|
||||
#' - `name`\cr Official name as used by WHONET/EARS-Net or the WHO
|
||||
#' - `group`\cr A short and concise group name, based on WHONET and WHOCC definitions
|
||||
#' - `atc`\cr ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC, like `J01CR02`
|
||||
#' - `atc_group1`\cr Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC, like `"Macrolides, lincosamides and streptogramins"`
|
||||
#' - `atc_group2`\cr Official chemical subgroup (4th level ATC code) as defined by the WHOCC, like `"Macrolides"`
|
||||
#' - `abbr`\cr List of abbreviations as used in many countries, also for antibiotic susceptibility testing (AST)
|
||||
#' - `synonyms`\cr Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID
|
||||
#' - `oral_ddd`\cr Defined Daily Dose (DDD), oral treatment, currently available for `r sum(!is.na(antibiotics$oral_ddd))` drugs
|
||||
#' - `oral_units`\cr Units of `oral_ddd`
|
||||
#' - `iv_ddd`\cr Defined Daily Dose (DDD), parenteral (intravenous) treatment, currently available for `r sum(!is.na(antibiotics$iv_ddd))` drugs
|
||||
#' - `iv_units`\cr Units of `iv_ddd`
|
||||
#' - `loinc`\cr All LOINC codes (Logical Observation Identifiers Names and Codes) associated with the name of the antimicrobial agent. Use [ab_loinc()] to retrieve them quickly, see [ab_property()].
|
||||
#'
|
||||
#' ## For the [antivirals] data set: a [data.frame] with `r nrow(antivirals)` observations and `r ncol(antivirals)` variables:
|
||||
#' - `atc`\cr ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC
|
||||
#' - `cid`\cr Compound ID as found in PubChem
|
||||
#' - `name`\cr Official name as used by WHONET/EARS-Net or the WHO
|
||||
#' - `atc_group`\cr Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC
|
||||
#' - `synonyms`\cr Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID
|
||||
#' - `oral_ddd`\cr Defined Daily Dose (DDD), oral treatment
|
||||
#' - `oral_units`\cr Units of `oral_ddd`
|
||||
#' - `iv_ddd`\cr Defined Daily Dose (DDD), parenteral treatment
|
||||
#' - `iv_units`\cr Units of `iv_ddd`
|
||||
#' @details Properties that are based on an ATC code are only available when an ATC is available. These properties are: `atc_group1`, `atc_group2`, `oral_ddd`, `oral_units`, `iv_ddd` and `iv_units`.
|
||||
#'
|
||||
#' Synonyms (i.e. trade names) were derived from the Compound ID (`cid`) and consequently only available where a CID is available.
|
||||
#'
|
||||
#' ## Direct download
|
||||
#' These data sets are available as 'flat files' for use even without \R - you can find the files here:
|
||||
#'
|
||||
#' * <https://github.com/msberends/AMR/raw/main/data-raw/antibiotics.txt>
|
||||
#' * <https://github.com/msberends/AMR/raw/main/data-raw/antivirals.txt>
|
||||
#'
|
||||
#' Files in \R format (with preserved data structure) can be found here:
|
||||
#'
|
||||
#' * <https://github.com/msberends/AMR/raw/main/data/antibiotics.rda>
|
||||
#' * <https://github.com/msberends/AMR/raw/main/data/antivirals.rda>
|
||||
#' @source World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): <https://www.whocc.no/atc_ddd_index/>
|
||||
#'
|
||||
#' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm>
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @inheritSection WHOCC WHOCC
|
||||
#' @seealso [microorganisms], [intrinsic_resistant]
|
||||
#' @examples
|
||||
#' head(antibiotics)
|
||||
#' head(antivirals)
|
||||
"antibiotics"
|
||||
|
||||
#' @rdname antibiotics
|
||||
"antivirals"
|
||||
|
||||
#' Data Set with `r format(nrow(microorganisms), big.mark = ",")` Microorganisms
|
||||
#'
|
||||
#' A data set containing the full microbial taxonomy (**last updated: `r CATALOGUE_OF_LIFE$yearmonth_LPSN`**) of `r nr2char(length(unique(microorganisms$kingdom[!microorganisms$kingdom %like% "unknown"])))` kingdoms from the Catalogue of Life (CoL) and the List of Prokaryotic names with Standing in Nomenclature (LPSN). MO codes can be looked up using [as.mo()].
|
||||
#' @inheritSection catalogue_of_life Catalogue of Life
|
||||
#' @format A [data.frame] with `r format(nrow(microorganisms), big.mark = ",")` observations and `r ncol(microorganisms)` variables:
|
||||
#' - `mo`\cr ID of microorganism as used by this package
|
||||
#' - `fullname`\cr Full name, like `"Escherichia coli"`
|
||||
#' - `kingdom`, `phylum`, `class`, `order`, `family`, `genus`, `species`, `subspecies`\cr Taxonomic rank of the microorganism
|
||||
#' - `rank`\cr Text of the taxonomic rank of the microorganism, like `"species"` or `"genus"`
|
||||
#' - `ref`\cr Author(s) and year of concerning scientific publication
|
||||
#' - `species_id`\cr ID of the species as used by the Catalogue of Life
|
||||
#' - `source`\cr Either `r vector_or(microorganisms$source)` (see *Source*)
|
||||
#' - `prevalence`\cr Prevalence of the microorganism, see [as.mo()]
|
||||
#' - `snomed`\cr Systematized Nomenclature of Medicine (SNOMED) code of the microorganism, according to the `r SNOMED_VERSION$current_source` (see *Source*). Use [mo_snomed()] to retrieve it quickly, see [mo_property()].
|
||||
#' @details
|
||||
#' Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.
|
||||
#'
|
||||
#' For example, *Staphylococcus pettenkoferi* was described for the first time in Diagnostic Microbiology and Infectious Disease in 2002 (\doi{10.1016/s0732-8893(02)00399-1}), but it was not before 2007 that a publication in IJSEM followed (\doi{10.1099/ijs.0.64381-0}). Consequently, the `AMR` package returns 2007 for `mo_year("S. pettenkoferi")`.
|
||||
#'
|
||||
#' ## Manual additions
|
||||
#' For convenience, some entries were added manually:
|
||||
#'
|
||||
#' - 11 entries of *Streptococcus* (beta-haemolytic: groups A, B, C, D, F, G, H, K and unspecified; other: viridans, milleri)
|
||||
#' - 2 entries of *Staphylococcus* (coagulase-negative (CoNS) and coagulase-positive (CoPS))
|
||||
#' - 3 entries of *Trichomonas* (*T. vaginalis*, and its family and genus)
|
||||
#' - 4 entries of *Toxoplasma* (*T. gondii*, and its order, family and genus)
|
||||
#' - 1 entry of *Candida* (*C. krusei*), that is not (yet) in the Catalogue of Life
|
||||
#' - 1 entry of *Blastocystis* (*B. hominis*), although it officially does not exist (Noel *et al.* 2005, PMID 15634993)
|
||||
#' - 1 entry of *Moraxella* (*M. catarrhalis*), which was formally named *Branhamella catarrhalis* (Catlin, 1970) though this change was never accepted within the field of clinical microbiology
|
||||
#' - 5 other 'undefined' entries (unknown, unknown Gram negatives, unknown Gram positives, unknown yeast and unknown fungus)
|
||||
#' - 6 families under the Enterobacterales order, according to Adeolu *et al.* (2016, PMID 27620848), that are not (yet) in the Catalogue of Life
|
||||
#'
|
||||
#' ## Direct download
|
||||
#' This data set is available as 'flat file' for use even without \R - you can find the file here: <https://github.com/msberends/AMR/raw/main/data-raw/microorganisms.txt>.
|
||||
#'
|
||||
#' The file in \R format (with preserved data structure) can be found here: <https://github.com/msberends/AMR/raw/main/data/microorganisms.rda>.
|
||||
#'
|
||||
#' @section About the Records from LPSN (see *Source*):
|
||||
#' The List of Prokaryotic names with Standing in Nomenclature (LPSN) provides comprehensive information on the nomenclature of prokaryotes. LPSN is a free to use service founded by Jean P. Euzeby in 1997 and later on maintained by Aidan C. Parte.
|
||||
#'
|
||||
#' As of February 2020, the regularly augmented LPSN database at DSMZ is the basis of the new LPSN service. The new database was implemented for the Type-Strain Genome Server and augmented in 2018 to store all kinds of nomenclatural information. Data from the previous version of LPSN and from the Prokaryotic Nomenclature Up-to-date (PNU) service were imported into the new system. PNU had been established in 1993 as a service of the Leibniz Institute DSMZ, and was curated by Norbert Weiss, Manfred Kracht and Dorothea Gleim.
|
||||
#' @source
|
||||
#' `r gsub("{year}", CATALOGUE_OF_LIFE$year, CATALOGUE_OF_LIFE$version, fixed = TRUE)` as currently implemented in this `AMR` package:
|
||||
#'
|
||||
#' * Annual Checklist (public online taxonomic database), <http://www.catalogueoflife.org>
|
||||
#'
|
||||
#' List of Prokaryotic names with Standing in Nomenclature (`r CATALOGUE_OF_LIFE$yearmonth_LPSN`) as currently implemented in this `AMR` package:
|
||||
#'
|
||||
#' * Parte, A.C., Sarda Carbasse, J., Meier-Kolthoff, J.P., Reimer, L.C. and Goker, M. (2020). List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ. International Journal of Systematic and Evolutionary Microbiology, 70, 5607-5612; \doi{10.1099/ijsem.0.004332}
|
||||
#' * Parte, A.C. (2018). LPSN - List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on. International Journal of Systematic and Evolutionary Microbiology, 68, 1825-1829; \doi{10.1099/ijsem.0.002786}
|
||||
#' * Parte, A.C. (2014). LPSN - List of Prokaryotic names with Standing in Nomenclature. Nucleic Acids Research, 42, Issue D1, D613-D616; \doi{10.1093/nar/gkt1111}
|
||||
#' * Euzeby, J.P. (1997). List of Bacterial Names with Standing in Nomenclature: a Folder Available on the Internet. International Journal of Systematic Bacteriology, 47, 590-592; \doi{10.1099/00207713-47-2-590}
|
||||
#'
|
||||
#' `r SNOMED_VERSION$current_source` as currently implemented in this `AMR` package:
|
||||
#'
|
||||
#' * Retrieved from the `r SNOMED_VERSION$title`, OID `r SNOMED_VERSION$current_oid`, version `r SNOMED_VERSION$current_version`; url: <`r SNOMED_VERSION$url`>
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @seealso [as.mo()], [mo_property()], [microorganisms.codes], [intrinsic_resistant]
|
||||
#' @examples
|
||||
#' head(microorganisms)
|
||||
"microorganisms"
|
||||
|
||||
#' Data Set with Previously Accepted Taxonomic Names
|
||||
#'
|
||||
#' A data set containing old (previously valid or accepted) taxonomic names according to the Catalogue of Life. This data set is used internally by [as.mo()].
|
||||
#' @inheritSection catalogue_of_life Catalogue of Life
|
||||
#' @format A [data.frame] with `r format(nrow(microorganisms.old), big.mark = ",")` observations and `r ncol(microorganisms.old)` variables:
|
||||
#' - `fullname`\cr Old full taxonomic name of the microorganism
|
||||
#' - `fullname_new`\cr New full taxonomic name of the microorganism
|
||||
#' - `ref`\cr Author(s) and year of concerning scientific publication
|
||||
#' - `prevalence`\cr Prevalence of the microorganism, see [as.mo()]
|
||||
#' @source Catalogue of Life: Annual Checklist (public online taxonomic database), <http://www.catalogueoflife.org> (check included annual version with [catalogue_of_life_version()]).
|
||||
#'
|
||||
#' Parte, A.C. (2018). LPSN - List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on. International Journal of Systematic and Evolutionary Microbiology, 68, 1825-1829; \doi{10.1099/ijsem.0.002786}
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @seealso [as.mo()] [mo_property()] [microorganisms]
|
||||
#' @examples
|
||||
#' head(microorganisms.old)
|
||||
"microorganisms.old"
|
||||
|
||||
#' Data Set with `r format(nrow(microorganisms.codes), big.mark = ",")` Common Microorganism Codes
|
||||
#'
|
||||
#' A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with [set_mo_source()]. They will all be searched when using [as.mo()] and consequently all the [`mo_*`][mo_property()] functions.
|
||||
#' @format A [data.frame] with `r format(nrow(microorganisms.codes), big.mark = ",")` observations and `r ncol(microorganisms.codes)` variables:
|
||||
#' - `code`\cr Commonly used code of a microorganism
|
||||
#' - `mo`\cr ID of the microorganism in the [microorganisms] data set
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @inheritSection catalogue_of_life Catalogue of Life
|
||||
#' @seealso [as.mo()] [microorganisms]
|
||||
#' @examples
|
||||
#' head(microorganisms.codes)
|
||||
"microorganisms.codes"
|
||||
|
||||
#' Data Set with `r format(nrow(example_isolates), big.mark = ",")` Example Isolates
|
||||
#'
|
||||
#' A data set containing `r format(nrow(example_isolates), big.mark = ",")` microbial isolates with their full antibiograms. The data set reflects reality and can be used to practice AMR data analysis. For examples, please read [the tutorial on our website](https://msberends.github.io/AMR/articles/AMR.html).
|
||||
#' @format A [data.frame] with `r format(nrow(example_isolates), big.mark = ",")` observations and `r ncol(example_isolates)` variables:
|
||||
#' - `date`\cr date of receipt at the laboratory
|
||||
#' - `hospital_id`\cr ID of the hospital, from A to D
|
||||
#' - `ward_icu`\cr [logical] to determine if ward is an intensive care unit
|
||||
#' - `ward_clinical`\cr [logical] to determine if ward is a regular clinical ward
|
||||
#' - `ward_outpatient`\cr [logical] to determine if ward is an outpatient clinic
|
||||
#' - `age`\cr age of the patient
|
||||
#' - `gender`\cr gender of the patient
|
||||
#' - `patient_id`\cr ID of the patient
|
||||
#' - `mo`\cr ID of microorganism created with [as.mo()], see also [microorganisms]
|
||||
#' - `PEN:RIF`\cr `r sum(vapply(FUN.VALUE = logical(1), example_isolates, is.rsi))` different antibiotics with class [`rsi`] (see [as.rsi()]); these column names occur in the [antibiotics] data set and can be translated with [ab_name()]
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @examples
|
||||
#' head(example_isolates)
|
||||
"example_isolates"
|
||||
|
||||
#' Data Set with Unclean Data
|
||||
#'
|
||||
#' A data set containing `r format(nrow(example_isolates_unclean), big.mark = ",")` microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice.
|
||||
#' @format A [data.frame] with `r format(nrow(example_isolates_unclean), big.mark = ",")` observations and `r ncol(example_isolates_unclean)` variables:
|
||||
#' - `patient_id`\cr ID of the patient
|
||||
#' - `date`\cr date of receipt at the laboratory
|
||||
#' - `hospital`\cr ID of the hospital, from A to C
|
||||
#' - `bacteria`\cr info about microorganism that can be transformed with [as.mo()], see also [microorganisms]
|
||||
#' - `AMX:GEN`\cr 4 different antibiotics that have to be transformed with [as.rsi()]
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @examples
|
||||
#' head(example_isolates_unclean)
|
||||
"example_isolates_unclean"
|
||||
|
||||
#' Data Set with `r format(nrow(WHONET), big.mark = ",")` Isolates - WHONET Example
|
||||
#'
|
||||
#' This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The antibiotic results are from our [example_isolates] data set. All patient names are created using online surname generators and are only in place for practice purposes.
|
||||
#' @format A [data.frame] with `r format(nrow(WHONET), big.mark = ",")` observations and `r ncol(WHONET)` variables:
|
||||
#' - `Identification number`\cr ID of the sample
|
||||
#' - `Specimen number`\cr ID of the specimen
|
||||
#' - `Organism`\cr Name of the microorganism. Before analysis, you should transform this to a valid microbial class, using [as.mo()].
|
||||
#' - `Country`\cr Country of origin
|
||||
#' - `Laboratory`\cr Name of laboratory
|
||||
#' - `Last name`\cr Fictitious last name of patient
|
||||
#' - `First name`\cr Fictitious initial of patient
|
||||
#' - `Sex`\cr Fictitious gender of patient
|
||||
#' - `Age`\cr Fictitious age of patient
|
||||
#' - `Age category`\cr Age group, can also be looked up using [age_groups()]
|
||||
#' - `Date of admission`\cr [Date] of hospital admission
|
||||
#' - `Specimen date`\cr [Date] when specimen was received at laboratory
|
||||
#' - `Specimen type`\cr Specimen type or group
|
||||
#' - `Specimen type (Numeric)`\cr Translation of `"Specimen type"`
|
||||
#' - `Reason`\cr Reason of request with Differential Diagnosis
|
||||
#' - `Isolate number`\cr ID of isolate
|
||||
#' - `Organism type`\cr Type of microorganism, can also be looked up using [mo_type()]
|
||||
#' - `Serotype`\cr Serotype of microorganism
|
||||
#' - `Beta-lactamase`\cr Microorganism produces beta-lactamase?
|
||||
#' - `ESBL`\cr Microorganism produces extended spectrum beta-lactamase?
|
||||
#' - `Carbapenemase`\cr Microorganism produces carbapenemase?
|
||||
#' - `MRSA screening test`\cr Microorganism is possible MRSA?
|
||||
#' - `Inducible clindamycin resistance`\cr Clindamycin can be induced?
|
||||
#' - `Comment`\cr Other comments
|
||||
#' - `Date of data entry`\cr [Date] this data was entered in WHONET
|
||||
#' - `AMP_ND10:CIP_EE`\cr `r sum(vapply(FUN.VALUE = logical(1), WHONET, is.rsi))` different antibiotics. You can lookup the abbreviations in the [antibiotics] data set, or use e.g. [`ab_name("AMP")`][ab_name()] to get the official name immediately. Before analysis, you should transform this to a valid antibiotic class, using [as.rsi()].
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @examples
|
||||
#' head(WHONET)
|
||||
"WHONET"
|
||||
|
||||
#' Data Set for R/SI Interpretation
|
||||
#'
|
||||
#' Data set containing reference data to interpret MIC and disk diffusion to R/SI values, according to international guidelines. Currently implemented guidelines are EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`). Use [as.rsi()] to transform MICs or disks measurements to R/SI values.
|
||||
#' @format A [data.frame] with `r format(nrow(rsi_translation), big.mark = ",")` observations and `r ncol(rsi_translation)` variables:
|
||||
#' - `guideline`\cr Name of the guideline
|
||||
#' - `method`\cr Either `r vector_or(rsi_translation$method)`
|
||||
#' - `site`\cr Body site, e.g. "Oral" or "Respiratory"
|
||||
#' - `mo`\cr Microbial ID, see [as.mo()]
|
||||
#' - `rank_index`\cr Taxonomic rank index of `mo` from 1 (subspecies/infraspecies) to 5 (unknown microorganism)
|
||||
#' - `ab`\cr Antibiotic ID, see [as.ab()]
|
||||
#' - `ref_tbl`\cr Info about where the guideline rule can be found
|
||||
#' - `disk_dose`\cr Dose of the used disk diffusion method
|
||||
#' - `breakpoint_S`\cr Lowest MIC value or highest number of millimetres that leads to "S"
|
||||
#' - `breakpoint_R`\cr Highest MIC value or lowest number of millimetres that leads to "R"
|
||||
#' - `uti`\cr A [logical] value (`TRUE`/`FALSE`) to indicate whether the rule applies to a urinary tract infection (UTI)
|
||||
#' @details
|
||||
#' The repository of this `AMR` package contains a file comprising this exact data set: <https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt>. This file **allows for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically and the `mo` and `ab` columns have been transformed to contain the full official names instead of codes.
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @seealso [intrinsic_resistant]
|
||||
#' @examples
|
||||
#' head(rsi_translation)
|
||||
"rsi_translation"
|
||||
|
||||
#' Data Set with Bacterial Intrinsic Resistance
|
||||
#'
|
||||
#' Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations.
|
||||
#' @format A [data.frame] with `r format(nrow(intrinsic_resistant), big.mark = ",")` observations and `r ncol(intrinsic_resistant)` variables:
|
||||
#' - `mo`\cr Microorganism ID
|
||||
#' - `ab`\cr Antibiotic ID
|
||||
#' @details The repository of this `AMR` package contains a file comprising this data set with full taxonomic and antibiotic names: <https://github.com/msberends/AMR/blob/main/data-raw/intrinsic_resistant.txt>. This file **allows for machine reading EUCAST guidelines about intrinsic resistance**, which is almost impossible with the Excel and PDF files distributed by EUCAST. The file is updated automatically.
|
||||
#'
|
||||
#' This data set is based on `r format_eucast_version_nr(3.3)`.
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @examples
|
||||
#' head(intrinsic_resistant)
|
||||
"intrinsic_resistant"
|
||||
|
||||
#' Data Set with Treatment Dosages as Defined by EUCAST
|
||||
#'
|
||||
#' EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with [eucast_dosage()].
|
||||
#' @format A [data.frame] with `r format(nrow(dosage), big.mark = ",")` observations and `r ncol(dosage)` variables:
|
||||
#' - `ab`\cr Antibiotic ID as used in this package (such as `AMC`), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
|
||||
#' - `name`\cr Official name of the antimicrobial agent as used by WHONET/EARS-Net or the WHO
|
||||
#' - `type`\cr Type of the dosage, either `r vector_or(dosage$type)`
|
||||
#' - `dose`\cr Dose, such as "2 g" or "25 mg/kg"
|
||||
#' - `dose_times`\cr Number of times a dose must be administered
|
||||
#' - `administration`\cr Route of administration, either `r vector_or(dosage$administration)`
|
||||
#' - `notes`\cr Additional dosage notes
|
||||
#' - `original_txt`\cr Original text in the PDF file of EUCAST
|
||||
#' - `eucast_version`\cr Version number of the EUCAST Clinical Breakpoints guideline to which these dosages apply
|
||||
#' @details `r format_eucast_version_nr(11.0)` are based on the dosages in this data set.
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @examples
|
||||
#' head(dosage)
|
||||
"dosage"
|
||||
@@ -1,32 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Deprecated Functions
|
||||
#'
|
||||
#' These functions are so-called '[Deprecated]'. **They will be removed in a future release.** Using the functions will give a warning with the name of the function it has been replaced by (if there is one).
|
||||
#' @keywords internal
|
||||
#' @name AMR-deprecated
|
||||
# @export
|
||||
NULL
|
||||
@@ -1,227 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Transform Input to Disk Diffusion Diameters
|
||||
#'
|
||||
#' This transforms a vector to a new class [`disk`], which is a disk diffusion growth zone size (around an antibiotic disk) in millimetres between 6 and 50.
|
||||
#' @rdname as.disk
|
||||
#' @param x vector
|
||||
#' @param na.rm a [logical] indicating whether missing values should be removed
|
||||
#' @details Interpret disk values as RSI values with [as.rsi()]. It supports guidelines from EUCAST and CLSI.
|
||||
#' @return An [integer] with additional class [`disk`]
|
||||
#' @aliases disk
|
||||
#' @export
|
||||
#' @seealso [as.rsi()]
|
||||
#' @examples
|
||||
#' # transform existing disk zones to the `disk` class (using base R)
|
||||
#' df <- data.frame(microorganism = "Escherichia coli",
|
||||
#' AMP = 20,
|
||||
#' CIP = 14,
|
||||
#' GEN = 18,
|
||||
#' TOB = 16)
|
||||
#' df[, 2:5] <- lapply(df[, 2:5], as.disk)
|
||||
#' str(df)
|
||||
#'
|
||||
#' \donttest{
|
||||
#' # transforming is easier with dplyr:
|
||||
#' if (require("dplyr")) {
|
||||
#' df %>% mutate(across(AMP:TOB, as.disk))
|
||||
#' }
|
||||
#' }
|
||||
#'
|
||||
#' # interpret disk values, see ?as.rsi
|
||||
#' as.rsi(x = as.disk(18),
|
||||
#' mo = "Strep pneu", # `mo` will be coerced with as.mo()
|
||||
#' ab = "ampicillin", # and `ab` with as.ab()
|
||||
#' guideline = "EUCAST")
|
||||
#'
|
||||
#' # interpret whole data set, pretend to be all from urinary tract infections:
|
||||
#' as.rsi(df, uti = TRUE)
|
||||
as.disk <- function(x, na.rm = FALSE) {
|
||||
meet_criteria(x, allow_class = c("disk", "character", "numeric", "integer"), allow_NA = TRUE)
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
|
||||
if (!is.disk(x)) {
|
||||
x <- unlist(x)
|
||||
if (na.rm == TRUE) {
|
||||
x <- x[!is.na(x)]
|
||||
}
|
||||
x[trimws(x) == ""] <- NA
|
||||
x.bak <- x
|
||||
|
||||
na_before <- length(x[is.na(x)])
|
||||
|
||||
# heavily based on cleaner::clean_double():
|
||||
clean_double2 <- function(x, remove = "[^0-9.,-]", fixed = FALSE) {
|
||||
x <- gsub(",", ".", x)
|
||||
# remove ending dot/comma
|
||||
x <- gsub("[,.]$", "", x)
|
||||
# only keep last dot/comma
|
||||
reverse <- function(x) vapply(FUN.VALUE = character(1), lapply(strsplit(x, NULL), rev), paste, collapse = "")
|
||||
x <- sub("{{dot}}", ".",
|
||||
gsub(".", "",
|
||||
reverse(sub(".", "}}tod{{",
|
||||
reverse(x),
|
||||
fixed = TRUE)),
|
||||
fixed = TRUE),
|
||||
fixed = TRUE)
|
||||
x_clean <- gsub(remove, "", x, ignore.case = TRUE, fixed = fixed)
|
||||
# remove everything that is not a number or dot
|
||||
as.double(gsub("[^0-9.]+", "", x_clean))
|
||||
}
|
||||
|
||||
# round up and make it an integer
|
||||
x <- as.integer(ceiling(clean_double2(x)))
|
||||
|
||||
# disks can never be less than 6 mm (size of smallest disk) or more than 50 mm
|
||||
x[x < 6 | x > 50] <- NA_integer_
|
||||
na_after <- length(x[is.na(x)])
|
||||
|
||||
if (na_before != na_after) {
|
||||
list_missing <- x.bak[is.na(x) & !is.na(x.bak)] %pm>%
|
||||
unique() %pm>%
|
||||
sort() %pm>%
|
||||
vector_and(quotes = TRUE)
|
||||
warning_("in `as.disk()`: ", na_after - na_before, " results truncated (",
|
||||
round(((na_after - na_before) / length(x)) * 100),
|
||||
"%) that were invalid disk zones: ",
|
||||
list_missing)
|
||||
}
|
||||
}
|
||||
set_clean_class(as.integer(x),
|
||||
new_class = c("disk", "integer"))
|
||||
}
|
||||
|
||||
all_valid_disks <- function(x) {
|
||||
if (!inherits(x, c("disk", "character", "numeric", "integer"))) {
|
||||
return(FALSE)
|
||||
}
|
||||
x_disk <- tryCatch(suppressWarnings(as.disk(x[!is.na(x)])),
|
||||
error = function(e) NA)
|
||||
!any(is.na(x_disk)) && !all(is.na(x))
|
||||
}
|
||||
|
||||
#' @rdname as.disk
|
||||
#' @details `NA_disk_` is a missing value of the new `<disk>` class.
|
||||
#' @export
|
||||
NA_disk_ <- set_clean_class(as.integer(NA_real_),
|
||||
new_class = c("disk", "integer"))
|
||||
|
||||
#' @rdname as.disk
|
||||
#' @export
|
||||
is.disk <- function(x) {
|
||||
inherits(x, "disk")
|
||||
}
|
||||
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
pillar_shaft.disk <- function(x, ...) {
|
||||
out <- trimws(format(x))
|
||||
out[is.na(x)] <- font_na(NA)
|
||||
create_pillar_column(out, align = "right", width = 2)
|
||||
}
|
||||
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
type_sum.disk <- function(x, ...) {
|
||||
"disk"
|
||||
}
|
||||
|
||||
#' @method print disk
|
||||
#' @export
|
||||
#' @noRd
|
||||
print.disk <- function(x, ...) {
|
||||
cat("Class <disk>\n")
|
||||
print(as.integer(x), quote = FALSE)
|
||||
}
|
||||
|
||||
#' @method [ disk
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[.disk" <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
#' @method [[ disk
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[[.disk" <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
#' @method [<- disk
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[<-.disk" <- function(i, j, ..., value) {
|
||||
value <- as.disk(value)
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(i)
|
||||
y
|
||||
}
|
||||
#' @method [[<- disk
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[[<-.disk" <- function(i, j, ..., value) {
|
||||
value <- as.disk(value)
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(i)
|
||||
y
|
||||
}
|
||||
#' @method c disk
|
||||
#' @export
|
||||
#' @noRd
|
||||
c.disk <- function(...) {
|
||||
as.disk(unlist(lapply(list(...), as.character)))
|
||||
}
|
||||
|
||||
#' @method unique disk
|
||||
#' @export
|
||||
#' @noRd
|
||||
unique.disk <- function(x, incomparables = FALSE, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
|
||||
#' @method rep disk
|
||||
#' @export
|
||||
#' @noRd
|
||||
rep.disk <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
get_skimmers.disk <- function(column) {
|
||||
skimr::sfl(
|
||||
skim_type = "disk",
|
||||
min = ~min(as.double(.), na.rm = TRUE),
|
||||
max = ~max(as.double(.), na.rm = TRUE),
|
||||
median = ~stats::median(as.double(.), na.rm = TRUE),
|
||||
n_unique = ~length(unique(stats::na.omit(.))),
|
||||
hist = ~skimr::inline_hist(stats::na.omit(as.double(.)))
|
||||
)
|
||||
}
|
||||
-189
@@ -1,189 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Determine (New) Episodes for Patients
|
||||
#'
|
||||
#' These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument `episode_days`. This can be used to determine clinical episodes for any epidemiological analysis. The [get_episode()] function returns the index number of the episode per group, while the [is_new_episode()] function returns values `TRUE`/`FALSE` to indicate whether an item in a vector is the start of a new episode.
|
||||
#' @param x vector of dates (class `Date` or `POSIXt`), will be sorted internally to determine episodes
|
||||
#' @param episode_days required episode length in days, can also be less than a day or `Inf`, see *Details*
|
||||
#' @param ... ignored, only in place to allow future extensions
|
||||
#' @details
|
||||
#' Dates are first sorted from old to new. The oldest date will mark the start of the first episode. After this date, the next date will be marked that is at least `episode_days` days later than the start of the first episode. From that second marked date on, the next date will be marked that is at least `episode_days` days later than the start of the second episode which will be the start of the third episode, and so on. Before the vector is being returned, the original order will be restored.
|
||||
#'
|
||||
#' The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but is more efficient for data sets containing microorganism codes or names and allows for different isolate selection methods.
|
||||
#'
|
||||
#' The `dplyr` package is not required for these functions to work, but these functions do support [variable grouping][dplyr::group_by()] and work conveniently inside `dplyr` verbs such as [`filter()`][dplyr::filter()], [`mutate()`][dplyr::mutate()] and [`summarise()`][dplyr::summarise()].
|
||||
#' @return
|
||||
#' * [get_episode()]: a [double] vector
|
||||
#' * [is_new_episode()]: a [logical] vector
|
||||
#' @seealso [first_isolate()]
|
||||
#' @rdname get_episode
|
||||
#' @export
|
||||
#' @examples
|
||||
#' # `example_isolates` is a data set available in the AMR package.
|
||||
#' # See ?example_isolates
|
||||
#' df <- example_isolates[sample(seq_len(2000), size = 200), ]
|
||||
#'
|
||||
#' get_episode(df$date, episode_days = 60) # indices
|
||||
#' is_new_episode(df$date, episode_days = 60) # TRUE/FALSE
|
||||
#'
|
||||
#' # filter on results from the third 60-day episode only, using base R
|
||||
#' df[which(get_episode(df$date, 60) == 3), ]
|
||||
#'
|
||||
#' # the functions also work for less than a day, e.g. to include one per hour:
|
||||
#' get_episode(c(Sys.time(),
|
||||
#' Sys.time() + 60 * 60),
|
||||
#' episode_days = 1/24)
|
||||
#'
|
||||
#' \donttest{
|
||||
#' if (require("dplyr")) {
|
||||
#' # is_new_episode() can also be used in dplyr verbs to determine patient
|
||||
#' # episodes based on any (combination of) grouping variables:
|
||||
#' df %>%
|
||||
#' mutate(condition = sample(x = c("A", "B", "C"),
|
||||
#' size = 2000,
|
||||
#' replace = TRUE)) %>%
|
||||
#' group_by(condition) %>%
|
||||
#' mutate(new_episode = is_new_episode(date, 365)) %>%
|
||||
#' select(patient_id, date, condition, new_episode)
|
||||
#'
|
||||
#' df %>%
|
||||
#' group_by(hospital_id, patient_id) %>%
|
||||
#' transmute(date,
|
||||
#' patient_id,
|
||||
#' new_index = get_episode(date, 60),
|
||||
#' new_logical = is_new_episode(date, 60))
|
||||
#'
|
||||
#' df %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(n_patients = n_distinct(patient_id),
|
||||
#' n_episodes_365 = sum(is_new_episode(date, episode_days = 365)),
|
||||
#' n_episodes_60 = sum(is_new_episode(date, episode_days = 60)),
|
||||
#' n_episodes_30 = sum(is_new_episode(date, episode_days = 30)))
|
||||
#'
|
||||
#'
|
||||
#' # grouping on patients and microorganisms leads to the same
|
||||
#' # results as first_isolate() when using 'episode-based':
|
||||
#' x <- df %>%
|
||||
#' filter_first_isolate(include_unknown = TRUE,
|
||||
#' method = "episode-based")
|
||||
#'
|
||||
#' y <- df %>%
|
||||
#' group_by(patient_id, mo) %>%
|
||||
#' filter(is_new_episode(date, 365)) %>%
|
||||
#' ungroup()
|
||||
#'
|
||||
#' identical(x, y)
|
||||
#'
|
||||
#' # but is_new_episode() has a lot more flexibility than first_isolate(),
|
||||
#' # since you can now group on anything that seems relevant:
|
||||
#' df %>%
|
||||
#' group_by(patient_id, mo, hospital_id, ward_icu) %>%
|
||||
#' mutate(flag_episode = is_new_episode(date, 365)) %>%
|
||||
#' select(group_vars(.), flag_episode)
|
||||
#' }
|
||||
#' }
|
||||
get_episode <- function(x, episode_days, ...) {
|
||||
meet_criteria(x, allow_class = c("Date", "POSIXt"), allow_NA = TRUE)
|
||||
meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
|
||||
|
||||
exec_episode(x = x,
|
||||
type = "sequential",
|
||||
episode_days = episode_days,
|
||||
... = ...)
|
||||
}
|
||||
|
||||
#' @rdname get_episode
|
||||
#' @export
|
||||
is_new_episode <- function(x, episode_days, ...) {
|
||||
meet_criteria(x, allow_class = c("Date", "POSIXt"), allow_NA = TRUE)
|
||||
meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
|
||||
|
||||
exec_episode(x = x,
|
||||
type = "logical",
|
||||
episode_days = episode_days,
|
||||
... = ...)
|
||||
}
|
||||
|
||||
exec_episode <- function(x, type, episode_days, ...) {
|
||||
x <- as.double(as.POSIXct(x)) # as.POSIXct() required for Date classes
|
||||
# since x is now in seconds, get seconds from episode_days as well
|
||||
episode_seconds <- episode_days * 60 * 60 * 24
|
||||
|
||||
if (length(x) == 1) { # this will also match 1 NA, which is fine
|
||||
if (type == "logical") {
|
||||
return(TRUE)
|
||||
} else if (type == "sequential") {
|
||||
return(1)
|
||||
}
|
||||
} else if (length(x) == 2 && !all(is.na(x))) {
|
||||
if (max(x) - min(x) >= episode_seconds) {
|
||||
if (type == "logical") {
|
||||
return(c(TRUE, TRUE))
|
||||
} else if (type == "sequential") {
|
||||
return(c(1, 2))
|
||||
}
|
||||
} else {
|
||||
if (type == "logical") {
|
||||
return(c(TRUE, FALSE))
|
||||
} else if (type == "sequential") {
|
||||
return(c(1, 1))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
# I asked on StackOverflow:
|
||||
# https://stackoverflow.com/questions/42122245/filter-one-row-every-year
|
||||
run_episodes <- function(x, episode_seconds) {
|
||||
indices <- integer()
|
||||
start <- x[1]
|
||||
ind <- 1
|
||||
indices[1] <- 1
|
||||
for (i in 2:length(x)) {
|
||||
if (isTRUE((x[i] - start) >= episode_seconds)) {
|
||||
ind <- ind + 1
|
||||
if (type == "logical") {
|
||||
indices[ind] <- i
|
||||
}
|
||||
start <- x[i]
|
||||
}
|
||||
if (type == "sequential") {
|
||||
indices[i] <- ind
|
||||
}
|
||||
}
|
||||
if (type == "logical") {
|
||||
result <- rep(FALSE, length(x))
|
||||
result[indices] <- TRUE
|
||||
result
|
||||
} else if (type == "sequential") {
|
||||
indices
|
||||
}
|
||||
}
|
||||
|
||||
ord <- order(x)
|
||||
out <- run_episodes(x[ord], episode_seconds)[order(ord)]
|
||||
out[is.na(x) & ord != 1] <- NA # every NA but the first must remain NA
|
||||
out
|
||||
}
|
||||
-1074
File diff suppressed because it is too large
Load Diff
@@ -1,646 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Determine First Isolates
|
||||
#'
|
||||
#' Determine first isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler *et al.* in 2007 (\doi{10.1086/511864}). To determine patient episodes not necessarily based on microorganisms, use [is_new_episode()] that also supports grouping with the `dplyr` package.
|
||||
#' @param x a [data.frame] containing isolates. Can be left blank for automatic determination, see *Examples*.
|
||||
#' @param col_date column name of the result date (or date that is was received on the lab), defaults to the first column with a date class
|
||||
#' @param col_patient_id column name of the unique IDs of the patients, defaults to the first column that starts with 'patient' or 'patid' (case insensitive)
|
||||
#' @param col_mo column name of the IDs of the microorganisms (see [as.mo()]), defaults to the first column of class [`mo`]. Values will be coerced using [as.mo()].
|
||||
#' @param col_testcode column name of the test codes. Use `col_testcode = NULL` to **not** exclude certain test codes (such as test codes for screening). In that case `testcodes_exclude` will be ignored.
|
||||
#' @param col_specimen column name of the specimen type or group
|
||||
#' @param col_icu column name of the logicals (`TRUE`/`FALSE`) whether a ward or department is an Intensive Care Unit (ICU)
|
||||
#' @param col_keyantimicrobials (only useful when `method = "phenotype-based"`) column name of the key antimicrobials to determine first isolates, see [key_antimicrobials()]. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use `col_keyantimicrobials = FALSE` to prevent this. Can also be the output of [key_antimicrobials()].
|
||||
#' @param episode_days episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see *Source*.
|
||||
#' @param testcodes_exclude a [character] vector with test codes that should be excluded (case-insensitive)
|
||||
#' @param icu_exclude a [logical] to indicate whether ICU isolates should be excluded (rows with value `TRUE` in the column set with `col_icu`)
|
||||
#' @param specimen_group value in the column set with `col_specimen` to filter on
|
||||
#' @param type type to determine weighed isolates; can be `"keyantimicrobials"` or `"points"`, see *Details*
|
||||
#' @param method the method to apply, either `"phenotype-based"`, `"episode-based"`, `"patient-based"` or `"isolate-based"` (can be abbreviated), see *Details*. The default is `"phenotype-based"` if antimicrobial test results are present in the data, and `"episode-based"` otherwise.
|
||||
#' @param ignore_I [logical] to indicate whether antibiotic interpretations with `"I"` will be ignored when `type = "keyantimicrobials"`, see *Details*
|
||||
#' @param points_threshold minimum number of points to require before differences in the antibiogram will lead to inclusion of an isolate when `type = "points"`, see *Details*
|
||||
#' @param info a [logical] to indicate info should be printed, defaults to `TRUE` only in interactive mode
|
||||
#' @param include_unknown a [logical] to indicate whether 'unknown' microorganisms should be included too, i.e. microbial code `"UNKNOWN"`, which defaults to `FALSE`. For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default. Isolates with a microbial ID of `NA` will always be excluded as first isolate.
|
||||
#' @param include_untested_rsi a [logical] to indicate whether also rows without antibiotic results are still eligible for becoming a first isolate. Use `include_untested_rsi = FALSE` to always return `FALSE` for such rows. This checks the data set for columns of class `<rsi>` and consequently requires transforming columns with antibiotic results using [as.rsi()] first.
|
||||
#' @param ... arguments passed on to [first_isolate()] when using [filter_first_isolate()], otherwise arguments passed on to [key_antimicrobials()] (such as `universal`, `gram_negative`, `gram_positive`)
|
||||
#' @details
|
||||
#' To conduct epidemiological analyses on antimicrobial resistance data, only so-called first isolates should be included to prevent overestimation and underestimation of antimicrobial resistance. Different methods can be used to do so, see below.
|
||||
#'
|
||||
#' These functions are context-aware. This means that the `x` argument can be left blank if used inside a [data.frame] call, see *Examples*.
|
||||
#'
|
||||
#' The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but more efficient for data sets containing microorganism codes or names.
|
||||
#'
|
||||
#' All isolates with a microbial ID of `NA` will be excluded as first isolate.
|
||||
#'
|
||||
#' ## Different methods
|
||||
#'
|
||||
#' According to Hindler *et al.* (2007, \doi{10.1086/511864}), there are different methods (algorithms) to select first isolates with increasing reliability: isolate-based, patient-based, episode-based and phenotype-based. All methods select on a combination of the taxonomic genus and species (not subspecies).
|
||||
#'
|
||||
#' All mentioned methods are covered in the [first_isolate()] function:
|
||||
#'
|
||||
#'
|
||||
#' | **Method** | **Function to apply** |
|
||||
#' |--------------------------------------------------|-------------------------------------------------------|
|
||||
#' | **Isolate-based** | `first_isolate(x, method = "isolate-based")` |
|
||||
#' | *(= all isolates)* | |
|
||||
#' | | |
|
||||
#' | | |
|
||||
#' | **Patient-based** | `first_isolate(x, method = "patient-based")` |
|
||||
#' | *(= first isolate per patient)* | |
|
||||
#' | | |
|
||||
#' | | |
|
||||
#' | **Episode-based** | `first_isolate(x, method = "episode-based")`, or: |
|
||||
#' | *(= first isolate per episode)* | |
|
||||
#' | - 7-Day interval from initial isolate | - `first_isolate(x, method = "e", episode_days = 7)` |
|
||||
#' | - 30-Day interval from initial isolate | - `first_isolate(x, method = "e", episode_days = 30)` |
|
||||
#' | | |
|
||||
#' | | |
|
||||
#' | **Phenotype-based** | `first_isolate(x, method = "phenotype-based")`, or: |
|
||||
#' | *(= first isolate per phenotype)* | |
|
||||
#' | - Major difference in any antimicrobial result | - `first_isolate(x, type = "points")` |
|
||||
#' | - Any difference in key antimicrobial results | - `first_isolate(x, type = "keyantimicrobials")` |
|
||||
#'
|
||||
#' ### Isolate-based
|
||||
#'
|
||||
#' This method does not require any selection, as all isolates should be included. It does, however, respect all arguments set in the [first_isolate()] function. For example, the default setting for `include_unknown` (`FALSE`) will omit selection of rows without a microbial ID.
|
||||
#'
|
||||
#' ### Patient-based
|
||||
#'
|
||||
#' To include every genus-species combination per patient once, set the `episode_days` to `Inf`. Although often inappropriate, this method makes sure that no duplicate isolates are selected from the same patient. In a large longitudinal data set, this could mean that isolates are *excluded* that were found years after the initial isolate.
|
||||
#'
|
||||
#' ### Episode-based
|
||||
#'
|
||||
#' To include every genus-species combination per patient episode once, set the `episode_days` to a sensible number of days. Depending on the type of analysis, this could be 14, 30, 60 or 365. Short episodes are common for analysing specific hospital or ward data, long episodes are common for analysing regional and national data.
|
||||
#'
|
||||
#' This is the most common method to correct for duplicate isolates. Patients are categorised into episodes based on their ID and dates (e.g., the date of specimen receipt or laboratory result). While this is a common method, it does not take into account antimicrobial test results. This means that e.g. a methicillin-resistant *Staphylococcus aureus* (MRSA) isolate cannot be differentiated from a wildtype *Staphylococcus aureus* isolate.
|
||||
#'
|
||||
#' ### Phenotype-based
|
||||
#'
|
||||
#' This is a more reliable method, since it also *weighs* the antibiogram (antimicrobial test results) yielding so-called 'first weighted isolates'. There are two different methods to weigh the antibiogram:
|
||||
#'
|
||||
#' 1. Using `type = "points"` and argument `points_threshold` (default)
|
||||
#'
|
||||
#' This method weighs *all* antimicrobial agents available in the data set. Any difference from I to S or R (or vice versa) counts as `0.5` points, a difference from S to R (or vice versa) counts as `1` point. When the sum of points exceeds `points_threshold`, which defaults to `2`, an isolate will be selected as a first weighted isolate.
|
||||
#'
|
||||
#' All antimicrobials are internally selected using the [all_antimicrobials()] function. The output of this function does not need to be passed to the [first_isolate()] function.
|
||||
#'
|
||||
#'
|
||||
#' 2. Using `type = "keyantimicrobials"` and argument `ignore_I`
|
||||
#'
|
||||
#' This method only weighs specific antimicrobial agents, called *key antimicrobials*. Any difference from S to R (or vice versa) in these key antimicrobials will select an isolate as a first weighted isolate. With `ignore_I = FALSE`, also differences from I to S or R (or vice versa) will lead to this.
|
||||
#'
|
||||
#' Key antimicrobials are internally selected using the [key_antimicrobials()] function, but can also be added manually as a variable to the data and set in the `col_keyantimicrobials` argument. Another option is to pass the output of the [key_antimicrobials()] function directly to the `col_keyantimicrobials` argument.
|
||||
#'
|
||||
#'
|
||||
#' The default method is phenotype-based (using `type = "points"`) and episode-based (using `episode_days = 365`). This makes sure that every genus-species combination is selected per patient once per year, while taking into account all antimicrobial test results. If no antimicrobial test results are available in the data set, only the episode-based method is applied at default.
|
||||
#' @rdname first_isolate
|
||||
#' @seealso [key_antimicrobials()]
|
||||
#' @export
|
||||
#' @return A [`logical`] vector
|
||||
#' @source Methodology of this function is strictly based on:
|
||||
#'
|
||||
#' - **M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition**, 2014, *Clinical and Laboratory Standards Institute (CLSI)*. <https://clsi.org/standards/products/microbiology/documents/m39/>.
|
||||
#'
|
||||
#' - Hindler JF and Stelling J (2007). **Analysis and Presentation of Cumulative Antibiograms: A New Consensus Guideline from the Clinical and Laboratory Standards Institute.** Clinical Infectious Diseases, 44(6), 867-873. \doi{10.1086/511864}
|
||||
#' @examples
|
||||
#' # `example_isolates` is a data set available in the AMR package.
|
||||
#' # See ?example_isolates.
|
||||
#'
|
||||
#' example_isolates[first_isolate(), ]
|
||||
#' \donttest{
|
||||
#' # get all first Gram-negatives
|
||||
#' example_isolates[which(first_isolate(info = FALSE) & mo_is_gram_negative()), ]
|
||||
#'
|
||||
#' if (require("dplyr")) {
|
||||
#' # filter on first isolates using dplyr:
|
||||
#' example_isolates %>%
|
||||
#' filter(first_isolate())
|
||||
#'
|
||||
#' # short-hand version:
|
||||
#' example_isolates %>%
|
||||
#' filter_first_isolate(info = FALSE)
|
||||
#'
|
||||
#' # flag the first isolates per group:
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' mutate(first = first_isolate()) %>%
|
||||
#' select(hospital_id, date, patient_id, mo, first)
|
||||
#'
|
||||
#' # now let's see if first isolates matter:
|
||||
#' A <- example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(count = n_rsi(GEN), # gentamicin availability
|
||||
#' resistance = resistance(GEN)) # gentamicin resistance
|
||||
#'
|
||||
#' B <- example_isolates %>%
|
||||
#' filter_first_isolate() %>% # the 1st isolate filter
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(count = n_rsi(GEN), # gentamicin availability
|
||||
#' resistance = resistance(GEN)) # gentamicin resistance
|
||||
#'
|
||||
#' # Have a look at A and B.
|
||||
#' A
|
||||
#' B
|
||||
#'
|
||||
#' # B is more reliable because every isolate is counted only once.
|
||||
#' # Gentamicin resistance in hospital D appears to be 4.2% higher than
|
||||
#' # when you (erroneously) would have used all isolates for analysis.
|
||||
#' }
|
||||
#' }
|
||||
first_isolate <- function(x = NULL,
|
||||
col_date = NULL,
|
||||
col_patient_id = NULL,
|
||||
col_mo = NULL,
|
||||
col_testcode = NULL,
|
||||
col_specimen = NULL,
|
||||
col_icu = NULL,
|
||||
col_keyantimicrobials = NULL,
|
||||
episode_days = 365,
|
||||
testcodes_exclude = NULL,
|
||||
icu_exclude = FALSE,
|
||||
specimen_group = NULL,
|
||||
type = "points",
|
||||
method = c("phenotype-based", "episode-based", "patient-based", "isolate-based"),
|
||||
ignore_I = TRUE,
|
||||
points_threshold = 2,
|
||||
info = interactive(),
|
||||
include_unknown = FALSE,
|
||||
include_untested_rsi = TRUE,
|
||||
...) {
|
||||
|
||||
dots <- unlist(list(...))
|
||||
if (length(dots) != 0) {
|
||||
# backwards compatibility with old arguments
|
||||
dots.names <- names(dots)
|
||||
if ("filter_specimen" %in% dots.names) {
|
||||
specimen_group <- dots[which(dots.names == "filter_specimen")]
|
||||
}
|
||||
if ("col_keyantibiotics" %in% dots.names) {
|
||||
col_keyantimicrobials <- dots[which(dots.names == "col_keyantibiotics")]
|
||||
}
|
||||
}
|
||||
|
||||
if (is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
|
||||
}
|
||||
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
|
||||
meet_criteria(col_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
meet_criteria(col_patient_id, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
meet_criteria(col_testcode, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
if (isFALSE(col_specimen)) {
|
||||
col_specimen <- NULL
|
||||
}
|
||||
meet_criteria(col_specimen, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
meet_criteria(col_icu, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
# method
|
||||
method <- coerce_method(method)
|
||||
meet_criteria(method, allow_class = "character", has_length = 1, is_in = c("phenotype-based", "episode-based", "patient-based", "isolate-based"))
|
||||
# key antimicrobials
|
||||
if (length(col_keyantimicrobials) > 1) {
|
||||
meet_criteria(col_keyantimicrobials, allow_class = "character", has_length = nrow(x))
|
||||
x$keyabcol <- col_keyantimicrobials
|
||||
col_keyantimicrobials <- "keyabcol"
|
||||
} else {
|
||||
if (isFALSE(col_keyantimicrobials)) {
|
||||
col_keyantimicrobials <- NULL
|
||||
# method cannot be phenotype-based anymore
|
||||
if (method == "phenotype-based") {
|
||||
method <- "episode-based"
|
||||
}
|
||||
}
|
||||
meet_criteria(col_keyantimicrobials, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
}
|
||||
meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
|
||||
meet_criteria(testcodes_exclude, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(icu_exclude, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(specimen_group, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(type, allow_class = "character", has_length = 1, is_in = c("points", "keyantimicrobials"))
|
||||
meet_criteria(ignore_I, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(points_threshold, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(info, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(include_unknown, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(include_untested_rsi, allow_class = "logical", has_length = 1)
|
||||
|
||||
# remove data.table, grouping from tibbles, etc.
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
||||
|
||||
any_col_contains_rsi <- any(vapply(FUN.VALUE = logical(1),
|
||||
X = x,
|
||||
# check only first 10,000 rows
|
||||
FUN = function(x) any(as.character(x[1:10000]) %in% c("R", "S", "I"), na.rm = TRUE),
|
||||
USE.NAMES = FALSE))
|
||||
if (method == "phenotype-based" & !any_col_contains_rsi) {
|
||||
method <- "episode-based"
|
||||
}
|
||||
if (info == TRUE & message_not_thrown_before("first_isolate", "method")) {
|
||||
message_(paste0("Determining first isolates ",
|
||||
ifelse(method %in% c("episode-based", "phenotype-based"),
|
||||
ifelse(is.infinite(episode_days),
|
||||
"without a specified episode length",
|
||||
paste("using an episode length of", episode_days, "days")),
|
||||
"")),
|
||||
as_note = FALSE,
|
||||
add_fn = font_black)
|
||||
}
|
||||
|
||||
# try to find columns based on type
|
||||
# -- mo
|
||||
if (is.null(col_mo)) {
|
||||
col_mo <- search_type_in_df(x = x, type = "mo", info = info)
|
||||
stop_if(is.null(col_mo), "`col_mo` must be set")
|
||||
}
|
||||
|
||||
# methods ----
|
||||
if (method == "isolate-based") {
|
||||
episode_days <- Inf
|
||||
col_keyantimicrobials <- NULL
|
||||
x$dummy_dates <- Sys.Date()
|
||||
col_date <- "dummy_dates"
|
||||
x$dummy_patients <- paste("dummy", seq_len(nrow(x))) # all 'patients' must be unique
|
||||
col_patient_id <- "dummy_patients"
|
||||
} else if (method == "patient-based") {
|
||||
episode_days <- Inf
|
||||
col_keyantimicrobials <- NULL
|
||||
} else if (method == "episode-based") {
|
||||
col_keyantimicrobials <- NULL
|
||||
} else if (method == "phenotype-based") {
|
||||
if (missing(type) & !is.null(col_keyantimicrobials)) {
|
||||
# type = "points" is default, but not set explicitly, while col_keyantimicrobials is
|
||||
type <- "keyantimicrobials"
|
||||
}
|
||||
if (type == "points") {
|
||||
x$keyantimicrobials <- all_antimicrobials(x, only_rsi_columns = FALSE)
|
||||
col_keyantimicrobials <- "keyantimicrobials"
|
||||
} else if (type == "keyantimicrobials" & is.null(col_keyantimicrobials)) {
|
||||
col_keyantimicrobials <- search_type_in_df(x = x, type = "keyantimicrobials", info = info)
|
||||
if (is.null(col_keyantimicrobials)) {
|
||||
# still not found as a column, create it ourselves
|
||||
x$keyantimicrobials <- key_antimicrobials(x, only_rsi_columns = FALSE, col_mo = col_mo, ...)
|
||||
col_keyantimicrobials <- "keyantimicrobials"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
# -- date
|
||||
if (is.null(col_date)) {
|
||||
col_date <- search_type_in_df(x = x, type = "date", info = info)
|
||||
stop_if(is.null(col_date), "`col_date` must be set")
|
||||
}
|
||||
|
||||
# -- patient id
|
||||
if (is.null(col_patient_id)) {
|
||||
if (all(c("First name", "Last name", "Sex") %in% colnames(x))) {
|
||||
# WHONET support
|
||||
x$patient_id <- paste(x$`First name`, x$`Last name`, x$Sex)
|
||||
col_patient_id <- "patient_id"
|
||||
message_("Using combined columns '", font_bold("First name"), "', '", font_bold("Last name"), "' and '", font_bold("Sex"), "' as input for `col_patient_id`")
|
||||
} else {
|
||||
col_patient_id <- search_type_in_df(x = x, type = "patient_id", info = info)
|
||||
}
|
||||
stop_if(is.null(col_patient_id), "`col_patient_id` must be set")
|
||||
}
|
||||
|
||||
# -- specimen
|
||||
if (is.null(col_specimen) & !is.null(specimen_group)) {
|
||||
col_specimen <- search_type_in_df(x = x, type = "specimen", info = info)
|
||||
}
|
||||
|
||||
# check if columns exist
|
||||
check_columns_existance <- function(column, tblname = x) {
|
||||
if (!is.null(column)) {
|
||||
stop_ifnot(column %in% colnames(tblname),
|
||||
"Column '", column, "' not found.", call = FALSE)
|
||||
}
|
||||
}
|
||||
|
||||
check_columns_existance(col_date)
|
||||
check_columns_existance(col_patient_id)
|
||||
check_columns_existance(col_mo)
|
||||
check_columns_existance(col_testcode)
|
||||
check_columns_existance(col_icu)
|
||||
check_columns_existance(col_keyantimicrobials)
|
||||
|
||||
# convert dates to Date
|
||||
dates <- as.Date(x[, col_date, drop = TRUE])
|
||||
dates[is.na(dates)] <- as.Date("1970-01-01")
|
||||
x[, col_date] <- dates
|
||||
|
||||
# create original row index
|
||||
x$newvar_row_index <- seq_len(nrow(x))
|
||||
x$newvar_mo <- as.mo(x[, col_mo, drop = TRUE])
|
||||
x$newvar_genus_species <- paste(mo_genus(x$newvar_mo), mo_species(x$newvar_mo))
|
||||
x$newvar_date <- x[, col_date, drop = TRUE]
|
||||
x$newvar_patient_id <- x[, col_patient_id, drop = TRUE]
|
||||
|
||||
if (is.null(col_testcode)) {
|
||||
testcodes_exclude <- NULL
|
||||
}
|
||||
# remove testcodes
|
||||
if (!is.null(testcodes_exclude) & info == TRUE & message_not_thrown_before("first_isolate", "excludingtestcodes")) {
|
||||
message_("Excluding test codes: ", vector_and(testcodes_exclude, quotes = TRUE),
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
}
|
||||
|
||||
if (is.null(col_specimen)) {
|
||||
specimen_group <- NULL
|
||||
}
|
||||
|
||||
# filter on specimen group and keyantibiotics when they are filled in
|
||||
if (!is.null(specimen_group)) {
|
||||
check_columns_existance(col_specimen, x)
|
||||
if (info == TRUE & message_not_thrown_before("first_isolate", "excludingspecimen")) {
|
||||
message_("Excluding other than specimen group '", specimen_group, "'",
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
}
|
||||
}
|
||||
if (!is.null(col_keyantimicrobials)) {
|
||||
x$newvar_key_ab <- x[, col_keyantimicrobials, drop = TRUE]
|
||||
}
|
||||
|
||||
if (is.null(testcodes_exclude)) {
|
||||
testcodes_exclude <- ""
|
||||
}
|
||||
|
||||
# arrange data to the right sorting
|
||||
if (is.null(specimen_group)) {
|
||||
x <- x[order(x$newvar_patient_id,
|
||||
x$newvar_genus_species,
|
||||
x$newvar_date), ]
|
||||
rownames(x) <- NULL
|
||||
row.start <- 1
|
||||
row.end <- nrow(x)
|
||||
} else {
|
||||
# filtering on specimen and only analyse these rows to save time
|
||||
x <- x[order(pm_pull(x, col_specimen),
|
||||
x$newvar_patient_id,
|
||||
x$newvar_genus_species,
|
||||
x$newvar_date), ]
|
||||
rownames(x) <- NULL
|
||||
suppressWarnings(
|
||||
row.start <- which(x %pm>% pm_pull(col_specimen) == specimen_group) %pm>% min(na.rm = TRUE)
|
||||
)
|
||||
suppressWarnings(
|
||||
row.end <- which(x %pm>% pm_pull(col_specimen) == specimen_group) %pm>% max(na.rm = TRUE)
|
||||
)
|
||||
}
|
||||
|
||||
# speed up - return immediately if obvious
|
||||
if (abs(row.start) == Inf | abs(row.end) == Inf) {
|
||||
if (info == TRUE) {
|
||||
message_("=> Found ", font_bold("no isolates"),
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
}
|
||||
return(rep(FALSE, nrow(x)))
|
||||
}
|
||||
if (row.start == row.end) {
|
||||
if (info == TRUE) {
|
||||
message_("=> Found ", font_bold("1 first isolate"), ", as the data only contained 1 row",
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
}
|
||||
return(TRUE)
|
||||
}
|
||||
if (length(c(row.start:row.end)) == pm_n_distinct(x[c(row.start:row.end), col_mo, drop = TRUE])) {
|
||||
if (info == TRUE) {
|
||||
message_("=> Found ", font_bold(paste(length(c(row.start:row.end)), "first isolates")),
|
||||
", as all isolates were different microbial species",
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
}
|
||||
return(rep(TRUE, length(c(row.start:row.end))))
|
||||
}
|
||||
|
||||
# did find some isolates - add new index numbers of rows
|
||||
x$newvar_row_index_sorted <- seq_len(nrow(x))
|
||||
|
||||
scope.size <- nrow(x[which(x$newvar_row_index_sorted %in% c(row.start + 1:row.end) &
|
||||
!is.na(x$newvar_mo)), , drop = FALSE])
|
||||
|
||||
# Analysis of first isolate ----
|
||||
if (!is.null(col_keyantimicrobials)) {
|
||||
if (info == TRUE & message_not_thrown_before("first_isolate", "type")) {
|
||||
if (type == "keyantimicrobials") {
|
||||
message_("Basing inclusion on key antimicrobials, ",
|
||||
ifelse(ignore_I == FALSE, "not ", ""),
|
||||
"ignoring I",
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
}
|
||||
if (type == "points") {
|
||||
message_("Basing inclusion on all antimicrobial results, using a points threshold of ",
|
||||
points_threshold,
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
x$other_pat_or_mo <- ifelse(x$newvar_patient_id == pm_lag(x$newvar_patient_id) &
|
||||
x$newvar_genus_species == pm_lag(x$newvar_genus_species),
|
||||
FALSE,
|
||||
TRUE)
|
||||
|
||||
x$episode_group <- paste(x$newvar_patient_id, x$newvar_genus_species)
|
||||
x$more_than_episode_ago <- unlist(lapply(split(x$newvar_date,
|
||||
x$episode_group),
|
||||
exec_episode, # this will skip meet_criteria() in is_new_episode(), saving time
|
||||
type = "logical",
|
||||
episode_days = episode_days),
|
||||
use.names = FALSE)
|
||||
|
||||
if (!is.null(col_keyantimicrobials)) {
|
||||
# with key antibiotics
|
||||
x$other_key_ab <- !antimicrobials_equal(y = x$newvar_key_ab,
|
||||
z = pm_lag(x$newvar_key_ab),
|
||||
type = type,
|
||||
ignore_I = ignore_I,
|
||||
points_threshold = points_threshold)
|
||||
x$newvar_first_isolate <- pm_if_else(x$newvar_row_index_sorted >= row.start &
|
||||
x$newvar_row_index_sorted <= row.end &
|
||||
x$newvar_genus_species != "" &
|
||||
(x$other_pat_or_mo | x$more_than_episode_ago | x$other_key_ab),
|
||||
TRUE,
|
||||
FALSE)
|
||||
} else {
|
||||
# no key antibiotics
|
||||
x$newvar_first_isolate <- pm_if_else(x$newvar_row_index_sorted >= row.start &
|
||||
x$newvar_row_index_sorted <= row.end &
|
||||
x$newvar_genus_species != "" &
|
||||
(x$other_pat_or_mo | x$more_than_episode_ago),
|
||||
TRUE,
|
||||
FALSE)
|
||||
}
|
||||
|
||||
# first one as TRUE
|
||||
x[row.start, "newvar_first_isolate"] <- TRUE
|
||||
# no tests that should be included, or ICU
|
||||
if (!is.null(col_testcode)) {
|
||||
x[which(x[, col_testcode] %in% tolower(testcodes_exclude)), "newvar_first_isolate"] <- FALSE
|
||||
}
|
||||
if (!is.null(col_icu)) {
|
||||
if (icu_exclude == TRUE) {
|
||||
message_("Excluding isolates from ICU.",
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
x[which(as.logical(x[, col_icu, drop = TRUE])), "newvar_first_isolate"] <- FALSE
|
||||
} else {
|
||||
message_("Including isolates from ICU.",
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
}
|
||||
}
|
||||
|
||||
decimal.mark <- getOption("OutDec")
|
||||
big.mark <- ifelse(decimal.mark != ",", ",", ".")
|
||||
|
||||
if (info == TRUE) {
|
||||
# print group name if used in dplyr::group_by()
|
||||
cur_group <- import_fn("cur_group", "dplyr", error_on_fail = FALSE)
|
||||
if (!is.null(cur_group)) {
|
||||
group_df <- tryCatch(cur_group(), error = function(e) data.frame())
|
||||
if (NCOL(group_df) > 0) {
|
||||
# transform factors to characters
|
||||
group <- vapply(FUN.VALUE = character(1), group_df, function(x) {
|
||||
if (is.numeric(x)) {
|
||||
format(x)
|
||||
} else if (is.logical(x)) {
|
||||
as.character(x)
|
||||
} else {
|
||||
paste0('"', x, '"')
|
||||
}
|
||||
})
|
||||
message_("\nGroup: ", paste0(names(group), " = ", group, collapse = ", "), "\n",
|
||||
as_note = FALSE,
|
||||
add_fn = font_red)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
# handle empty microorganisms
|
||||
if (any(x$newvar_mo == "UNKNOWN", na.rm = TRUE) & info == TRUE) {
|
||||
message_(ifelse(include_unknown == TRUE, "Included ", "Excluded "),
|
||||
format(sum(x$newvar_mo == "UNKNOWN", na.rm = TRUE),
|
||||
decimal.mark = decimal.mark, big.mark = big.mark),
|
||||
" isolates with a microbial ID 'UNKNOWN' (in column '", font_bold(col_mo), "')")
|
||||
}
|
||||
x[which(x$newvar_mo == "UNKNOWN"), "newvar_first_isolate"] <- include_unknown
|
||||
|
||||
# exclude all NAs
|
||||
if (any(is.na(x$newvar_mo)) & info == TRUE) {
|
||||
message_("Excluded ", format(sum(is.na(x$newvar_mo), na.rm = TRUE),
|
||||
decimal.mark = decimal.mark, big.mark = big.mark),
|
||||
" isolates with a microbial ID 'NA' (in column '", font_bold(col_mo), "')")
|
||||
}
|
||||
x[which(is.na(x$newvar_mo)), "newvar_first_isolate"] <- FALSE
|
||||
|
||||
# handle isolates without antibiogram
|
||||
if (include_untested_rsi == FALSE && any(is.rsi(x))) {
|
||||
rsi_all_NA <- which(unname(vapply(FUN.VALUE = logical(1),
|
||||
as.data.frame(t(x[, is.rsi(x), drop = FALSE])),
|
||||
function(rsi_values) all(is.na(rsi_values)))))
|
||||
x[rsi_all_NA, "newvar_first_isolate"] <- FALSE
|
||||
}
|
||||
|
||||
# arrange back according to original sorting again
|
||||
x <- x[order(x$newvar_row_index), , drop = FALSE]
|
||||
rownames(x) <- NULL
|
||||
|
||||
if (info == TRUE) {
|
||||
n_found <- sum(x$newvar_first_isolate, na.rm = TRUE)
|
||||
p_found_total <- percentage(n_found / nrow(x[which(!is.na(x$newvar_mo)), , drop = FALSE]), digits = 1)
|
||||
p_found_scope <- percentage(n_found / scope.size, digits = 1)
|
||||
if (p_found_total %unlike% "[.]") {
|
||||
p_found_total <- gsub("%", ".0%", p_found_total, fixed = TRUE)
|
||||
}
|
||||
if (p_found_scope %unlike% "[.]") {
|
||||
p_found_scope <- gsub("%", ".0%", p_found_scope, fixed = TRUE)
|
||||
}
|
||||
# mark up number of found
|
||||
n_found <- format(n_found, big.mark = big.mark, decimal.mark = decimal.mark)
|
||||
message_(paste0("=> Found ",
|
||||
font_bold(paste0(n_found,
|
||||
ifelse(method == "isolate-based", "", paste0(" '", method, "'")),
|
||||
" first isolates")),
|
||||
" (",
|
||||
ifelse(p_found_total != p_found_scope,
|
||||
paste0(p_found_scope, " within scope and "),
|
||||
""),
|
||||
p_found_total, " of total where a microbial ID was available)"),
|
||||
add_fn = font_black, as_note = FALSE)
|
||||
}
|
||||
|
||||
x$newvar_first_isolate
|
||||
|
||||
}
|
||||
|
||||
#' @rdname first_isolate
|
||||
#' @export
|
||||
filter_first_isolate <- function(x = NULL,
|
||||
col_date = NULL,
|
||||
col_patient_id = NULL,
|
||||
col_mo = NULL,
|
||||
episode_days = 365,
|
||||
method = c("phenotype-based", "episode-based", "patient-based", "isolate-based"),
|
||||
...) {
|
||||
if (is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
|
||||
}
|
||||
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
|
||||
meet_criteria(col_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
meet_criteria(col_patient_id, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
|
||||
method <- coerce_method(method)
|
||||
meet_criteria(method, allow_class = "character", has_length = 1, is_in = c("phenotype-based", "episode-based", "patient-based", "isolate-based"))
|
||||
|
||||
subset(x, first_isolate(x = x,
|
||||
col_date = col_date,
|
||||
col_patient_id = col_patient_id,
|
||||
col_mo = col_mo,
|
||||
episode_days = episode_days,
|
||||
method = method,
|
||||
...))
|
||||
}
|
||||
|
||||
coerce_method <- function(method) {
|
||||
if (is.null(method)) {
|
||||
return(method)
|
||||
}
|
||||
method <- tolower(as.character(method[1L]))
|
||||
method[method %like% "^(p$|pheno)"] <- "phenotype-based"
|
||||
method[method %like% "^(e$|episode)"] <- "episode-based"
|
||||
method[method %like% "^pat"] <- "patient-based"
|
||||
method[method %like% "^(i$|iso)"] <- "isolate-based"
|
||||
method
|
||||
}
|
||||
-202
@@ -1,202 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' *G*-test for Count Data
|
||||
#'
|
||||
#' [g.test()] performs chi-squared contingency table tests and goodness-of-fit tests, just like [chisq.test()] but is more reliable (1). A *G*-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a ***G*-test of goodness-of-fit**), or to see whether the proportions of one variable are different for different values of the other variable (called a ***G*-test of independence**).
|
||||
#' @inherit stats::chisq.test params return
|
||||
#' @details If `x` is a [matrix] with one row or column, or if `x` is a vector and `y` is not given, then a *goodness-of-fit test* is performed (`x` is treated as a one-dimensional contingency table). The entries of `x` must be non-negative integers. In this case, the hypothesis tested is whether the population probabilities equal those in `p`, or are all equal if `p` is not given.
|
||||
#'
|
||||
#' If `x` is a [matrix] with at least two rows and columns, it is taken as a two-dimensional contingency table: the entries of `x` must be non-negative integers. Otherwise, `x` and `y` must be vectors or factors of the same length; cases with missing values are removed, the objects are coerced to factors, and the contingency table is computed from these. Then Pearson's chi-squared test is performed of the null hypothesis that the joint distribution of the cell counts in a 2-dimensional contingency table is the product of the row and column marginals.
|
||||
#'
|
||||
#' The p-value is computed from the asymptotic chi-squared distribution of the test statistic.
|
||||
#'
|
||||
#' In the contingency table case simulation is done by random sampling from the set of all contingency tables with given marginals, and works only if the marginals are strictly positive. Note that this is not the usual sampling situation assumed for a chi-squared test (such as the *G*-test) but rather that for Fisher's exact test.
|
||||
#'
|
||||
#' In the goodness-of-fit case simulation is done by random sampling from the discrete distribution specified by `p`, each sample being of size `n = sum(x)`. This simulation is done in \R and may be slow.
|
||||
#'
|
||||
#' ## *G*-test Of Goodness-of-Fit (Likelihood Ratio Test)
|
||||
#' Use the *G*-test of goodness-of-fit when you have one nominal variable with two or more values (such as male and female, or red, pink and white flowers). You compare the observed counts of numbers of observations in each category with the expected counts, which you calculate using some kind of theoretical expectation (such as a 1:1 sex ratio or a 1:2:1 ratio in a genetic cross).
|
||||
#'
|
||||
#' If the expected number of observations in any category is too small, the *G*-test may give inaccurate results, and you should use an exact test instead ([fisher.test()]).
|
||||
#'
|
||||
#' The *G*-test of goodness-of-fit is an alternative to the chi-square test of goodness-of-fit ([chisq.test()]); each of these tests has some advantages and some disadvantages, and the results of the two tests are usually very similar.
|
||||
#'
|
||||
#' ## *G*-test of Independence
|
||||
#' Use the *G*-test of independence when you have two nominal variables, each with two or more possible values. You want to know whether the proportions for one variable are different among values of the other variable.
|
||||
#'
|
||||
#' It is also possible to do a *G*-test of independence with more than two nominal variables. For example, Jackson et al. (2013) also had data for children under 3, so you could do an analysis of old vs. young, thigh vs. arm, and reaction vs. no reaction, all analyzed together.
|
||||
#'
|
||||
#' Fisher's exact test ([fisher.test()]) is an **exact** test, where the *G*-test is still only an **approximation**. For any 2x2 table, Fisher's Exact test may be slower but will still run in seconds, even if the sum of your observations is multiple millions.
|
||||
#'
|
||||
#' The *G*-test of independence is an alternative to the chi-square test of independence ([chisq.test()]), and they will give approximately the same results.
|
||||
#'
|
||||
#' ## How the Test Works
|
||||
#' Unlike the exact test of goodness-of-fit ([fisher.test()]), the *G*-test does not directly calculate the probability of obtaining the observed results or something more extreme. Instead, like almost all statistical tests, the *G*-test has an intermediate step; it uses the data to calculate a test statistic that measures how far the observed data are from the null expectation. You then use a mathematical relationship, in this case the chi-square distribution, to estimate the probability of obtaining that value of the test statistic.
|
||||
#'
|
||||
#' The *G*-test uses the log of the ratio of two likelihoods as the test statistic, which is why it is also called a likelihood ratio test or log-likelihood ratio test. The formula to calculate a *G*-statistic is:
|
||||
#'
|
||||
#' \eqn{G = 2 * sum(x * log(x / E))}
|
||||
#'
|
||||
#' where `E` are the expected values. Since this is chi-square distributed, the p value can be calculated in \R with:
|
||||
#' ```
|
||||
#' p <- stats::pchisq(G, df, lower.tail = FALSE)
|
||||
#' ```
|
||||
#' where `df` are the degrees of freedom.
|
||||
#'
|
||||
#' If there are more than two categories and you want to find out which ones are significantly different from their null expectation, you can use the same method of testing each category vs. the sum of all categories, with the Bonferroni correction. You use *G*-tests for each category, of course.
|
||||
#' @seealso [chisq.test()]
|
||||
#' @references 1. McDonald, J.H. 2014. **Handbook of Biological Statistics (3rd ed.)**. Sparky House Publishing, Baltimore, Maryland. <http://www.biostathandbook.com/gtestgof.html>.
|
||||
#' @source The code for this function is identical to that of [chisq.test()], except that:
|
||||
#' - The calculation of the statistic was changed to \eqn{2 * sum(x * log(x / E))}
|
||||
#' - Yates' continuity correction was removed as it does not apply to a *G*-test
|
||||
#' - The possibility to simulate p values with `simulate.p.value` was removed
|
||||
#' @export
|
||||
#' @importFrom stats pchisq complete.cases
|
||||
#' @examples
|
||||
#' # = EXAMPLE 1 =
|
||||
#' # Shivrain et al. (2006) crossed clearfield rice (which are resistant
|
||||
#' # to the herbicide imazethapyr) with red rice (which are susceptible to
|
||||
#' # imazethapyr). They then crossed the hybrid offspring and examined the
|
||||
#' # F2 generation, where they found 772 resistant plants, 1611 moderately
|
||||
#' # resistant plants, and 737 susceptible plants. If resistance is controlled
|
||||
#' # by a single gene with two co-dominant alleles, you would expect a 1:2:1
|
||||
#' # ratio.
|
||||
#'
|
||||
#' x <- c(772, 1611, 737)
|
||||
#' g.test(x, p = c(1, 2, 1) / 4)
|
||||
#'
|
||||
#' # There is no significant difference from a 1:2:1 ratio.
|
||||
#' # Meaning: resistance controlled by a single gene with two co-dominant
|
||||
#' # alleles, is plausible.
|
||||
#'
|
||||
#'
|
||||
#' # = EXAMPLE 2 =
|
||||
#' # Red crossbills (Loxia curvirostra) have the tip of the upper bill either
|
||||
#' # right or left of the lower bill, which helps them extract seeds from pine
|
||||
#' # cones. Some have hypothesized that frequency-dependent selection would
|
||||
#' # keep the number of right and left-billed birds at a 1:1 ratio. Groth (1992)
|
||||
#' # observed 1752 right-billed and 1895 left-billed crossbills.
|
||||
#'
|
||||
#' x <- c(1752, 1895)
|
||||
#' g.test(x)
|
||||
#'
|
||||
#' # There is a significant difference from a 1:1 ratio.
|
||||
#' # Meaning: there are significantly more left-billed birds.
|
||||
g.test <- function(x,
|
||||
y = NULL,
|
||||
# correct = TRUE,
|
||||
p = rep(1 / length(x), length(x)),
|
||||
rescale.p = FALSE) {
|
||||
DNAME <- deparse(substitute(x))
|
||||
if (is.data.frame(x))
|
||||
x <- as.matrix(x)
|
||||
if (is.matrix(x)) {
|
||||
if (min(dim(x)) == 1L)
|
||||
x <- as.vector(x)
|
||||
}
|
||||
if (!is.matrix(x) && !is.null(y)) {
|
||||
if (length(x) != length(y))
|
||||
stop("'x' and 'y' must have the same length")
|
||||
DNAME2 <- deparse(substitute(y))
|
||||
xname <- if (length(DNAME) > 1L || nchar(DNAME, "w") >
|
||||
30)
|
||||
""
|
||||
else DNAME
|
||||
yname <- if (length(DNAME2) > 1L || nchar(DNAME2, "w") >
|
||||
30)
|
||||
""
|
||||
else DNAME2
|
||||
OK <- complete.cases(x, y)
|
||||
x <- factor(x[OK])
|
||||
y <- factor(y[OK])
|
||||
if ((nlevels(x) < 2L) || (nlevels(y) < 2L))
|
||||
stop("'x' and 'y' must have at least 2 levels")
|
||||
x <- table(x, y)
|
||||
names(dimnames(x)) <- c(xname, yname)
|
||||
DNAME <- paste(paste(DNAME, collapse = "\n"), "and",
|
||||
paste(DNAME2, collapse = "\n"))
|
||||
}
|
||||
if (any(x < 0) || any(is.na((x)))) # this last one was anyNA, but only introduced in R 3.1.0
|
||||
stop("all entries of 'x' must be nonnegative and finite")
|
||||
if ((n <- sum(x)) == 0)
|
||||
stop("at least one entry of 'x' must be positive")
|
||||
|
||||
|
||||
if (is.matrix(x)) {
|
||||
METHOD <- "G-test of independence"
|
||||
nr <- as.integer(nrow(x))
|
||||
nc <- as.integer(ncol(x))
|
||||
if (is.na(nr) || is.na(nc) || is.na(nr * nc))
|
||||
stop("invalid nrow(x) or ncol(x)", domain = NA)
|
||||
# add fisher.test suggestion
|
||||
if (nr == 2 && nc == 2)
|
||||
warning("`fisher.test()` is always more reliable for 2x2 tables and although much slower, often only takes seconds.")
|
||||
sr <- rowSums(x)
|
||||
sc <- colSums(x)
|
||||
E <- outer(sr, sc, "*") / n
|
||||
v <- function(r, c, n) c * r * (n - r) * (n - c) / n ^ 3
|
||||
V <- outer(sr, sc, v, n)
|
||||
dimnames(E) <- dimnames(x)
|
||||
|
||||
STATISTIC <- 2 * sum(x * log(x / E)) # sum((abs(x - E) - YATES)^2/E) for chisq.test
|
||||
PARAMETER <- (nr - 1L) * (nc - 1L)
|
||||
PVAL <- pchisq(STATISTIC, PARAMETER, lower.tail = FALSE)
|
||||
|
||||
}
|
||||
else {
|
||||
if (length(dim(x)) > 2L)
|
||||
stop("invalid 'x'")
|
||||
if (length(x) == 1L)
|
||||
stop("'x' must at least have 2 elements")
|
||||
if (length(x) != length(p))
|
||||
stop("'x' and 'p' must have the same number of elements")
|
||||
if (any(p < 0))
|
||||
stop("probabilities must be non-negative.")
|
||||
if (abs(sum(p) - 1) > sqrt(.Machine$double.eps)) {
|
||||
if (rescale.p)
|
||||
p <- p / sum(p)
|
||||
else stop("probabilities must sum to 1.")
|
||||
}
|
||||
METHOD <- "G-test of goodness-of-fit (likelihood ratio test)"
|
||||
E <- n * p
|
||||
V <- n * p * (1 - p)
|
||||
STATISTIC <- 2 * sum(x * log(x / E)) # sum((x - E)^2/E) for chisq.test
|
||||
names(E) <- names(x)
|
||||
|
||||
PARAMETER <- length(x) - 1
|
||||
PVAL <- pchisq(STATISTIC, PARAMETER, lower.tail = FALSE)
|
||||
|
||||
}
|
||||
names(STATISTIC) <- "X-squared"
|
||||
names(PARAMETER) <- "df"
|
||||
if (any(E < 5) && is.finite(PARAMETER))
|
||||
warning("G-statistic approximation may be incorrect due to E < 5")
|
||||
|
||||
structure(list(statistic = STATISTIC, argument = PARAMETER,
|
||||
p.value = PVAL, method = METHOD, data.name = DNAME,
|
||||
observed = x, expected = E, residuals = (x - E) / sqrt(E),
|
||||
stdres = (x - E) / sqrt(V)), class = "htest")
|
||||
}
|
||||
-397
@@ -1,397 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' PCA Biplot with `ggplot2`
|
||||
#'
|
||||
#' Produces a `ggplot2` variant of a so-called [biplot](https://en.wikipedia.org/wiki/Biplot) for PCA (principal component analysis), but is more flexible and more appealing than the base \R [biplot()] function.
|
||||
#' @param x an object returned by [pca()], [prcomp()] or [princomp()]
|
||||
#' @inheritParams stats::biplot.prcomp
|
||||
#' @param labels an optional vector of labels for the observations. If set, the labels will be placed below their respective points. When using the [pca()] function as input for `x`, this will be determined automatically based on the attribute `non_numeric_cols`, see [pca()].
|
||||
#' @param labels_textsize the size of the text used for the labels
|
||||
#' @param labels_text_placement adjustment factor the placement of the variable names (`>=1` means further away from the arrow head)
|
||||
#' @param groups an optional vector of groups for the labels, with the same length as `labels`. If set, the points and labels will be coloured according to these groups. When using the [pca()] function as input for `x`, this will be determined automatically based on the attribute `non_numeric_cols`, see [pca()].
|
||||
#' @param ellipse a [logical] to indicate whether a normal data ellipse should be drawn for each group (set with `groups`)
|
||||
#' @param ellipse_prob statistical size of the ellipse in normal probability
|
||||
#' @param ellipse_size the size of the ellipse line
|
||||
#' @param ellipse_alpha the alpha (transparency) of the ellipse line
|
||||
#' @param points_size the size of the points
|
||||
#' @param points_alpha the alpha (transparency) of the points
|
||||
#' @param arrows a [logical] to indicate whether arrows should be drawn
|
||||
#' @param arrows_textsize the size of the text for variable names
|
||||
#' @param arrows_colour the colour of the arrow and their text
|
||||
#' @param arrows_size the size (thickness) of the arrow lines
|
||||
#' @param arrows_textsize the size of the text at the end of the arrows
|
||||
#' @param arrows_textangled a [logical] whether the text at the end of the arrows should be angled
|
||||
#' @param arrows_alpha the alpha (transparency) of the arrows and their text
|
||||
#' @param base_textsize the text size for all plot elements except the labels and arrows
|
||||
#' @param ... arguments passed on to functions
|
||||
#' @source The [ggplot_pca()] function is based on the `ggbiplot()` function from the `ggbiplot` package by Vince Vu, as found on GitHub: <https://github.com/vqv/ggbiplot> (retrieved: 2 March 2020, their latest commit: [`7325e88`](https://github.com/vqv/ggbiplot/commit/7325e880485bea4c07465a0304c470608fffb5d9); 12 February 2015).
|
||||
#'
|
||||
#' As per their GPL-2 licence that demands documentation of code changes, the changes made based on the source code were:
|
||||
#' 1. Rewritten code to remove the dependency on packages `plyr`, `scales` and `grid`
|
||||
#' 2. Parametrised more options, like arrow and ellipse settings
|
||||
#' 3. Hardened all input possibilities by defining the exact type of user input for every argument
|
||||
#' 4. Added total amount of explained variance as a caption in the plot
|
||||
#' 5. Cleaned all syntax based on the `lintr` package, fixed grammatical errors and added integrity checks
|
||||
#' 6. Updated documentation
|
||||
#' @details The colours for labels and points can be changed by adding another scale layer for colour, such as `scale_colour_viridis_d()` and `scale_colour_brewer()`.
|
||||
#' @rdname ggplot_pca
|
||||
#' @export
|
||||
#' @examples
|
||||
#' # `example_isolates` is a data set available in the AMR package.
|
||||
#' # See ?example_isolates.
|
||||
#'
|
||||
#' \donttest{
|
||||
#' if (require("dplyr")) {
|
||||
#' # calculate the resistance per group first
|
||||
#' resistance_data <- example_isolates %>%
|
||||
#' group_by(order = mo_order(mo), # group on anything, like order
|
||||
#' genus = mo_genus(mo)) %>% # and genus as we do here;
|
||||
#' filter(n() >= 30) %>% # filter on only 30 results per group
|
||||
#' summarise_if(is.rsi, resistance) # then get resistance of all drugs
|
||||
#'
|
||||
#' # now conduct PCA for certain antimicrobial agents
|
||||
#' pca_result <- resistance_data %>%
|
||||
#' pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)
|
||||
#'
|
||||
#' summary(pca_result)
|
||||
#'
|
||||
#' # old base R plotting method:
|
||||
#' biplot(pca_result)
|
||||
#' # new ggplot2 plotting method using this package:
|
||||
#' ggplot_pca(pca_result)
|
||||
#'
|
||||
#' if (require("ggplot2")) {
|
||||
#' ggplot_pca(pca_result) +
|
||||
#' scale_colour_viridis_d() +
|
||||
#' labs(title = "Title here")
|
||||
#' }
|
||||
#' }
|
||||
#' }
|
||||
ggplot_pca <- function(x,
|
||||
choices = 1:2,
|
||||
scale = 1,
|
||||
pc.biplot = TRUE,
|
||||
labels = NULL,
|
||||
labels_textsize = 3,
|
||||
labels_text_placement = 1.5,
|
||||
groups = NULL,
|
||||
ellipse = TRUE,
|
||||
ellipse_prob = 0.68,
|
||||
ellipse_size = 0.5,
|
||||
ellipse_alpha = 0.5,
|
||||
points_size = 2,
|
||||
points_alpha = 0.25,
|
||||
arrows = TRUE,
|
||||
arrows_colour = "darkblue",
|
||||
arrows_size = 0.5,
|
||||
arrows_textsize = 3,
|
||||
arrows_textangled = TRUE,
|
||||
arrows_alpha = 0.75,
|
||||
base_textsize = 10,
|
||||
...) {
|
||||
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(x, allow_class = c("prcomp", "princomp", "PCA", "lda"))
|
||||
meet_criteria(choices, allow_class = c("numeric", "integer"), has_length = 2, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(scale, allow_class = c("numeric", "integer", "logical"), has_length = 1)
|
||||
meet_criteria(pc.biplot, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(labels, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(labels_textsize, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(labels_text_placement, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(groups, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(ellipse, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(ellipse_prob, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(ellipse_size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(ellipse_alpha, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(points_size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(points_alpha, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(arrows, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(arrows_colour, allow_class = "character", has_length = 1)
|
||||
meet_criteria(arrows_size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(arrows_textsize, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(arrows_textangled, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(arrows_alpha, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(base_textsize, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
|
||||
calculations <- pca_calculations(pca_model = x,
|
||||
groups = groups,
|
||||
groups_missing = missing(groups),
|
||||
labels = labels,
|
||||
labels_missing = missing(labels),
|
||||
choices = choices,
|
||||
scale = scale,
|
||||
pc.biplot = pc.biplot,
|
||||
ellipse_prob = ellipse_prob,
|
||||
labels_text_placement = labels_text_placement)
|
||||
choices <- calculations$choices
|
||||
df.u <- calculations$df.u
|
||||
df.v <- calculations$df.v
|
||||
ell <- calculations$ell
|
||||
groups <- calculations$groups
|
||||
group_name <- calculations$group_name
|
||||
labels <- calculations$labels
|
||||
|
||||
# Append the proportion of explained variance to the axis labels
|
||||
if ((1 - as.integer(scale)) == 0) {
|
||||
u.axis.labs <- paste0("Standardised PC", choices)
|
||||
} else {
|
||||
u.axis.labs <- paste0("PC", choices)
|
||||
}
|
||||
u.axis.labs <- paste0(u.axis.labs,
|
||||
paste0("\n(explained var: ",
|
||||
percentage(x$sdev[choices] ^ 2 / sum(x$sdev ^ 2)),
|
||||
")"))
|
||||
|
||||
# Score Labels
|
||||
if (!is.null(labels)) {
|
||||
df.u$labels <- labels
|
||||
}
|
||||
|
||||
# Grouping variable
|
||||
if (!is.null(groups)) {
|
||||
df.u$groups <- groups
|
||||
}
|
||||
|
||||
# Base plot
|
||||
g <- ggplot2::ggplot(data = df.u,
|
||||
ggplot2::aes(x = xvar, y = yvar)) +
|
||||
ggplot2::xlab(u.axis.labs[1]) +
|
||||
ggplot2::ylab(u.axis.labs[2]) +
|
||||
ggplot2::expand_limits(x = c(-1.15, 1.15),
|
||||
y = c(-1.15, 1.15))
|
||||
|
||||
# Draw either labels or points
|
||||
if (!is.null(df.u$labels)) {
|
||||
if (!is.null(df.u$groups)) {
|
||||
g <- g + ggplot2::geom_point(ggplot2::aes(colour = groups),
|
||||
alpha = points_alpha,
|
||||
size = points_size) +
|
||||
ggplot2::geom_text(ggplot2::aes(label = labels, colour = groups),
|
||||
nudge_y = -0.05,
|
||||
size = labels_textsize) +
|
||||
ggplot2::labs(colour = group_name)
|
||||
} else {
|
||||
g <- g + ggplot2::geom_point(alpha = points_alpha,
|
||||
size = points_size) +
|
||||
ggplot2::geom_text(ggplot2::aes(label = labels),
|
||||
nudge_y = -0.05,
|
||||
size = labels_textsize)
|
||||
}
|
||||
} else {
|
||||
if (!is.null(df.u$groups)) {
|
||||
g <- g + ggplot2::geom_point(ggplot2::aes(colour = groups),
|
||||
alpha = points_alpha,
|
||||
size = points_size) +
|
||||
ggplot2::labs(colour = group_name)
|
||||
} else {
|
||||
g <- g + ggplot2::geom_point(alpha = points_alpha,
|
||||
size = points_size)
|
||||
}
|
||||
}
|
||||
|
||||
# Overlay a concentration ellipse if there are groups
|
||||
if (!is.null(df.u$groups) & !is.null(ell) & isTRUE(ellipse)) {
|
||||
g <- g + ggplot2::geom_path(data = ell,
|
||||
ggplot2::aes(colour = groups, group = groups),
|
||||
size = ellipse_size,
|
||||
alpha = points_alpha)
|
||||
}
|
||||
|
||||
# Label the variable axes
|
||||
if (arrows == TRUE) {
|
||||
g <- g + ggplot2::geom_segment(data = df.v,
|
||||
ggplot2::aes(x = 0, y = 0, xend = xvar, yend = yvar),
|
||||
arrow = ggplot2::arrow(length = ggplot2::unit(0.5, "picas"),
|
||||
angle = 20,
|
||||
ends = "last",
|
||||
type = "open"),
|
||||
colour = arrows_colour,
|
||||
size = arrows_size,
|
||||
alpha = arrows_alpha)
|
||||
if (arrows_textangled == TRUE) {
|
||||
g <- g + ggplot2::geom_text(data = df.v,
|
||||
ggplot2::aes(label = varname, x = xvar, y = yvar, angle = angle, hjust = hjust),
|
||||
colour = arrows_colour,
|
||||
size = arrows_textsize,
|
||||
alpha = arrows_alpha)
|
||||
} else {
|
||||
g <- g + ggplot2::geom_text(data = df.v,
|
||||
ggplot2::aes(label = varname, x = xvar, y = yvar, hjust = hjust),
|
||||
colour = arrows_colour,
|
||||
size = arrows_textsize,
|
||||
alpha = arrows_alpha)
|
||||
}
|
||||
}
|
||||
|
||||
# Add caption label about total explained variance
|
||||
g <- g + ggplot2::labs(caption = paste0("Total explained variance: ",
|
||||
percentage(sum(x$sdev[choices] ^ 2 / sum(x$sdev ^ 2)))))
|
||||
|
||||
# mark-up nicely
|
||||
g <- g + ggplot2::theme_minimal(base_size = base_textsize) +
|
||||
ggplot2::theme(panel.grid.major = ggplot2::element_line(colour = "grey85"),
|
||||
panel.grid.minor = ggplot2::element_blank(),
|
||||
# centre title and subtitle
|
||||
plot.title = ggplot2::element_text(hjust = 0.5),
|
||||
plot.subtitle = ggplot2::element_text(hjust = 0.5))
|
||||
|
||||
g
|
||||
}
|
||||
|
||||
#' @importFrom stats qchisq var
|
||||
pca_calculations <- function(pca_model,
|
||||
groups = NULL,
|
||||
groups_missing = TRUE,
|
||||
labels = NULL,
|
||||
labels_missing = TRUE,
|
||||
choices = 1:2,
|
||||
scale = 1,
|
||||
pc.biplot = TRUE,
|
||||
ellipse_prob = 0.68,
|
||||
labels_text_placement = 1.5) {
|
||||
|
||||
non_numeric_cols <- attributes(pca_model)$non_numeric_cols
|
||||
if (groups_missing) {
|
||||
groups <- tryCatch(non_numeric_cols[[1]],
|
||||
error = function(e) NULL)
|
||||
group_name <- tryCatch(colnames(non_numeric_cols[1]),
|
||||
error = function(e) NULL)
|
||||
}
|
||||
if (labels_missing) {
|
||||
labels <- tryCatch(non_numeric_cols[[2]],
|
||||
error = function(e) NULL)
|
||||
}
|
||||
if (!is.null(groups) & is.null(labels)) {
|
||||
# turn them around
|
||||
labels <- groups
|
||||
groups <- NULL
|
||||
group_name <- NULL
|
||||
}
|
||||
|
||||
# Recover the SVD
|
||||
if (inherits(pca_model, "prcomp")) {
|
||||
nobs.factor <- sqrt(nrow(pca_model$x) - 1)
|
||||
d <- pca_model$sdev
|
||||
u <- sweep(pca_model$x, 2, 1 / (d * nobs.factor), FUN = "*")
|
||||
v <- pca_model$rotation
|
||||
} else if (inherits(pca_model, "princomp")) {
|
||||
nobs.factor <- sqrt(pca_model$n.obs)
|
||||
d <- pca_model$sdev
|
||||
u <- sweep(pca_model$scores, 2, 1 / (d * nobs.factor), FUN = "*")
|
||||
v <- pca_model$loadings
|
||||
} else if (inherits(pca_model, "PCA")) {
|
||||
nobs.factor <- sqrt(nrow(pca_model$call$X))
|
||||
d <- unlist(sqrt(pca_model$eig)[1])
|
||||
u <- sweep(pca_model$ind$coord, 2, 1 / (d * nobs.factor), FUN = "*")
|
||||
v <- sweep(pca_model$var$coord, 2, sqrt(pca_model$eig[seq_len(ncol(pca_model$var$coord)), 1]), FUN = "/")
|
||||
} else if (inherits(pca_model, "lda")) {
|
||||
nobs.factor <- sqrt(pca_model$N)
|
||||
d <- pca_model$svd
|
||||
u <- predict(pca_model)$x / nobs.factor
|
||||
v <- pca_model$scaling
|
||||
} else {
|
||||
stop("Expected an object of class prcomp, princomp, PCA, or lda")
|
||||
}
|
||||
|
||||
# Scores
|
||||
choices <- pmin(choices, ncol(u))
|
||||
obs.scale <- 1 - as.integer(scale)
|
||||
df.u <- as.data.frame(sweep(u[, choices], 2, d[choices] ^ obs.scale, FUN = "*"),
|
||||
stringsAsFactors = FALSE)
|
||||
|
||||
# Directions
|
||||
v <- sweep(v, 2, d ^ as.integer(scale), FUN = "*")
|
||||
df.v <- as.data.frame(v[, choices],
|
||||
stringsAsFactors = FALSE)
|
||||
|
||||
names(df.u) <- c("xvar", "yvar")
|
||||
names(df.v) <- names(df.u)
|
||||
|
||||
if (isTRUE(pc.biplot)) {
|
||||
df.u <- df.u * nobs.factor
|
||||
}
|
||||
|
||||
# Scale the radius of the correlation circle so that it corresponds to
|
||||
# a data ellipse for the standardized PC scores
|
||||
circle_prob <- 0.69
|
||||
r <- sqrt(qchisq(circle_prob, df = 2)) * prod(colMeans(df.u ^ 2)) ^ (0.25)
|
||||
|
||||
# Scale directions
|
||||
v.scale <- rowSums(v ^ 2)
|
||||
df.v <- r * df.v / sqrt(max(v.scale))
|
||||
|
||||
# Grouping variable
|
||||
if (!is.null(groups)) {
|
||||
df.u$groups <- groups
|
||||
}
|
||||
|
||||
df.v$varname <- rownames(v)
|
||||
|
||||
# Variables for text label placement
|
||||
df.v$angle <- with(df.v, (180 / pi) * atan(yvar / xvar))
|
||||
df.v$hjust <- with(df.v, (1 - labels_text_placement * sign(xvar)) / 2)
|
||||
|
||||
if (!is.null(df.u$groups)) {
|
||||
theta <- c(seq(-pi, pi, length = 50), seq(pi, -pi, length = 50))
|
||||
circle <- cbind(cos(theta), sin(theta))
|
||||
|
||||
df.groups <- lapply(unique(df.u$groups), function(g, df = df.u) {
|
||||
x <- df[which(df$groups == g), , drop = FALSE]
|
||||
if (nrow(x) <= 2) {
|
||||
return(data.frame(X1 = numeric(0),
|
||||
X2 = numeric(0),
|
||||
groups = character(0),
|
||||
stringsAsFactors = FALSE))
|
||||
}
|
||||
sigma <- var(cbind(x$xvar, x$yvar))
|
||||
mu <- c(mean(x$xvar), mean(x$yvar))
|
||||
ed <- sqrt(qchisq(ellipse_prob, df = 2))
|
||||
data.frame(sweep(circle %*% chol(sigma) * ed,
|
||||
MARGIN = 2,
|
||||
STATS = mu,
|
||||
FUN = "+"),
|
||||
groups = x$groups[1],
|
||||
stringsAsFactors = FALSE)
|
||||
})
|
||||
ell <- do.call(rbind, df.groups)
|
||||
if (NROW(ell) == 0) {
|
||||
ell <- NULL
|
||||
} else {
|
||||
names(ell)[1:2] <- c("xvar", "yvar")
|
||||
}
|
||||
} else {
|
||||
ell <- NULL
|
||||
}
|
||||
|
||||
list(choices = choices,
|
||||
df.u = df.u,
|
||||
df.v = df.v,
|
||||
ell = ell,
|
||||
groups = groups,
|
||||
group_name = group_name,
|
||||
labels = labels
|
||||
)
|
||||
}
|
||||
-484
@@ -1,484 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' AMR Plots with `ggplot2`
|
||||
#'
|
||||
#' Use these functions to create bar plots for AMR data analysis. All functions rely on [ggplot2][ggplot2::ggplot()] functions.
|
||||
#' @param data a [data.frame] with column(s) of class [`rsi`] (see [as.rsi()])
|
||||
#' @param position position adjustment of bars, either `"fill"`, `"stack"` or `"dodge"`
|
||||
#' @param x variable to show on x axis, either `"antibiotic"` (default) or `"interpretation"` or a grouping variable
|
||||
#' @param fill variable to categorise using the plots legend, either `"antibiotic"` (default) or `"interpretation"` or a grouping variable
|
||||
#' @param breaks a [numeric] vector of positions
|
||||
#' @param limits a [numeric] vector of length two providing limits of the scale, use `NA` to refer to the existing minimum or maximum
|
||||
#' @param facet variable to split plots by, either `"interpretation"` (default) or `"antibiotic"` or a grouping variable
|
||||
#' @inheritParams proportion
|
||||
#' @param nrow (when using `facet`) number of rows
|
||||
#' @param colours a named vactor with colour to be used for filling. The default colours are colour-blind friendly.
|
||||
#' @param aesthetics aesthetics to apply the colours to, defaults to "fill" but can also be (a combination of) "alpha", "colour", "fill", "linetype", "shape" or "size"
|
||||
#' @param datalabels show datalabels using [labels_rsi_count()]
|
||||
#' @param datalabels.size size of the datalabels
|
||||
#' @param datalabels.colour colour of the datalabels
|
||||
#' @param title text to show as title of the plot
|
||||
#' @param subtitle text to show as subtitle of the plot
|
||||
#' @param caption text to show as caption of the plot
|
||||
#' @param x.title text to show as x axis description
|
||||
#' @param y.title text to show as y axis description
|
||||
#' @param ... other arguments passed on to [geom_rsi()] or, in case of [scale_rsi_colours()], named values to set colours. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red. See *Examples*.
|
||||
#' @details At default, the names of antibiotics will be shown on the plots using [ab_name()]. This can be set with the `translate_ab` argument. See [count_df()].
|
||||
#'
|
||||
#' ## The Functions
|
||||
#' [geom_rsi()] will take any variable from the data that has an [`rsi`] class (created with [as.rsi()]) using [rsi_df()] and will plot bars with the percentage R, I and S. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.
|
||||
#'
|
||||
#' [facet_rsi()] creates 2d plots (at default based on S/I/R) using [ggplot2::facet_wrap()].
|
||||
#'
|
||||
#' [scale_y_percent()] transforms the y axis to a 0 to 100% range using [ggplot2::scale_y_continuous()].
|
||||
#'
|
||||
#' [scale_rsi_colours()] sets colours to the bars (green for S, yellow for I, and red for R). with multilingual support. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red.
|
||||
#'
|
||||
#' [theme_rsi()] is a [ggplot2 theme][[ggplot2::theme()] with minimal distraction.
|
||||
#'
|
||||
#' [labels_rsi_count()] print datalabels on the bars with percentage and amount of isolates using [ggplot2::geom_text()].
|
||||
#'
|
||||
#' [ggplot_rsi()] is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (`%>%`). See *Examples*.
|
||||
#' @rdname ggplot_rsi
|
||||
#' @export
|
||||
#' @examples
|
||||
#' \donttest{
|
||||
#' if (require("ggplot2") & require("dplyr")) {
|
||||
#'
|
||||
#' # get antimicrobial results for drugs against a UTI:
|
||||
#' ggplot(example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)) +
|
||||
#' geom_rsi()
|
||||
#'
|
||||
#' # prettify the plot using some additional functions:
|
||||
#' df <- example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)
|
||||
#' ggplot(df) +
|
||||
#' geom_rsi() +
|
||||
#' scale_y_percent() +
|
||||
#' scale_rsi_colours() +
|
||||
#' labels_rsi_count() +
|
||||
#' theme_rsi()
|
||||
#'
|
||||
#' # or better yet, simplify this using the wrapper function - a single command:
|
||||
#' example_isolates %>%
|
||||
#' select(AMX, NIT, FOS, TMP, CIP) %>%
|
||||
#' ggplot_rsi()
|
||||
#'
|
||||
#' # get only proportions and no counts:
|
||||
#' example_isolates %>%
|
||||
#' select(AMX, NIT, FOS, TMP, CIP) %>%
|
||||
#' ggplot_rsi(datalabels = FALSE)
|
||||
#'
|
||||
#' # add other ggplot2 arguments as you like:
|
||||
#' example_isolates %>%
|
||||
#' select(AMX, NIT, FOS, TMP, CIP) %>%
|
||||
#' ggplot_rsi(width = 0.5,
|
||||
#' colour = "black",
|
||||
#' size = 1,
|
||||
#' linetype = 2,
|
||||
#' alpha = 0.25)
|
||||
#'
|
||||
#' # you can alter the colours with colour names:
|
||||
#' example_isolates %>%
|
||||
#' select(AMX) %>%
|
||||
#' ggplot_rsi(colours = c(SI = "yellow"))
|
||||
#'
|
||||
#' # but you can also use the built-in colour-blind friendly colours for
|
||||
#' # your plots, where "S" is green, "I" is yellow and "R" is red:
|
||||
#' data.frame(x = c("Value1", "Value2", "Value3"),
|
||||
#' y = c(1, 2, 3),
|
||||
#' z = c("Value4", "Value5", "Value6")) %>%
|
||||
#' ggplot() +
|
||||
#' geom_col(aes(x = x, y = y, fill = z)) +
|
||||
#' scale_rsi_colours(Value4 = "S", Value5 = "I", Value6 = "R")
|
||||
#'
|
||||
#' # resistance of ciprofloxacine per age group
|
||||
#' example_isolates %>%
|
||||
#' mutate(first_isolate = first_isolate()) %>%
|
||||
#' filter(first_isolate == TRUE,
|
||||
#' mo == as.mo("E. coli")) %>%
|
||||
#' # age_groups() is also a function in this AMR package:
|
||||
#' group_by(age_group = age_groups(age)) %>%
|
||||
#' select(age_group, CIP) %>%
|
||||
#' ggplot_rsi(x = "age_group")
|
||||
#'
|
||||
#' # a shorter version which also adjusts data label colours:
|
||||
#' example_isolates %>%
|
||||
#' select(AMX, NIT, FOS, TMP, CIP) %>%
|
||||
#' ggplot_rsi(colours = FALSE)
|
||||
#'
|
||||
#'
|
||||
#' # it also supports groups (don't forget to use the group var on `x` or `facet`):
|
||||
#' example_isolates %>%
|
||||
#' filter(mo_is_gram_negative()) %>%
|
||||
#' # select only UTI-specific drugs
|
||||
#' select(hospital_id, AMX, NIT, FOS, TMP, CIP) %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' ggplot_rsi(x = "hospital_id",
|
||||
#' facet = "antibiotic",
|
||||
#' nrow = 1,
|
||||
#' title = "AMR of Anti-UTI Drugs Per Hospital",
|
||||
#' x.title = "Hospital",
|
||||
#' datalabels = FALSE)
|
||||
#' }
|
||||
#' }
|
||||
ggplot_rsi <- function(data,
|
||||
position = NULL,
|
||||
x = "antibiotic",
|
||||
fill = "interpretation",
|
||||
# params = list(),
|
||||
facet = NULL,
|
||||
breaks = seq(0, 1, 0.1),
|
||||
limits = NULL,
|
||||
translate_ab = "name",
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE,
|
||||
minimum = 30,
|
||||
language = get_AMR_locale(),
|
||||
nrow = NULL,
|
||||
colours = c(S = "#3CAEA3",
|
||||
SI = "#3CAEA3",
|
||||
I = "#F6D55C",
|
||||
IR = "#ED553B",
|
||||
R = "#ED553B"),
|
||||
datalabels = TRUE,
|
||||
datalabels.size = 2.5,
|
||||
datalabels.colour = "grey15",
|
||||
title = NULL,
|
||||
subtitle = NULL,
|
||||
caption = NULL,
|
||||
x.title = "Antimicrobial",
|
||||
y.title = "Proportion",
|
||||
...) {
|
||||
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(data, allow_class = "data.frame", contains_column_class = "rsi")
|
||||
meet_criteria(position, allow_class = "character", has_length = 1, is_in = c("fill", "stack", "dodge"), allow_NULL = TRUE)
|
||||
meet_criteria(x, allow_class = "character", has_length = 1)
|
||||
meet_criteria(fill, allow_class = "character", has_length = 1)
|
||||
meet_criteria(facet, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(breaks, allow_class = c("numeric", "integer"))
|
||||
meet_criteria(limits, allow_class = c("numeric", "integer"), has_length = 2, allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
|
||||
meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(combine_IR, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(nrow, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(colours, allow_class = c("character", "logical"))
|
||||
meet_criteria(datalabels, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(datalabels.size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(datalabels.colour, allow_class = "character", has_length = 1)
|
||||
meet_criteria(title, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(subtitle, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(caption, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(x.title, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(y.title, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
|
||||
# we work with aes_string later on
|
||||
x_deparse <- deparse(substitute(x))
|
||||
if (x_deparse != "x") {
|
||||
x <- x_deparse
|
||||
}
|
||||
if (x %like% '".*"') {
|
||||
x <- substr(x, 2, nchar(x) - 1)
|
||||
}
|
||||
facet_deparse <- deparse(substitute(facet))
|
||||
if (facet_deparse != "facet") {
|
||||
facet <- facet_deparse
|
||||
}
|
||||
if (facet %like% '".*"') {
|
||||
facet <- substr(facet, 2, nchar(facet) - 1)
|
||||
}
|
||||
if (facet %in% c("NULL", "")) {
|
||||
facet <- NULL
|
||||
}
|
||||
|
||||
if (is.null(position)) {
|
||||
position <- "fill"
|
||||
}
|
||||
|
||||
p <- ggplot2::ggplot(data = data) +
|
||||
geom_rsi(position = position, x = x, fill = fill, translate_ab = translate_ab,
|
||||
minimum = minimum, language = language,
|
||||
combine_SI = combine_SI, combine_IR = combine_IR, ...) +
|
||||
theme_rsi()
|
||||
|
||||
if (fill == "interpretation") {
|
||||
p <- p + scale_rsi_colours(colours = colours)
|
||||
}
|
||||
|
||||
if (identical(position, "fill")) {
|
||||
# proportions, so use y scale with percentage
|
||||
p <- p + scale_y_percent(breaks = breaks, limits = limits)
|
||||
}
|
||||
|
||||
if (datalabels == TRUE) {
|
||||
p <- p + labels_rsi_count(position = position,
|
||||
x = x,
|
||||
translate_ab = translate_ab,
|
||||
minimum = minimum,
|
||||
language = language,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR,
|
||||
datalabels.size = datalabels.size,
|
||||
datalabels.colour = datalabels.colour)
|
||||
}
|
||||
|
||||
if (!is.null(facet)) {
|
||||
p <- p + facet_rsi(facet = facet, nrow = nrow)
|
||||
}
|
||||
|
||||
p <- p + ggplot2::labs(title = title,
|
||||
subtitle = subtitle,
|
||||
caption = caption,
|
||||
x = x.title,
|
||||
y = y.title)
|
||||
|
||||
p
|
||||
}
|
||||
|
||||
#' @rdname ggplot_rsi
|
||||
#' @export
|
||||
geom_rsi <- function(position = NULL,
|
||||
x = c("antibiotic", "interpretation"),
|
||||
fill = "interpretation",
|
||||
translate_ab = "name",
|
||||
minimum = 30,
|
||||
language = get_AMR_locale(),
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE,
|
||||
...) {
|
||||
x <- x[1]
|
||||
stop_ifnot_installed("ggplot2")
|
||||
stop_if(is.data.frame(position), "`position` is invalid. Did you accidentally use '%>%' instead of '+'?")
|
||||
meet_criteria(position, allow_class = "character", has_length = 1, is_in = c("fill", "stack", "dodge"), allow_NULL = TRUE)
|
||||
meet_criteria(x, allow_class = "character", has_length = 1)
|
||||
meet_criteria(fill, allow_class = "character", has_length = 1)
|
||||
meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
|
||||
meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(combine_IR, allow_class = "logical", has_length = 1)
|
||||
|
||||
y <- "value"
|
||||
if (missing(position) | is.null(position)) {
|
||||
position <- "fill"
|
||||
}
|
||||
|
||||
if (identical(position, "fill")) {
|
||||
position <- ggplot2::position_fill(vjust = 0.5, reverse = TRUE)
|
||||
}
|
||||
|
||||
# we work with aes_string later on
|
||||
x_deparse <- deparse(substitute(x))
|
||||
if (x_deparse != "x") {
|
||||
x <- x_deparse
|
||||
}
|
||||
if (x %like% '".*"') {
|
||||
x <- substr(x, 2, nchar(x) - 1)
|
||||
}
|
||||
|
||||
if (tolower(x) %in% tolower(c("ab", "abx", "antibiotics"))) {
|
||||
x <- "antibiotic"
|
||||
} else if (tolower(x) %in% tolower(c("SIR", "RSI", "interpretations", "result"))) {
|
||||
x <- "interpretation"
|
||||
}
|
||||
|
||||
ggplot2::geom_col(
|
||||
data = function(x) {
|
||||
rsi_df(data = x,
|
||||
translate_ab = translate_ab,
|
||||
language = language,
|
||||
minimum = minimum,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR)
|
||||
},
|
||||
mapping = ggplot2::aes_string(x = x, y = y, fill = fill),
|
||||
position = position,
|
||||
...
|
||||
)
|
||||
}
|
||||
|
||||
#' @rdname ggplot_rsi
|
||||
#' @export
|
||||
facet_rsi <- function(facet = c("interpretation", "antibiotic"), nrow = NULL) {
|
||||
facet <- facet[1]
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(facet, allow_class = "character", has_length = 1)
|
||||
meet_criteria(nrow, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
|
||||
|
||||
# we work with aes_string later on
|
||||
facet_deparse <- deparse(substitute(facet))
|
||||
if (facet_deparse != "facet") {
|
||||
facet <- facet_deparse
|
||||
}
|
||||
if (facet %like% '".*"') {
|
||||
facet <- substr(facet, 2, nchar(facet) - 1)
|
||||
}
|
||||
|
||||
if (tolower(facet) %in% tolower(c("SIR", "RSI", "interpretations", "result"))) {
|
||||
facet <- "interpretation"
|
||||
} else if (tolower(facet) %in% tolower(c("ab", "abx", "antibiotics"))) {
|
||||
facet <- "antibiotic"
|
||||
}
|
||||
|
||||
ggplot2::facet_wrap(facets = facet, scales = "free_x", nrow = nrow)
|
||||
}
|
||||
|
||||
#' @rdname ggplot_rsi
|
||||
#' @export
|
||||
scale_y_percent <- function(breaks = seq(0, 1, 0.1), limits = NULL) {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(breaks, allow_class = c("numeric", "integer"))
|
||||
meet_criteria(limits, allow_class = c("numeric", "integer"), has_length = 2, allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
if (all(breaks[breaks != 0] > 1)) {
|
||||
breaks <- breaks / 100
|
||||
}
|
||||
ggplot2::scale_y_continuous(breaks = breaks,
|
||||
labels = percentage(breaks),
|
||||
limits = limits)
|
||||
}
|
||||
|
||||
#' @rdname ggplot_rsi
|
||||
#' @export
|
||||
scale_rsi_colours <- function(...,
|
||||
aesthetics = "fill") {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(aesthetics, allow_class = "character", is_in = c("alpha", "colour", "color", "fill", "linetype", "shape", "size"))
|
||||
# behaviour until AMR pkg v1.5.0 and also when coming from ggplot_rsi()
|
||||
if ("colours" %in% names(list(...))) {
|
||||
original_cols <- c(S = "#3CAEA3",
|
||||
SI = "#3CAEA3",
|
||||
I = "#F6D55C",
|
||||
IR = "#ED553B",
|
||||
R = "#ED553B")
|
||||
colours <- replace(original_cols, names(list(...)$colours), list(...)$colours)
|
||||
# limits = force is needed in ggplot2 3.3.4 and 3.3.5, see here;
|
||||
# https://github.com/tidyverse/ggplot2/issues/4511#issuecomment-866185530
|
||||
return(ggplot2::scale_fill_manual(values = colours, limits = force))
|
||||
}
|
||||
if (identical(unlist(list(...)), FALSE)) {
|
||||
return(invisible())
|
||||
}
|
||||
|
||||
names_susceptible <- c("S", "SI", "IS", "S+I", "I+S", "susceptible", "Susceptible",
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible"),
|
||||
"replacement", drop = TRUE]))
|
||||
names_incr_exposure <- c("I", "intermediate", "increased exposure", "incr. exposure",
|
||||
"Increased exposure", "Incr. exposure", "Susceptible, incr. exp.",
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Intermediate"),
|
||||
"replacement", drop = TRUE]),
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible, incr. exp."),
|
||||
"replacement", drop = TRUE]))
|
||||
names_resistant <- c("R", "IR", "RI", "R+I", "I+R", "resistant", "Resistant",
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Resistant"),
|
||||
"replacement", drop = TRUE]))
|
||||
|
||||
susceptible <- rep("#3CAEA3", length(names_susceptible))
|
||||
names(susceptible) <- names_susceptible
|
||||
incr_exposure <- rep("#F6D55C", length(names_incr_exposure))
|
||||
names(incr_exposure) <- names_incr_exposure
|
||||
resistant <- rep("#ED553B", length(names_resistant))
|
||||
names(resistant) <- names_resistant
|
||||
|
||||
original_cols = c(susceptible, incr_exposure, resistant)
|
||||
dots <- c(...)
|
||||
# replace S, I, R as colours: scale_rsi_colours(mydatavalue = "S")
|
||||
dots[dots == "S"] <- "#3CAEA3"
|
||||
dots[dots == "I"] <- "#F6D55C"
|
||||
dots[dots == "R"] <- "#ED553B"
|
||||
cols <- replace(original_cols, names(dots), dots)
|
||||
# limits = force is needed in ggplot2 3.3.4 and 3.3.5, see here;
|
||||
# https://github.com/tidyverse/ggplot2/issues/4511#issuecomment-866185530
|
||||
ggplot2::scale_discrete_manual(aesthetics = aesthetics, values = cols, limits = force)
|
||||
}
|
||||
|
||||
#' @rdname ggplot_rsi
|
||||
#' @export
|
||||
theme_rsi <- function() {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
ggplot2::theme_minimal(base_size = 10) +
|
||||
ggplot2::theme(panel.grid.major.x = ggplot2::element_blank(),
|
||||
panel.grid.minor = ggplot2::element_blank(),
|
||||
panel.grid.major.y = ggplot2::element_line(colour = "grey75"),
|
||||
# center title and subtitle
|
||||
plot.title = ggplot2::element_text(hjust = 0.5),
|
||||
plot.subtitle = ggplot2::element_text(hjust = 0.5))
|
||||
}
|
||||
|
||||
#' @rdname ggplot_rsi
|
||||
#' @export
|
||||
labels_rsi_count <- function(position = NULL,
|
||||
x = "antibiotic",
|
||||
translate_ab = "name",
|
||||
minimum = 30,
|
||||
language = get_AMR_locale(),
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE,
|
||||
datalabels.size = 3,
|
||||
datalabels.colour = "grey15") {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(position, allow_class = "character", has_length = 1, is_in = c("fill", "stack", "dodge"), allow_NULL = TRUE)
|
||||
meet_criteria(x, allow_class = "character", has_length = 1)
|
||||
meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
|
||||
meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(combine_IR, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(datalabels.size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(datalabels.colour, allow_class = "character", has_length = 1)
|
||||
|
||||
if (is.null(position)) {
|
||||
position <- "fill"
|
||||
}
|
||||
if (identical(position, "fill")) {
|
||||
position <- ggplot2::position_fill(vjust = 0.5, reverse = TRUE)
|
||||
}
|
||||
x_name <- x
|
||||
ggplot2::geom_text(mapping = ggplot2::aes_string(label = "lbl",
|
||||
x = x,
|
||||
y = "value"),
|
||||
position = position,
|
||||
inherit.aes = FALSE,
|
||||
size = datalabels.size,
|
||||
colour = datalabels.colour,
|
||||
lineheight = 0.75,
|
||||
data = function(x) {
|
||||
transformed <- rsi_df(data = x,
|
||||
translate_ab = translate_ab,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR,
|
||||
minimum = minimum,
|
||||
language = language)
|
||||
transformed$gr <- transformed[, x_name, drop = TRUE]
|
||||
transformed %pm>%
|
||||
pm_group_by(gr) %pm>%
|
||||
pm_mutate(lbl = paste0("n=", isolates)) %pm>%
|
||||
pm_ungroup() %pm>%
|
||||
pm_select(-gr)
|
||||
})
|
||||
}
|
||||
@@ -1,339 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Guess Antibiotic Column
|
||||
#'
|
||||
#' This tries to find a column name in a data set based on information from the [antibiotics] data set. Also supports WHONET abbreviations.
|
||||
#' @param x a [data.frame]
|
||||
#' @param search_string a text to search `x` for, will be checked with [as.ab()] if this value is not a column in `x`
|
||||
#' @param verbose a [logical] to indicate whether additional info should be printed
|
||||
#' @param only_rsi_columns a [logical] to indicate whether only antibiotic columns must be detected that were transformed to class `<rsi>` (see [as.rsi()]) on beforehand (defaults to `FALSE`)
|
||||
#' @details You can look for an antibiotic (trade) name or abbreviation and it will search `x` and the [antibiotics] data set for any column containing a name or code of that antibiotic. **Longer columns names take precedence over shorter column names.**
|
||||
#' @return A column name of `x`, or `NULL` when no result is found.
|
||||
#' @export
|
||||
#' @examples
|
||||
#' df <- data.frame(amox = "S",
|
||||
#' tetr = "R")
|
||||
#'
|
||||
#' guess_ab_col(df, "amoxicillin")
|
||||
#' # [1] "amox"
|
||||
#' guess_ab_col(df, "J01AA07") # ATC code of tetracycline
|
||||
#' # [1] "tetr"
|
||||
#'
|
||||
#' guess_ab_col(df, "J01AA07", verbose = TRUE)
|
||||
#' # NOTE: Using column 'tetr' as input for J01AA07 (tetracycline).
|
||||
#' # [1] "tetr"
|
||||
#'
|
||||
#' # WHONET codes
|
||||
#' df <- data.frame(AMP_ND10 = "R",
|
||||
#' AMC_ED20 = "S")
|
||||
#' guess_ab_col(df, "ampicillin")
|
||||
#' # [1] "AMP_ND10"
|
||||
#' guess_ab_col(df, "J01CR02")
|
||||
#' # [1] "AMC_ED20"
|
||||
#' guess_ab_col(df, as.ab("augmentin"))
|
||||
#' # [1] "AMC_ED20"
|
||||
#'
|
||||
#' # Longer names take precendence:
|
||||
#' df <- data.frame(AMP_ED2 = "S",
|
||||
#' AMP_ED20 = "S")
|
||||
#' guess_ab_col(df, "ampicillin")
|
||||
#' # [1] "AMP_ED20"
|
||||
guess_ab_col <- function(x = NULL, search_string = NULL, verbose = FALSE, only_rsi_columns = FALSE) {
|
||||
meet_criteria(x, allow_class = "data.frame", allow_NULL = TRUE)
|
||||
meet_criteria(search_string, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(verbose, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
|
||||
if (is.null(x) & is.null(search_string)) {
|
||||
return(as.name("guess_ab_col"))
|
||||
} else {
|
||||
meet_criteria(search_string, allow_class = "character", has_length = 1, allow_NULL = FALSE)
|
||||
}
|
||||
|
||||
all_found <- get_column_abx(x, info = verbose, only_rsi_columns = only_rsi_columns,
|
||||
verbose = verbose, fn = "guess_ab_col")
|
||||
search_string.ab <- suppressWarnings(as.ab(search_string))
|
||||
ab_result <- unname(all_found[names(all_found) == search_string.ab])
|
||||
|
||||
if (length(ab_result) == 0) {
|
||||
if (verbose == TRUE) {
|
||||
message_("No column found as input for ", search_string,
|
||||
" (", ab_name(search_string, language = NULL, tolower = TRUE), ").",
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
}
|
||||
return(NULL)
|
||||
} else {
|
||||
if (verbose == TRUE) {
|
||||
message_("Using column '", font_bold(ab_result), "' as input for ", search_string,
|
||||
" (", ab_name(search_string, language = NULL, tolower = TRUE), ").")
|
||||
}
|
||||
return(ab_result)
|
||||
}
|
||||
}
|
||||
|
||||
get_column_abx <- function(x,
|
||||
...,
|
||||
soft_dependencies = NULL,
|
||||
hard_dependencies = NULL,
|
||||
verbose = FALSE,
|
||||
info = TRUE,
|
||||
only_rsi_columns = FALSE,
|
||||
sort = TRUE,
|
||||
reuse_previous_result = TRUE,
|
||||
fn = NULL) {
|
||||
# check if retrieved before, then get it from package environment
|
||||
if (isTRUE(reuse_previous_result) && identical(unique_call_id(entire_session = FALSE,
|
||||
match_fn = fn),
|
||||
pkg_env$get_column_abx.call)) {
|
||||
# so within the same call, within the same environment, we got here again.
|
||||
# but we could've come from another function within the same call, so now only check the columns that changed
|
||||
|
||||
# first remove the columns that are not existing anymore
|
||||
previous <- pkg_env$get_column_abx.out
|
||||
current <- previous[previous %in% colnames(x)]
|
||||
|
||||
# then compare columns in current call with columns in original call
|
||||
new_cols <- colnames(x)[!colnames(x) %in% pkg_env$get_column_abx.checked_cols]
|
||||
if (length(new_cols) > 0) {
|
||||
# these columns did not exist in the last call, so add them
|
||||
new_cols_rsi <- get_column_abx(x[, new_cols, drop = FALSE], reuse_previous_result = FALSE, info = FALSE, sort = FALSE)
|
||||
current <- c(current, new_cols_rsi)
|
||||
# order according to columns in current call
|
||||
current <- current[match(colnames(x)[colnames(x) %in% current], current)]
|
||||
}
|
||||
|
||||
# update pkg environment to improve speed on next run
|
||||
pkg_env$get_column_abx.out <- current
|
||||
pkg_env$get_column_abx.checked_cols <- colnames(x)
|
||||
|
||||
# and return right values
|
||||
return(pkg_env$get_column_abx.out)
|
||||
}
|
||||
|
||||
meet_criteria(x, allow_class = "data.frame")
|
||||
meet_criteria(soft_dependencies, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(hard_dependencies, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(verbose, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(info, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(sort, allow_class = "logical", has_length = 1)
|
||||
|
||||
if (info == TRUE) {
|
||||
message_("Auto-guessing columns suitable for analysis", appendLF = FALSE, as_note = FALSE)
|
||||
}
|
||||
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
||||
x.bak <- x
|
||||
if (only_rsi_columns == TRUE) {
|
||||
x <- x[, which(is.rsi(x)), drop = FALSE]
|
||||
}
|
||||
|
||||
if (NROW(x) > 10000) {
|
||||
# only test maximum of 10,000 values per column
|
||||
if (info == TRUE) {
|
||||
message_(" (using only ", font_bold("the first 10,000 rows"), ")...",
|
||||
appendLF = FALSE,
|
||||
as_note = FALSE)
|
||||
}
|
||||
x <- x[1:10000, , drop = FALSE]
|
||||
} else if (info == TRUE) {
|
||||
message_("...", appendLF = FALSE, as_note = FALSE)
|
||||
}
|
||||
|
||||
# only check columns that are a valid AB code, ATC code, name, abbreviation or synonym,
|
||||
# or already have the <rsi> class (as.rsi)
|
||||
# and that they have no more than 50% invalid values
|
||||
vectr_antibiotics <- unlist(AB_lookup$generalised_all)
|
||||
vectr_antibiotics <- vectr_antibiotics[!is.na(vectr_antibiotics) & nchar(vectr_antibiotics) >= 3]
|
||||
x_columns <- vapply(FUN.VALUE = character(1),
|
||||
colnames(x),
|
||||
function(col, df = x) {
|
||||
if (generalise_antibiotic_name(col) %in% vectr_antibiotics ||
|
||||
is.rsi(x[, col, drop = TRUE]) ||
|
||||
is.rsi.eligible(x[, col, drop = TRUE], threshold = 0.5)
|
||||
) {
|
||||
return(col)
|
||||
} else {
|
||||
return(NA_character_)
|
||||
}
|
||||
}, USE.NAMES = FALSE)
|
||||
|
||||
x_columns <- x_columns[!is.na(x_columns)]
|
||||
x <- x[, x_columns, drop = FALSE] # without drop = FALSE, x will become a vector when x_columns is length 1
|
||||
df_trans <- data.frame(colnames = colnames(x),
|
||||
abcode = suppressWarnings(as.ab(colnames(x), info = FALSE)),
|
||||
stringsAsFactors = FALSE)
|
||||
df_trans <- df_trans[!is.na(df_trans$abcode), , drop = FALSE]
|
||||
out <- as.character(df_trans$colnames)
|
||||
names(out) <- df_trans$abcode
|
||||
|
||||
# add from self-defined dots (...):
|
||||
# such as get_column_abx(example_isolates %>% rename(thisone = AMX), amox = "thisone")
|
||||
all_okay <- TRUE
|
||||
dots <- list(...)
|
||||
# remove data.frames, since this is also used running `eucast_rules(eucast_rules_df = df)`
|
||||
dots <- dots[!vapply(FUN.VALUE = logical(1), dots, is.data.frame)]
|
||||
if (length(dots) > 0) {
|
||||
newnames <- suppressWarnings(as.ab(names(dots), info = FALSE))
|
||||
if (any(is.na(newnames))) {
|
||||
if (info == TRUE) {
|
||||
message_(" WARNING", add_fn = list(font_yellow, font_bold), as_note = FALSE)
|
||||
}
|
||||
warning_("Invalid antibiotic reference(s): ", vector_and(names(dots)[is.na(newnames)], quotes = FALSE),
|
||||
call = FALSE,
|
||||
immediate = TRUE)
|
||||
all_okay <- FALSE
|
||||
}
|
||||
unexisting_cols <- which(!vapply(FUN.VALUE = logical(1), dots, function(col) all(col %in% x_columns)))
|
||||
if (length(unexisting_cols) > 0) {
|
||||
if (info == TRUE) {
|
||||
message_(" ERROR", add_fn = list(font_red, font_bold), as_note = FALSE)
|
||||
}
|
||||
stop_("Column(s) not found: ", vector_and(unlist(dots[[unexisting_cols]]), quotes = FALSE),
|
||||
call = FALSE)
|
||||
all_okay <- FALSE
|
||||
}
|
||||
# turn all NULLs to NAs
|
||||
dots <- unlist(lapply(dots, function(dot) if (is.null(dot)) NA else dot))
|
||||
names(dots) <- newnames
|
||||
dots <- dots[!is.na(names(dots))]
|
||||
# merge, but overwrite automatically determined ones by 'dots'
|
||||
out <- c(out[!out %in% dots & !names(out) %in% names(dots)], dots)
|
||||
# delete NAs, this will make e.g. eucast_rules(... TMP = NULL) work to prevent TMP from being used
|
||||
out <- out[!is.na(out)]
|
||||
}
|
||||
|
||||
if (length(out) == 0) {
|
||||
if (info == TRUE & all_okay == TRUE) {
|
||||
message_("No columns found.")
|
||||
}
|
||||
pkg_env$get_column_abx.call <- unique_call_id(entire_session = FALSE, match_fn = fn)
|
||||
pkg_env$get_column_abx.checked_cols <- colnames(x.bak)
|
||||
pkg_env$get_column_abx.out <- out
|
||||
return(out)
|
||||
}
|
||||
|
||||
# sort on name
|
||||
if (sort == TRUE) {
|
||||
out <- out[order(names(out), out)]
|
||||
}
|
||||
# only keep the first hits, no duplicates
|
||||
duplicates <- c(out[duplicated(names(out))], out[duplicated(unname(out))])
|
||||
if (length(duplicates) > 0) {
|
||||
all_okay <- FALSE
|
||||
}
|
||||
|
||||
if (info == TRUE) {
|
||||
if (all_okay == TRUE) {
|
||||
message_(" OK.", add_fn = list(font_green, font_bold), as_note = FALSE)
|
||||
} else {
|
||||
message_(" WARNING.", add_fn = list(font_yellow, font_bold), as_note = FALSE)
|
||||
}
|
||||
for (i in seq_len(length(out))) {
|
||||
if (verbose == TRUE & !names(out[i]) %in% names(duplicates)) {
|
||||
message_("Using column '", font_bold(out[i]), "' as input for ", names(out)[i],
|
||||
" (", ab_name(names(out)[i], tolower = TRUE, language = NULL), ").")
|
||||
}
|
||||
if (names(out[i]) %in% names(duplicates)) {
|
||||
already_set_as <- out[unname(out) == unname(out[i])][1L]
|
||||
warning_(paste0("Column '", font_bold(out[i]), "' will not be used for ",
|
||||
names(out)[i], " (", ab_name(names(out)[i], tolower = TRUE, language = NULL), ")",
|
||||
", as it is already set for ",
|
||||
names(already_set_as), " (", ab_name(names(already_set_as), tolower = TRUE, language = NULL), ")"),
|
||||
add_fn = font_red,
|
||||
immediate = verbose)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
out <- out[!duplicated(names(out))]
|
||||
out <- out[!duplicated(unname(out))]
|
||||
if (sort == TRUE) {
|
||||
out <- out[order(names(out), out)]
|
||||
}
|
||||
|
||||
if (!is.null(hard_dependencies)) {
|
||||
hard_dependencies <- unique(hard_dependencies)
|
||||
if (!all(hard_dependencies %in% names(out))) {
|
||||
# missing a hard dependency will return NA and consequently the data will not be analysed
|
||||
missing <- hard_dependencies[!hard_dependencies %in% names(out)]
|
||||
generate_warning_abs_missing(missing, any = FALSE)
|
||||
return(NA)
|
||||
}
|
||||
}
|
||||
if (!is.null(soft_dependencies)) {
|
||||
soft_dependencies <- unique(soft_dependencies)
|
||||
if (info == TRUE & !all(soft_dependencies %in% names(out))) {
|
||||
# missing a soft dependency may lower the reliability
|
||||
missing <- soft_dependencies[!soft_dependencies %in% names(out)]
|
||||
missing_msg <- vector_and(paste0(ab_name(missing, tolower = TRUE, language = NULL),
|
||||
" (", font_bold(missing, collapse = NULL), ")"),
|
||||
quotes = FALSE)
|
||||
message_("Reliability would be improved if these antimicrobial results would be available too: ",
|
||||
missing_msg)
|
||||
}
|
||||
}
|
||||
|
||||
pkg_env$get_column_abx.call <- unique_call_id(entire_session = FALSE, match_fn = fn)
|
||||
pkg_env$get_column_abx.checked_cols <- colnames(x.bak)
|
||||
pkg_env$get_column_abx.out <- out
|
||||
out
|
||||
}
|
||||
|
||||
get_ab_from_namespace <- function(x, cols_ab) {
|
||||
# cols_ab comes from get_column_abx()
|
||||
|
||||
x <- trimws(unique(toupper(unlist(strsplit(x, ",")))))
|
||||
x_new <- character()
|
||||
for (val in x) {
|
||||
if (paste0("AB_", val) %in% ls(envir = asNamespace("AMR"))) {
|
||||
# antibiotic group names, as defined in data-raw/_internals.R, such as `AB_CARBAPENEMS`
|
||||
val <- eval(parse(text = paste0("AB_", val)), envir = asNamespace("AMR"))
|
||||
} else if (val %in% AB_lookup$ab) {
|
||||
# separate drugs, such as `AMX`
|
||||
val <- as.ab(val)
|
||||
} else {
|
||||
stop_("unknown antimicrobial agent (group): ", val, call = FALSE)
|
||||
}
|
||||
x_new <- c(x_new, val)
|
||||
}
|
||||
x_new <- unique(x_new)
|
||||
out <- cols_ab[match(x_new, names(cols_ab))]
|
||||
out[!is.na(out)]
|
||||
}
|
||||
|
||||
generate_warning_abs_missing <- function(missing, any = FALSE) {
|
||||
missing <- paste0(missing, " (", ab_name(missing, tolower = TRUE, language = NULL), ")")
|
||||
if (any == TRUE) {
|
||||
any_txt <- c(" any of", "is")
|
||||
} else {
|
||||
any_txt <- c("", "are")
|
||||
}
|
||||
warning_(paste0("Introducing NAs since", any_txt[1], " these antimicrobials ", any_txt[2], " required: ",
|
||||
vector_and(missing, quotes = FALSE)),
|
||||
immediate = TRUE)
|
||||
}
|
||||
@@ -1,120 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Italicise Taxonomic Families, Genera, Species, Subspecies
|
||||
#'
|
||||
#' According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italics. This function finds taxonomic names within strings and makes them italic.
|
||||
#' @param string a [character] (vector)
|
||||
#' @param type type of conversion of the taxonomic names, either "markdown" or "ansi", see *Details*
|
||||
#' @details
|
||||
#' This function finds the taxonomic names and makes them italic based on the [microorganisms] data set.
|
||||
#'
|
||||
#' The taxonomic names can be italicised using markdown (the default) by adding `*` before and after the taxonomic names, or using ANSI colours by adding `\033[3m` before and `\033[23m` after the taxonomic names. If multiple ANSI colours are not available, no conversion will occur.
|
||||
#'
|
||||
#' This function also supports abbreviation of the genus if it is followed by a species, such as "E. coli" and "K. pneumoniae ozaenae".
|
||||
#' @export
|
||||
#' @examples
|
||||
#' italicise_taxonomy("An overview of Staphylococcus aureus isolates")
|
||||
#' italicise_taxonomy("An overview of S. aureus isolates")
|
||||
#'
|
||||
#' cat(italicise_taxonomy("An overview of S. aureus isolates", type = "ansi"))
|
||||
italicise_taxonomy <- function(string, type = c("markdown", "ansi")) {
|
||||
if (missing(type)) {
|
||||
type <- "markdown"
|
||||
}
|
||||
meet_criteria(string, allow_class = "character")
|
||||
meet_criteria(type, allow_class = "character", has_length = 1, is_in = c("markdown", "ansi"))
|
||||
|
||||
if (type == "markdown") {
|
||||
before <- "*"
|
||||
after <- "*"
|
||||
} else if (type == "ansi") {
|
||||
if (!has_colour()) {
|
||||
return(string)
|
||||
}
|
||||
before <- "\033[3m"
|
||||
after <- "\033[23m"
|
||||
}
|
||||
|
||||
vapply(FUN.VALUE = character(1),
|
||||
string,
|
||||
function(s) {
|
||||
s_split <- unlist(strsplit(s, " "))
|
||||
|
||||
search_strings <- gsub("[^a-zA-Z-]", "", s_split)
|
||||
|
||||
ind_species <- search_strings != "" &
|
||||
search_strings %in% MO_lookup[which(MO_lookup$rank %in% c("family",
|
||||
"genus",
|
||||
"species",
|
||||
"subspecies",
|
||||
"infraspecies",
|
||||
"subsp.")),
|
||||
"species",
|
||||
drop = TRUE]
|
||||
|
||||
ind_fullname <- search_strings != "" &
|
||||
search_strings %in% c(MO_lookup[which(MO_lookup$rank %in% c("family",
|
||||
"genus",
|
||||
"species",
|
||||
"subspecies",
|
||||
"infraspecies",
|
||||
"subsp.")),
|
||||
"fullname",
|
||||
drop = TRUE],
|
||||
MO_lookup[which(MO_lookup$rank %in% c("family",
|
||||
"genus",
|
||||
"species",
|
||||
"subspecies",
|
||||
"infraspecies",
|
||||
"subsp.")),
|
||||
"subspecies",
|
||||
drop = TRUE])
|
||||
|
||||
# also support E. coli, add "E." to indices
|
||||
has_previous_genera_abbr <- s_split[which(ind_species) - 1] %like_case% "^[A-Z][.]?$"
|
||||
ind_species <- c(which(ind_species), which(ind_species)[has_previous_genera_abbr] - 1)
|
||||
|
||||
ind <- c(ind_species, which(ind_fullname))
|
||||
|
||||
s_split[ind] <- paste0(before, s_split[ind], after)
|
||||
s_paste <- paste(s_split, collapse = " ")
|
||||
|
||||
# clean up a bit
|
||||
s_paste <- gsub(paste0(after, " ", before), " ", s_paste, fixed = TRUE)
|
||||
|
||||
s_paste
|
||||
},
|
||||
USE.NAMES = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname italicise_taxonomy
|
||||
#' @export
|
||||
italicize_taxonomy <- function(string, type = c("markdown", "ansi")) {
|
||||
if (missing(type)) {
|
||||
type <- "markdown"
|
||||
}
|
||||
italicise_taxonomy(string = string, type = type)
|
||||
}
|
||||
@@ -1,175 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Join [microorganisms] to a Data Set
|
||||
#'
|
||||
#' Join the data set [microorganisms] easily to an existing data set or to a [character] vector.
|
||||
#' @rdname join
|
||||
#' @name join
|
||||
#' @aliases join inner_join
|
||||
#' @param x existing data set to join, or [character] vector. In case of a [character] vector, the resulting [data.frame] will contain a column 'x' with these values.
|
||||
#' @param by a variable to join by - if left empty will search for a column with class [`mo`] (created with [as.mo()]) or will be `"mo"` if that column name exists in `x`, could otherwise be a column name of `x` with values that exist in `microorganisms$mo` (such as `by = "bacteria_id"`), or another column in [microorganisms] (but then it should be named, like `by = c("bacteria_id" = "fullname")`)
|
||||
#' @param suffix if there are non-joined duplicate variables in `x` and `y`, these suffixes will be added to the output to disambiguate them. Should be a [character] vector of length 2.
|
||||
#' @param ... ignored, only in place to allow future extensions
|
||||
#' @details **Note:** As opposed to the `join()` functions of `dplyr`, [character] vectors are supported and at default existing columns will get a suffix `"2"` and the newly joined columns will not get a suffix.
|
||||
#'
|
||||
#' If the `dplyr` package is installed, their join functions will be used. Otherwise, the much slower [merge()] and [interaction()] functions from base \R will be used.
|
||||
#' @return a [data.frame]
|
||||
#' @export
|
||||
#' @examples
|
||||
#' left_join_microorganisms(as.mo("K. pneumoniae"))
|
||||
#' left_join_microorganisms("B_KLBSL_PNMN")
|
||||
#'
|
||||
#' \donttest{
|
||||
#' if (require("dplyr")) {
|
||||
#' example_isolates %>%
|
||||
#' left_join_microorganisms() %>%
|
||||
#' colnames()
|
||||
#'
|
||||
#' df <- data.frame(date = seq(from = as.Date("2018-01-01"),
|
||||
#' to = as.Date("2018-01-07"),
|
||||
#' by = 1),
|
||||
#' bacteria = as.mo(c("S. aureus", "MRSA", "MSSA", "STAAUR",
|
||||
#' "E. coli", "E. coli", "E. coli")),
|
||||
#' stringsAsFactors = FALSE)
|
||||
#' colnames(df)
|
||||
#' df_joined <- left_join_microorganisms(df, "bacteria")
|
||||
#' colnames(df_joined)
|
||||
#' }
|
||||
#' }
|
||||
inner_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
|
||||
meet_criteria(x, allow_class = c("data.frame", "character"))
|
||||
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(suffix, allow_class = "character", has_length = 2)
|
||||
|
||||
join_microorganisms(type = "inner_join", x = x, by = by, suffix = suffix, ...)
|
||||
}
|
||||
|
||||
#' @rdname join
|
||||
#' @export
|
||||
left_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
|
||||
meet_criteria(x, allow_class = c("data.frame", "character"))
|
||||
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(suffix, allow_class = "character", has_length = 2)
|
||||
|
||||
join_microorganisms(type = "left_join", x = x, by = by, suffix = suffix, ...)
|
||||
}
|
||||
|
||||
#' @rdname join
|
||||
#' @export
|
||||
right_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
|
||||
meet_criteria(x, allow_class = c("data.frame", "character"))
|
||||
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(suffix, allow_class = "character", has_length = 2)
|
||||
|
||||
join_microorganisms(type = "right_join", x = x, by = by, suffix = suffix, ...)
|
||||
}
|
||||
|
||||
#' @rdname join
|
||||
#' @export
|
||||
full_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
|
||||
meet_criteria(x, allow_class = c("data.frame", "character"))
|
||||
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(suffix, allow_class = "character", has_length = 2)
|
||||
|
||||
join_microorganisms(type = "full_join", x = x, by = by, suffix = suffix, ...)
|
||||
}
|
||||
|
||||
#' @rdname join
|
||||
#' @export
|
||||
semi_join_microorganisms <- function(x, by = NULL, ...) {
|
||||
meet_criteria(x, allow_class = c("data.frame", "character"))
|
||||
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
|
||||
|
||||
join_microorganisms(type = "semi_join", x = x, by = by, ...)
|
||||
}
|
||||
|
||||
#' @rdname join
|
||||
#' @export
|
||||
anti_join_microorganisms <- function(x, by = NULL, ...) {
|
||||
meet_criteria(x, allow_class = c("data.frame", "character"))
|
||||
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
|
||||
|
||||
join_microorganisms(type = "anti_join", x = x, by = by, ...)
|
||||
}
|
||||
|
||||
join_microorganisms <- function(type, x, by, suffix, ...) {
|
||||
check_dataset_integrity()
|
||||
|
||||
if (!is.data.frame(x)) {
|
||||
x <- data.frame(mo = x, stringsAsFactors = FALSE)
|
||||
by <- "mo"
|
||||
}
|
||||
if (is.null(by)) {
|
||||
by <- search_type_in_df(x, "mo", info = FALSE)
|
||||
if (is.null(by) && NCOL(x) == 1) {
|
||||
by <- colnames(x)[1L]
|
||||
} else {
|
||||
stop_if(is.null(by), "no column with microorganism names or codes found, set this column with `by`", call = -2)
|
||||
}
|
||||
message_('Joining, by = "', by, '"', add_fn = font_black, as_note = FALSE) # message same as dplyr::join functions
|
||||
}
|
||||
if (!all(x[, by, drop = TRUE] %in% MO_lookup$mo, na.rm = TRUE)) {
|
||||
x$join.mo <- as.mo(x[, by, drop = TRUE])
|
||||
by <- c("join.mo" = "mo")
|
||||
} else {
|
||||
x[, by] <- as.mo(x[, by, drop = TRUE])
|
||||
}
|
||||
|
||||
if (is.null(names(by))) {
|
||||
# will always be joined to microorganisms$mo, so add name to that
|
||||
by <- stats::setNames("mo", by)
|
||||
}
|
||||
|
||||
# use dplyr if available - it's much faster than poorman alternatives
|
||||
dplyr_join <- import_fn(name = type, pkg = "dplyr", error_on_fail = FALSE)
|
||||
if (!is.null(dplyr_join)) {
|
||||
join_fn <- dplyr_join
|
||||
} else {
|
||||
# otherwise use poorman, see R/aa_helper_pm_functions.R
|
||||
join_fn <- get(paste0("pm_", type), envir = asNamespace("AMR"))
|
||||
}
|
||||
if (type %like% "full|left|right|inner") {
|
||||
joined <- join_fn(x = x, y = AMR::microorganisms, by = by, suffix = suffix, ...)
|
||||
} else {
|
||||
joined <- join_fn(x = x, y = AMR::microorganisms, by = by, ...)
|
||||
}
|
||||
|
||||
if ("join.mo" %in% colnames(joined)) {
|
||||
if ("mo" %in% colnames(joined)) {
|
||||
ind_mo <- which(colnames(joined) %in% c("mo", "join.mo"))
|
||||
colnames(joined)[ind_mo[1L]] <- paste0("mo", suffix[1L])
|
||||
colnames(joined)[ind_mo[2L]] <- paste0("mo", suffix[2L])
|
||||
} else {
|
||||
colnames(joined)[colnames(joined) == "join.mo"] <- "mo"
|
||||
}
|
||||
}
|
||||
|
||||
if (type %like% "full|left|right|inner" && NROW(joined) > NROW(x)) {
|
||||
warning_("in `", type, "_join()`: the newly joined data set contains ", nrow(joined) - nrow(x), " rows more than the number of rows of `x`.")
|
||||
}
|
||||
|
||||
joined
|
||||
}
|
||||
@@ -1,333 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' (Key) Antimicrobials for First Weighted Isolates
|
||||
#'
|
||||
#' These functions can be used to determine first weighted isolates by considering the phenotype for isolate selection (see [first_isolate()]). Using a phenotype-based method to determine first isolates is more reliable than methods that disregard phenotypes.
|
||||
#' @param x a [data.frame] with antibiotics columns, like `AMX` or `amox`. Can be left blank to determine automatically
|
||||
#' @param y,z [character] vectors to compare
|
||||
#' @inheritParams first_isolate
|
||||
#' @param universal names of **broad-spectrum** antimicrobial agents, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
|
||||
#' @param gram_negative names of antibiotic agents for **Gram-positives**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
|
||||
#' @param gram_positive names of antibiotic agents for **Gram-negatives**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
|
||||
#' @param antifungal names of antifungal agents for **fungi**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
|
||||
#' @param only_rsi_columns a [logical] to indicate whether only columns must be included that were transformed to class `<rsi>` (see [as.rsi()]) on beforehand (defaults to `FALSE`)
|
||||
#' @param ... ignored, only in place to allow future extensions
|
||||
#' @details
|
||||
#' The [key_antimicrobials()] and [all_antimicrobials()] functions are context-aware. This means that the `x` argument can be left blank if used inside a [data.frame] call, see *Examples*.
|
||||
#'
|
||||
#' The function [key_antimicrobials()] returns a [character] vector with 12 antimicrobial results for every isolate. The function [all_antimicrobials()] returns a [character] vector with all antimicrobial results for every isolate. These vectors can then be compared using [antimicrobials_equal()], to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (`"."`) by [key_antimicrobials()] and ignored by [antimicrobials_equal()].
|
||||
#'
|
||||
#' Please see the [first_isolate()] function how these important functions enable the 'phenotype-based' method for determination of first isolates.
|
||||
#'
|
||||
#' The default antimicrobial agents used for **all rows** (set in `universal`) are:
|
||||
#'
|
||||
#' - Ampicillin
|
||||
#' - Amoxicillin/clavulanic acid
|
||||
#' - Cefuroxime
|
||||
#' - Ciprofloxacin
|
||||
#' - Piperacillin/tazobactam
|
||||
#' - Trimethoprim/sulfamethoxazole
|
||||
#'
|
||||
#' The default antimicrobial agents used for **Gram-negative bacteria** (set in `gram_negative`) are:
|
||||
#'
|
||||
#' - Cefotaxime
|
||||
#' - Ceftazidime
|
||||
#' - Colistin
|
||||
#' - Gentamicin
|
||||
#' - Meropenem
|
||||
#' - Tobramycin
|
||||
#'
|
||||
#' The default antimicrobial agents used for **Gram-positive bacteria** (set in `gram_positive`) are:
|
||||
#'
|
||||
#' - Erythromycin
|
||||
#' - Oxacillin
|
||||
#' - Rifampin
|
||||
#' - Teicoplanin
|
||||
#' - Tetracycline
|
||||
#' - Vancomycin
|
||||
#'
|
||||
#'
|
||||
#' The default antimicrobial agents used for **fungi** (set in `antifungal`) are:
|
||||
#'
|
||||
#' - Anidulafungin
|
||||
#' - Caspofungin
|
||||
#' - Fluconazole
|
||||
#' - Miconazole
|
||||
#' - Nystatin
|
||||
#' - Voriconazole
|
||||
#' @rdname key_antimicrobials
|
||||
#' @export
|
||||
#' @seealso [first_isolate()]
|
||||
#' @examples
|
||||
#' # `example_isolates` is a data set available in the AMR package.
|
||||
#' # See ?example_isolates.
|
||||
#'
|
||||
#' # output of the `key_antimicrobials()` function could be like this:
|
||||
#' strainA <- "SSSRR.S.R..S"
|
||||
#' strainB <- "SSSIRSSSRSSS"
|
||||
#'
|
||||
#' # those strings can be compared with:
|
||||
#' antimicrobials_equal(strainA, strainB, type = "keyantimicrobials")
|
||||
#' # TRUE, because I is ignored (as well as missing values)
|
||||
#'
|
||||
#' antimicrobials_equal(strainA, strainB, type = "keyantimicrobials", ignore_I = FALSE)
|
||||
#' # FALSE, because I is not ignored and so the 4th [character] differs
|
||||
#'
|
||||
#' \donttest{
|
||||
#' if (require("dplyr")) {
|
||||
#' # set key antibiotics to a new variable
|
||||
#' my_patients <- example_isolates %>%
|
||||
#' mutate(keyab = key_antimicrobials(antifungal = NULL)) %>% # no need to define `x`
|
||||
#' mutate(
|
||||
#' # now calculate first isolates
|
||||
#' first_regular = first_isolate(col_keyantimicrobials = FALSE),
|
||||
#' # and first WEIGHTED isolates
|
||||
#' first_weighted = first_isolate(col_keyantimicrobials = "keyab")
|
||||
#' )
|
||||
#'
|
||||
#' # Check the difference in this data set, 'weighted' results in more isolates:
|
||||
#' sum(my_patients$first_regular, na.rm = TRUE)
|
||||
#' sum(my_patients$first_weighted, na.rm = TRUE)
|
||||
#' }
|
||||
#' }
|
||||
key_antimicrobials <- function(x = NULL,
|
||||
col_mo = NULL,
|
||||
universal = c("ampicillin", "amoxicillin/clavulanic acid", "cefuroxime",
|
||||
"piperacillin/tazobactam", "ciprofloxacin", "trimethoprim/sulfamethoxazole"),
|
||||
gram_negative = c("gentamicin", "tobramycin", "colistin",
|
||||
"cefotaxime", "ceftazidime", "meropenem"),
|
||||
gram_positive = c("vancomycin", "teicoplanin", "tetracycline",
|
||||
"erythromycin", "oxacillin", "rifampin"),
|
||||
antifungal = c("anidulafungin", "caspofungin", "fluconazole",
|
||||
"miconazole", "nystatin", "voriconazole"),
|
||||
only_rsi_columns = FALSE,
|
||||
...) {
|
||||
if (is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
|
||||
}
|
||||
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
|
||||
meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE, is_in = colnames(x))
|
||||
meet_criteria(universal, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(gram_negative, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(gram_positive, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(antifungal, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
|
||||
# force regular data.frame, not a tibble or data.table
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
||||
cols <- get_column_abx(x, info = FALSE, only_rsi_columns = only_rsi_columns, fn = "key_antimicrobials")
|
||||
|
||||
# try to find columns based on type
|
||||
# -- mo
|
||||
if (is.null(col_mo)) {
|
||||
col_mo <- search_type_in_df(x = x, type = "mo", info = FALSE)
|
||||
}
|
||||
if (is.null(col_mo)) {
|
||||
warning_("in `key_antimicrobials()`: no column found for `col_mo`, ignoring antibiotics set in `gram_negative` and `gram_positive`, and antimycotics set in `antifungal`")
|
||||
gramstain <- NA_character_
|
||||
kingdom <- NA_character_
|
||||
} else {
|
||||
x.mo <- as.mo(x[, col_mo, drop = TRUE])
|
||||
gramstain <- mo_gramstain(x.mo, language = NULL)
|
||||
kingdom <- mo_kingdom(x.mo, language = NULL)
|
||||
}
|
||||
|
||||
AMR_string <- function(x, values, name, filter, cols = cols) {
|
||||
if (is.null(values)) {
|
||||
return(rep(NA_character_, length(which(filter))))
|
||||
}
|
||||
|
||||
values_old_length <- length(values)
|
||||
values <- as.ab(values, flag_multiple_results = FALSE, info = FALSE)
|
||||
values <- cols[names(cols) %in% values]
|
||||
values_new_length <- length(values)
|
||||
|
||||
if (values_new_length < values_old_length &
|
||||
any(filter, na.rm = TRUE) &
|
||||
message_not_thrown_before("key_antimicrobials", name)) {
|
||||
warning_("in `key_antimicrobials()`: ",
|
||||
ifelse(values_new_length == 0,
|
||||
"No columns available ",
|
||||
paste0("Only using ", values_new_length, " out of ", values_old_length, " defined columns ")),
|
||||
"as key antimicrobials for ", name, "s. See ?key_antimicrobials.")
|
||||
}
|
||||
|
||||
generate_antimcrobials_string(x[which(filter), c(universal, values), drop = FALSE])
|
||||
}
|
||||
|
||||
if (is.null(universal)) {
|
||||
universal <- character(0)
|
||||
} else {
|
||||
universal <- as.ab(universal, flag_multiple_results = FALSE, info = FALSE)
|
||||
universal <- cols[names(cols) %in% universal]
|
||||
}
|
||||
|
||||
key_ab <- rep(NA_character_, nrow(x))
|
||||
|
||||
key_ab[which(gramstain == "Gram-negative")] <- AMR_string(x = x,
|
||||
values = gram_negative,
|
||||
name = "Gram-negative",
|
||||
filter = gramstain == "Gram-negative",
|
||||
cols = cols)
|
||||
|
||||
key_ab[which(gramstain == "Gram-positive")] <- AMR_string(x = x,
|
||||
values = gram_positive,
|
||||
name = "Gram-positive",
|
||||
filter = gramstain == "Gram-positive",
|
||||
cols = cols)
|
||||
|
||||
key_ab[which(kingdom == "Fungi")] <- AMR_string(x = x,
|
||||
values = antifungal,
|
||||
name = "antifungal",
|
||||
filter = kingdom == "Fungi",
|
||||
cols = cols)
|
||||
|
||||
# back-up - only use `universal`
|
||||
key_ab[which(is.na(key_ab))] <- AMR_string(x = x,
|
||||
values = character(0),
|
||||
name = "",
|
||||
filter = is.na(key_ab),
|
||||
cols = cols)
|
||||
|
||||
if (length(unique(key_ab)) == 1) {
|
||||
warning_("in `key_antimicrobials()`: no distinct key antibiotics determined.")
|
||||
}
|
||||
|
||||
key_ab
|
||||
}
|
||||
|
||||
#' @rdname key_antimicrobials
|
||||
#' @export
|
||||
all_antimicrobials <- function(x = NULL,
|
||||
only_rsi_columns = FALSE,
|
||||
...) {
|
||||
if (is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
|
||||
}
|
||||
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
|
||||
# force regular data.frame, not a tibble or data.table
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
||||
cols <- get_column_abx(x, only_rsi_columns = only_rsi_columns, info = FALSE,
|
||||
sort = FALSE, fn = "all_antimicrobials")
|
||||
|
||||
generate_antimcrobials_string(x[ , cols, drop = FALSE])
|
||||
}
|
||||
|
||||
generate_antimcrobials_string <- function(df) {
|
||||
if (NCOL(df) == 0) {
|
||||
return(rep("", NROW(df)))
|
||||
}
|
||||
if (NROW(df) == 0) {
|
||||
return(character(0))
|
||||
}
|
||||
tryCatch({
|
||||
do.call(paste0,
|
||||
lapply(as.list(df),
|
||||
function(x) {
|
||||
x <- toupper(as.character(x))
|
||||
x[!x %in% c("R", "S", "I")] <- "."
|
||||
paste(x)
|
||||
}))
|
||||
},
|
||||
error = function(e) rep(strrep(".", NCOL(df)), NROW(df)))
|
||||
}
|
||||
|
||||
#' @rdname key_antimicrobials
|
||||
#' @export
|
||||
antimicrobials_equal <- function(y,
|
||||
z,
|
||||
type = c("points", "keyantimicrobials"),
|
||||
ignore_I = TRUE,
|
||||
points_threshold = 2,
|
||||
...) {
|
||||
meet_criteria(y, allow_class = "character")
|
||||
meet_criteria(z, allow_class = "character")
|
||||
stop_if(missing(type), "argument \"type\" is missing, with no default")
|
||||
meet_criteria(type, allow_class = "character", has_length = 1, is_in = c("points", "keyantimicrobials"))
|
||||
meet_criteria(ignore_I, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(points_threshold, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
stop_ifnot(length(y) == length(z), "length of `y` and `z` must be equal")
|
||||
|
||||
key2rsi <- function(val) {
|
||||
val <- strsplit(val, "")[[1L]]
|
||||
val.int <- rep(NA_real_, length(val))
|
||||
val.int[val == "S"] <- 1
|
||||
val.int[val == "I"] <- 2
|
||||
val.int[val == "R"] <- 3
|
||||
val.int
|
||||
}
|
||||
# only run on uniques
|
||||
uniq <- unique(c(y, z))
|
||||
uniq_list <- lapply(uniq, key2rsi)
|
||||
names(uniq_list) <- uniq
|
||||
|
||||
y <- uniq_list[match(y, names(uniq_list))]
|
||||
z <- uniq_list[match(z, names(uniq_list))]
|
||||
|
||||
determine_equality <- function(a, b, type, points_threshold, ignore_I) {
|
||||
if (length(a) != length(b)) {
|
||||
# incomparable, so not equal
|
||||
return(FALSE)
|
||||
}
|
||||
# ignore NAs on both sides
|
||||
NA_ind <- which(is.na(a) | is.na(b))
|
||||
a[NA_ind] <- NA_real_
|
||||
b[NA_ind] <- NA_real_
|
||||
|
||||
if (type == "points") {
|
||||
# count points for every single character:
|
||||
# - no change is 0 points
|
||||
# - I <-> S|R is 0.5 point
|
||||
# - S|R <-> R|S is 1 point
|
||||
# use the levels of as.rsi (S = 1, I = 2, R = 3)
|
||||
# and divide by 2 (S = 0.5, I = 1, R = 1.5)
|
||||
(sum(abs(a - b), na.rm = TRUE) / 2) < points_threshold
|
||||
} else {
|
||||
if (ignore_I == TRUE) {
|
||||
ind <- which(a == 2 | b == 2) # since as.double(as.rsi("I")) == 2
|
||||
a[ind] <- NA_real_
|
||||
b[ind] <- NA_real_
|
||||
}
|
||||
all(a == b, na.rm = TRUE)
|
||||
}
|
||||
}
|
||||
out <- unlist(mapply(FUN = determine_equality,
|
||||
y,
|
||||
z,
|
||||
MoreArgs = list(type = type,
|
||||
points_threshold = points_threshold,
|
||||
ignore_I = ignore_I),
|
||||
SIMPLIFY = FALSE,
|
||||
USE.NAMES = FALSE))
|
||||
out[is.na(y) | is.na(z)] <- NA
|
||||
out
|
||||
}
|
||||
@@ -1,76 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Kurtosis of the Sample
|
||||
#'
|
||||
#' @description Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. A normal distribution has a kurtosis of 3 and a excess kurtosis of 0.
|
||||
#' @param x a vector of values, a [matrix] or a [data.frame]
|
||||
#' @param na.rm a [logical] to indicate whether `NA` values should be stripped before the computation proceeds
|
||||
#' @param excess a [logical] to indicate whether the *excess kurtosis* should be returned, defined as the kurtosis minus 3.
|
||||
#' @seealso [skewness()]
|
||||
#' @rdname kurtosis
|
||||
#' @export
|
||||
#' @examples
|
||||
#' kurtosis(rnorm(10000))
|
||||
#' kurtosis(rnorm(10000), excess = TRUE)
|
||||
kurtosis <- function(x, na.rm = FALSE, excess = FALSE) {
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(excess, allow_class = "logical", has_length = 1)
|
||||
UseMethod("kurtosis")
|
||||
}
|
||||
|
||||
#' @method kurtosis default
|
||||
#' @rdname kurtosis
|
||||
#' @export
|
||||
kurtosis.default <- function(x, na.rm = FALSE, excess = FALSE) {
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(excess, allow_class = "logical", has_length = 1)
|
||||
x <- as.vector(x)
|
||||
if (na.rm == TRUE) {
|
||||
x <- x[!is.na(x)]
|
||||
}
|
||||
n <- length(x)
|
||||
k <- n * sum((x - mean(x, na.rm = na.rm))^4, na.rm = na.rm) /
|
||||
(sum((x - mean(x, na.rm = na.rm))^2, na.rm = na.rm)^2)
|
||||
k - ifelse(excess, 3, 0)
|
||||
}
|
||||
|
||||
#' @method kurtosis matrix
|
||||
#' @rdname kurtosis
|
||||
#' @export
|
||||
kurtosis.matrix <- function(x, na.rm = FALSE, excess = FALSE) {
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(excess, allow_class = "logical", has_length = 1)
|
||||
apply(x, 2, kurtosis.default, na.rm = na.rm, excess = excess)
|
||||
}
|
||||
|
||||
#' @method kurtosis data.frame
|
||||
#' @rdname kurtosis
|
||||
#' @export
|
||||
kurtosis.data.frame <- function(x, na.rm = FALSE, excess = FALSE) {
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(excess, allow_class = "logical", has_length = 1)
|
||||
vapply(FUN.VALUE = double(1), x, kurtosis.default, na.rm = na.rm, excess = excess)
|
||||
}
|
||||
@@ -1,139 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Vectorised Pattern Matching with Keyboard Shortcut
|
||||
#'
|
||||
#' Convenient wrapper around [grepl()] to match a pattern: `x %like% pattern`. It always returns a [`logical`] vector and is always case-insensitive (use `x %like_case% pattern` for case-sensitive matching). Also, `pattern` can be as long as `x` to compare items of each index in both vectors, or they both can have the same length to iterate over all cases.
|
||||
#' @param x a [character] vector where matches are sought, or an object which can be coerced by [as.character()] to a [character] vector.
|
||||
#' @param pattern a [character] vector containing regular expressions (or a [character] string for `fixed = TRUE`) to be matched in the given [character] vector. Coerced by [as.character()] to a [character] string if possible.
|
||||
#' @param ignore.case if `FALSE`, the pattern matching is *case sensitive* and if `TRUE`, case is ignored during matching.
|
||||
#' @return A [logical] vector
|
||||
#' @name like
|
||||
#' @rdname like
|
||||
#' @export
|
||||
#' @details
|
||||
#' These [like()] and `%like%`/`%unlike%` functions:
|
||||
#' * Are case-insensitive (use `%like_case%`/`%unlike_case%` for case-sensitive matching)
|
||||
#' * Support multiple patterns
|
||||
#' * Check if `pattern` is a valid regular expression and sets `fixed = TRUE` if not, to greatly improve speed (vectorised over `pattern`)
|
||||
#' * Always use compatibility with Perl unless `fixed = TRUE`, to greatly improve speed
|
||||
#'
|
||||
#' Using RStudio? The `%like%`/`%unlike%` functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like `Shift+Ctrl+L` or `Shift+Cmd+L` (see menu `Tools` > `Modify Keyboard Shortcuts...`). If you keep pressing your shortcut, the inserted text will be iterated over `%like%` -> `%unlike%` -> `%like_case%` -> `%unlike_case%`.
|
||||
#' @source Idea from the [`like` function from the `data.table` package](https://github.com/Rdatatable/data.table/blob/ec1259af1bf13fc0c96a1d3f9e84d55d8106a9a4/R/like.R), although altered as explained in *Details*.
|
||||
#' @seealso [grepl()]
|
||||
|
||||
#' @examples
|
||||
#' a <- "This is a test"
|
||||
#' b <- "TEST"
|
||||
#' a %like% b
|
||||
#' b %like% a
|
||||
#'
|
||||
#' # also supports multiple patterns
|
||||
#' a <- c("Test case", "Something different", "Yet another thing")
|
||||
#' b <- c( "case", "diff", "yet")
|
||||
#' a %like% b
|
||||
#' a %unlike% b
|
||||
#'
|
||||
#' a[1] %like% b
|
||||
#' a %like% b[1]
|
||||
#'
|
||||
#' # get isolates whose name start with 'Ent' or 'ent'
|
||||
#' example_isolates[which(mo_name(example_isolates$mo) %like% "^ent"), ]
|
||||
#' \donttest{
|
||||
#' # faster way, since mo_name() is context-aware:
|
||||
#' example_isolates[which(mo_name() %like% "^ent"), ]
|
||||
#'
|
||||
#' if (require("dplyr")) {
|
||||
#' example_isolates %>%
|
||||
#' filter(mo_name() %like% "^ent")
|
||||
#' }
|
||||
#' }
|
||||
like <- function(x, pattern, ignore.case = TRUE) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(pattern, allow_NA = FALSE)
|
||||
meet_criteria(ignore.case, allow_class = "logical", has_length = 1)
|
||||
|
||||
if (all(is.na(x))) {
|
||||
return(rep(FALSE, length(x)))
|
||||
}
|
||||
|
||||
# set to fixed if no valid regex (vectorised)
|
||||
fixed <- !is_valid_regex(pattern)
|
||||
|
||||
if (ignore.case == TRUE) {
|
||||
# set here, otherwise if fixed = TRUE, this warning will be thrown: argument `ignore.case = TRUE` will be ignored
|
||||
x <- tolower(x)
|
||||
pattern <- tolower(pattern)
|
||||
}
|
||||
|
||||
if (is.factor(x)) {
|
||||
x <- as.character(x)
|
||||
}
|
||||
|
||||
if (length(pattern) == 1) {
|
||||
grepl(pattern, x, ignore.case = FALSE, fixed = fixed, perl = !fixed)
|
||||
} else {
|
||||
if (length(x) == 1) {
|
||||
x <- rep(x, length(pattern))
|
||||
} else if (length(pattern) != length(x)) {
|
||||
stop_("arguments `x` and `pattern` must be of same length, or either one must be 1 ",
|
||||
"(`x` has length ", length(x), " and `pattern` has length ", length(pattern), ")")
|
||||
}
|
||||
unlist(
|
||||
mapply(FUN = grepl,
|
||||
x = x,
|
||||
pattern = pattern,
|
||||
fixed = fixed,
|
||||
perl = !fixed,
|
||||
MoreArgs = list(ignore.case = FALSE),
|
||||
SIMPLIFY = FALSE,
|
||||
USE.NAMES = FALSE)
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname like
|
||||
#' @export
|
||||
"%like%" <- function(x, pattern) {
|
||||
like(x, pattern, ignore.case = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname like
|
||||
#' @export
|
||||
"%unlike%" <- function(x, pattern) {
|
||||
!like(x, pattern, ignore.case = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname like
|
||||
#' @export
|
||||
"%like_case%" <- function(x, pattern) {
|
||||
like(x, pattern, ignore.case = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname like
|
||||
#' @export
|
||||
"%unlike_case%" <- function(x, pattern) {
|
||||
!like(x, pattern, ignore.case = FALSE)
|
||||
}
|
||||
@@ -1,804 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
# these are allowed MIC values and will become [factor] levels
|
||||
ops <- c("<", "<=", "", ">=", ">")
|
||||
valid_mic_levels <- c(c(t(vapply(FUN.VALUE = character(9), ops,
|
||||
function(x) paste0(x, "0.00", 1:9)))),
|
||||
unique(c(t(vapply(FUN.VALUE = character(104), ops,
|
||||
function(x) paste0(x, sort(as.double(paste0("0.0",
|
||||
sort(c(1:99, 125, 128, 256, 512, 625)))))))))),
|
||||
unique(c(t(vapply(FUN.VALUE = character(103), ops,
|
||||
function(x) paste0(x, sort(as.double(paste0("0.",
|
||||
c(1:99, 125, 128, 256, 512))))))))),
|
||||
c(t(vapply(FUN.VALUE = character(10), ops,
|
||||
function(x) paste0(x, sort(c(1:9, 1.5)))))),
|
||||
c(t(vapply(FUN.VALUE = character(45), ops,
|
||||
function(x) paste0(x, c(10:98)[9:98 %% 2 == TRUE])))),
|
||||
c(t(vapply(FUN.VALUE = character(17), ops,
|
||||
function(x) paste0(x, sort(c(2 ^ c(7:11), 192, 80 * c(2:12))))))))
|
||||
|
||||
#' Transform Input to Minimum Inhibitory Concentrations (MIC)
|
||||
#'
|
||||
#' This transforms vectors to a new class [`mic`], which treats the input as decimal numbers, while maintaining operators (such as ">=") and only allowing valid MIC values known to the field of (medical) microbiology.
|
||||
#' @rdname as.mic
|
||||
#' @param x a [character] or [numeric] vector
|
||||
#' @param na.rm a [logical] indicating whether missing values should be removed
|
||||
#' @param ... arguments passed on to methods
|
||||
#' @details To interpret MIC values as RSI values, use [as.rsi()] on MIC values. It supports guidelines from EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`).
|
||||
#'
|
||||
#' This class for MIC values is a quite a special data type: formally it is an ordered [factor] with valid MIC values as [factor] levels (to make sure only valid MIC values are retained), but for any mathematical operation it acts as decimal numbers:
|
||||
#'
|
||||
#' ```
|
||||
#' x <- random_mic(10)
|
||||
#' x
|
||||
#' #> Class <mic>
|
||||
#' #> [1] 16 1 8 8 64 >=128 0.0625 32 32 16
|
||||
#'
|
||||
#' is.factor(x)
|
||||
#' #> [1] TRUE
|
||||
#'
|
||||
#' x[1] * 2
|
||||
#' #> [1] 32
|
||||
#'
|
||||
#' median(x)
|
||||
#' #> [1] 26
|
||||
#' ```
|
||||
#'
|
||||
#' This makes it possible to maintain operators that often come with MIC values, such ">=" and "<=", even when filtering using [numeric] values in data analysis, e.g.:
|
||||
#'
|
||||
#' ```
|
||||
#' x[x > 4]
|
||||
#' #> Class <mic>
|
||||
#' #> [1] 16 8 8 64 >=128 32 32 16
|
||||
#'
|
||||
#' df <- data.frame(x, hospital = "A")
|
||||
#' subset(df, x > 4) # or with dplyr: df %>% filter(x > 4)
|
||||
#' #> x hospital
|
||||
#' #> 1 16 A
|
||||
#' #> 5 64 A
|
||||
#' #> 6 >=128 A
|
||||
#' #> 8 32 A
|
||||
#' #> 9 32 A
|
||||
#' #> 10 16 A
|
||||
#' ```
|
||||
#'
|
||||
#' The following [generic functions][groupGeneric()] are implemented for the MIC class: `!`, `!=`, `%%`, `%/%`, `&`, `*`, `+`, `-`, `/`, `<`, `<=`, `==`, `>`, `>=`, `^`, `|`, [abs()], [acos()], [acosh()], [all()], [any()], [asin()], [asinh()], [atan()], [atanh()], [ceiling()], [cos()], [cosh()], [cospi()], [cummax()], [cummin()], [cumprod()], [cumsum()], [digamma()], [exp()], [expm1()], [floor()], [gamma()], [lgamma()], [log()], [log1p()], [log2()], [log10()], [max()], [mean()], [min()], [prod()], [range()], [round()], [sign()], [signif()], [sin()], [sinh()], [sinpi()], [sqrt()], [sum()], [tan()], [tanh()], [tanpi()], [trigamma()] and [trunc()]. Some functions of the `stats` package are also implemented: [median()], [quantile()], [mad()], [IQR()], [fivenum()]. Also, [boxplot.stats()] is supported. Since [sd()] and [var()] are non-generic functions, these could not be extended. Use [mad()] as an alternative, or use e.g. `sd(as.numeric(x))` where `x` is your vector of MIC values.
|
||||
#'
|
||||
#' Using [as.double()] or [as.numeric()] on MIC values will remove the operators and return a numeric vector. Do **not** use [as.integer()] on MIC values as by the \R convention on [factor]s, it will return the index of the factor levels (which is often useless for regular users).
|
||||
#'
|
||||
#' Use [droplevels()] to drop unused levels. At default, it will return a plain factor. Use `droplevels(..., as.mic = TRUE)` to maintain the `<mic>` class.
|
||||
#' @return Ordered [factor] with additional class [`mic`], that in mathematical operations acts as decimal numbers. Bare in mind that the outcome of any mathematical operation on MICs will return a [numeric] value.
|
||||
#' @aliases mic
|
||||
#' @export
|
||||
#' @seealso [as.rsi()]
|
||||
#' @examples
|
||||
#' mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
|
||||
#' mic_data
|
||||
#' is.mic(mic_data)
|
||||
#'
|
||||
#' # this can also coerce combined MIC/RSI values:
|
||||
#' as.mic("<=0.002; S")
|
||||
#'
|
||||
#' # mathematical processing treats MICs as numeric values
|
||||
#' fivenum(mic_data)
|
||||
#' quantile(mic_data)
|
||||
#' all(mic_data < 512)
|
||||
#'
|
||||
#' # interpret MIC values
|
||||
#' as.rsi(x = as.mic(2),
|
||||
#' mo = as.mo("Streptococcus pneumoniae"),
|
||||
#' ab = "AMX",
|
||||
#' guideline = "EUCAST")
|
||||
#' as.rsi(x = as.mic(c(0.01, 2, 4, 8)),
|
||||
#' mo = as.mo("Streptococcus pneumoniae"),
|
||||
#' ab = "AMX",
|
||||
#' guideline = "EUCAST")
|
||||
#'
|
||||
#' # plot MIC values, see ?plot
|
||||
#' plot(mic_data)
|
||||
#' plot(mic_data, mo = "E. coli", ab = "cipro")
|
||||
#' autoplot(mic_data, mo = "E. coli", ab = "cipro")
|
||||
#' autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "nl") # Dutch
|
||||
#' autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "uk") # Ukrainian
|
||||
as.mic <- function(x, na.rm = FALSE) {
|
||||
meet_criteria(x, allow_class = c("mic", "character", "numeric", "integer", "factor"), allow_NA = TRUE)
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
|
||||
if (is.mic(x)) {
|
||||
x
|
||||
} else {
|
||||
x <- as.character(unlist(x))
|
||||
if (na.rm == TRUE) {
|
||||
x <- x[!is.na(x)]
|
||||
}
|
||||
x[trimws(x) == ""] <- NA
|
||||
x.bak <- x
|
||||
|
||||
# comma to period
|
||||
x <- gsub(",", ".", x, fixed = TRUE)
|
||||
# transform Unicode for >= and <=
|
||||
x <- gsub("\u2264", "<=", x, fixed = TRUE)
|
||||
x <- gsub("\u2265", ">=", x, fixed = TRUE)
|
||||
# remove other invalid characters
|
||||
x <- gsub("[^a-zA-Z0-9.><= ]+", "", x, perl = TRUE)
|
||||
# remove space between operator and number ("<= 0.002" -> "<=0.002")
|
||||
x <- gsub("(<|=|>) +", "\\1", x, perl = TRUE)
|
||||
# transform => to >= and =< to <=
|
||||
x <- gsub("=<", "<=", x, fixed = TRUE)
|
||||
x <- gsub("=>", ">=", x, fixed = TRUE)
|
||||
# dots without a leading zero must start with 0
|
||||
x <- gsub("([^0-9]|^)[.]", "\\10.", x, perl = TRUE)
|
||||
# values like "<=0.2560.512" should be 0.512
|
||||
x <- gsub(".*[.].*[.]", "0.", x, perl = TRUE)
|
||||
# remove ending .0
|
||||
x <- gsub("[.]+0$", "", x, perl = TRUE)
|
||||
# remove all after last digit
|
||||
x <- gsub("[^0-9]+$", "", x, perl = TRUE)
|
||||
# keep only one zero before dot
|
||||
x <- gsub("0+[.]", "0.", x, perl = TRUE)
|
||||
# starting 00 is probably 0.0 if there's no dot yet
|
||||
x[x %unlike% "[.]"] <- gsub("^00", "0.0", x[!x %like% "[.]"])
|
||||
# remove last zeroes
|
||||
x <- gsub("([.].?)0+$", "\\1", x, perl = TRUE)
|
||||
x <- gsub("(.*[.])0+$", "\\10", x, perl = TRUE)
|
||||
# remove ending .0 again
|
||||
x[x %like% "[.]"] <- gsub("0+$", "", x[x %like% "[.]"])
|
||||
# never end with dot
|
||||
x <- gsub("[.]$", "", x, perl = TRUE)
|
||||
# trim it
|
||||
x <- trimws(x)
|
||||
|
||||
## previously unempty values now empty - should return a warning later on
|
||||
x[x.bak != "" & x == ""] <- "invalid"
|
||||
|
||||
na_before <- x[is.na(x) | x == ""] %pm>% length()
|
||||
x[!x %in% valid_mic_levels] <- NA
|
||||
na_after <- x[is.na(x) | x == ""] %pm>% length()
|
||||
|
||||
if (na_before != na_after) {
|
||||
list_missing <- x.bak[is.na(x) & !is.na(x.bak) & x.bak != ""] %pm>%
|
||||
unique() %pm>%
|
||||
sort() %pm>%
|
||||
vector_and(quotes = TRUE)
|
||||
warning_("in `as.mic()`: ", na_after - na_before, " results truncated (",
|
||||
round(((na_after - na_before) / length(x)) * 100),
|
||||
"%) that were invalid MICs: ",
|
||||
list_missing, call = FALSE)
|
||||
}
|
||||
|
||||
set_clean_class(factor(x, levels = valid_mic_levels, ordered = TRUE),
|
||||
new_class = c("mic", "ordered", "factor"))
|
||||
}
|
||||
}
|
||||
|
||||
all_valid_mics <- function(x) {
|
||||
if (!inherits(x, c("mic", "character", "factor", "numeric", "integer"))) {
|
||||
return(FALSE)
|
||||
}
|
||||
x_mic <- tryCatch(suppressWarnings(as.mic(x[!is.na(x)])),
|
||||
error = function(e) NA)
|
||||
!any(is.na(x_mic)) && !all(is.na(x))
|
||||
}
|
||||
|
||||
#' @rdname as.mic
|
||||
#' @details `NA_mic_` is a missing value of the new `<mic>` class, analogous to e.g. base \R's [`NA_character_`][base::NA].
|
||||
#' @format NULL
|
||||
#' @export
|
||||
NA_mic_ <- set_clean_class(factor(NA, levels = valid_mic_levels, ordered = TRUE),
|
||||
new_class = c("mic", "ordered", "factor"))
|
||||
|
||||
#' @rdname as.mic
|
||||
#' @export
|
||||
is.mic <- function(x) {
|
||||
inherits(x, "mic")
|
||||
}
|
||||
|
||||
#' @method as.double mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
as.double.mic <- function(x, ...) {
|
||||
as.double(gsub("[<=>]+", "", as.character(x), perl = TRUE))
|
||||
}
|
||||
|
||||
#' @method as.numeric mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
as.numeric.mic <- function(x, ...) {
|
||||
as.numeric(gsub("[<=>]+", "", as.character(x), perl = TRUE))
|
||||
}
|
||||
|
||||
#' @rdname as.mic
|
||||
#' @method droplevels mic
|
||||
#' @param as.mic a [logical] to indicate whether the `<mic>` class should be kept, defaults to `FALSE`
|
||||
#' @export
|
||||
droplevels.mic <- function(x, as.mic = FALSE, ...) {
|
||||
x <- droplevels.factor(x, ...)
|
||||
if (as.mic == TRUE) {
|
||||
class(x) <- c("mic", "ordered", "factor")
|
||||
}
|
||||
x
|
||||
}
|
||||
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
pillar_shaft.mic <- function(x, ...) {
|
||||
crude_numbers <- as.double(x)
|
||||
operators <- gsub("[^<=>]+", "", as.character(x))
|
||||
operators[!is.na(operators) & operators != ""] <- font_silver(operators[!is.na(operators) & operators != ""], collapse = NULL)
|
||||
out <- trimws(paste0(operators, trimws(format(crude_numbers))))
|
||||
out[is.na(x)] <- font_na(NA)
|
||||
# maketrailing zeroes almost invisible
|
||||
out[out %like% "[.]"] <- gsub("([.]?0+)$", font_white("\\1"), out[out %like% "[.]"], perl = TRUE)
|
||||
create_pillar_column(out, align = "right", width = max(nchar(font_stripstyle(out))))
|
||||
}
|
||||
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
type_sum.mic <- function(x, ...) {
|
||||
"mic"
|
||||
}
|
||||
|
||||
#' @method print mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
print.mic <- function(x, ...) {
|
||||
cat("Class <mic>",
|
||||
ifelse(length(levels(x)) < length(valid_mic_levels), font_red(" with dropped levels"), ""),
|
||||
"\n", sep = "")
|
||||
print(as.character(x), quote = FALSE)
|
||||
att <- attributes(x)
|
||||
if ("na.action" %in% names(att)) {
|
||||
cat(font_silver(paste0("(NA ", class(att$na.action), ": ", paste0(att$na.action, collapse = ", "), ")\n")))
|
||||
}
|
||||
}
|
||||
|
||||
#' @method summary mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
summary.mic <- function(object, ...) {
|
||||
summary(as.double(object), ...)
|
||||
}
|
||||
|
||||
#' @method as.matrix mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
as.matrix.mic <- function(x, ...) {
|
||||
as.matrix(as.double(x), ...)
|
||||
}
|
||||
|
||||
#' @method [ mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[.mic" <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
#' @method [[ mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[[.mic" <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
#' @method [<- mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[<-.mic" <- function(i, j, ..., value) {
|
||||
value <- as.mic(value)
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(i)
|
||||
y
|
||||
}
|
||||
#' @method [[<- mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[[<-.mic" <- function(i, j, ..., value) {
|
||||
value <- as.mic(value)
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(i)
|
||||
y
|
||||
}
|
||||
#' @method c mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
c.mic <- function(...) {
|
||||
as.mic(unlist(lapply(list(...), as.character)))
|
||||
}
|
||||
|
||||
#' @method unique mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
unique.mic <- function(x, incomparables = FALSE, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
|
||||
#' @method rep mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
rep.mic <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
|
||||
#' @method sort mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
sort.mic <- function(x, decreasing = FALSE, ...) {
|
||||
if (decreasing == TRUE) {
|
||||
ord <- order(-as.double(x))
|
||||
} else {
|
||||
ord <- order(as.double(x))
|
||||
}
|
||||
x[ord]
|
||||
}
|
||||
|
||||
#' @method hist mic
|
||||
#' @importFrom graphics hist
|
||||
#' @export
|
||||
#' @noRd
|
||||
hist.mic <- function(x, ...) {
|
||||
warning_("in `hist()`: use `plot()` or ggplot2's `autoplot()` for optimal plotting of MIC values")
|
||||
hist(log2(x))
|
||||
}
|
||||
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
get_skimmers.mic <- function(column) {
|
||||
skimr::sfl(
|
||||
skim_type = "mic",
|
||||
p0 = ~stats::quantile(., probs = 0, na.rm = TRUE, names = FALSE),
|
||||
p25 = ~stats::quantile(., probs = 0.25, na.rm = TRUE, names = FALSE),
|
||||
p50 = ~stats::quantile(., probs = 0.5, na.rm = TRUE, names = FALSE),
|
||||
p75 = ~stats::quantile(., probs = 0.75, na.rm = TRUE, names = FALSE),
|
||||
p100 = ~stats::quantile(., probs = 1, na.rm = TRUE, names = FALSE),
|
||||
hist = ~skimr::inline_hist(log2(stats::na.omit(.)), 5)
|
||||
)
|
||||
}
|
||||
|
||||
# Miscellaneous mathematical functions ------------------------------------
|
||||
|
||||
#' @method mean mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
mean.mic <- function(x, trim = 0, na.rm = FALSE, ...) {
|
||||
mean(as.double(x), trim = trim, na.rm = na.rm, ...)
|
||||
}
|
||||
|
||||
#' @method median mic
|
||||
#' @importFrom stats median
|
||||
#' @export
|
||||
#' @noRd
|
||||
median.mic <- function(x, na.rm = FALSE, ...) {
|
||||
median(as.double(x), na.rm = na.rm, ...)
|
||||
}
|
||||
|
||||
#' @method quantile mic
|
||||
#' @importFrom stats quantile
|
||||
#' @export
|
||||
#' @noRd
|
||||
quantile.mic <- function(x, probs = seq(0, 1, 0.25), na.rm = FALSE,
|
||||
names = TRUE, type = 7, ...) {
|
||||
quantile(as.double(x), probs = probs, na.rm = na.rm, names = names, type = type, ...)
|
||||
}
|
||||
|
||||
# Math (see ?groupGeneric) ----------------------------------------------
|
||||
|
||||
#' @method abs mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
abs.mic <- function(x) {
|
||||
abs(as.double(x))
|
||||
}
|
||||
#' @method sign mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
sign.mic <- function(x) {
|
||||
sign(as.double(x))
|
||||
}
|
||||
#' @method sqrt mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
sqrt.mic <- function(x) {
|
||||
sqrt(as.double(x))
|
||||
}
|
||||
#' @method floor mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
floor.mic <- function(x) {
|
||||
floor(as.double(x))
|
||||
}
|
||||
#' @method ceiling mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
ceiling.mic <- function(x) {
|
||||
ceiling(as.double(x))
|
||||
}
|
||||
#' @method trunc mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
trunc.mic <- function(x, ...) {
|
||||
trunc(as.double(x), ...)
|
||||
}
|
||||
#' @method round mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
round.mic <- function(x, digits = 0) {
|
||||
round(as.double(x), digits = digits)
|
||||
}
|
||||
#' @method signif mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
signif.mic <- function(x, digits = 6) {
|
||||
signif(as.double(x), digits = digits)
|
||||
}
|
||||
#' @method exp mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
exp.mic <- function(x) {
|
||||
exp(as.double(x))
|
||||
}
|
||||
#' @method log mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
log.mic <- function(x, base = exp(1)) {
|
||||
log(as.double(x), base = base)
|
||||
}
|
||||
#' @method log10 mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
log10.mic <- function(x) {
|
||||
log10(as.double(x))
|
||||
}
|
||||
#' @method log2 mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
log2.mic <- function(x) {
|
||||
log2(as.double(x))
|
||||
}
|
||||
#' @method expm1 mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
expm1.mic <- function(x) {
|
||||
expm1(as.double(x))
|
||||
}
|
||||
#' @method log1p mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
log1p.mic <- function(x) {
|
||||
log1p(as.double(x))
|
||||
}
|
||||
#' @method cos mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
cos.mic <- function(x) {
|
||||
cos(as.double(x))
|
||||
}
|
||||
#' @method sin mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
sin.mic <- function(x) {
|
||||
sin(as.double(x))
|
||||
}
|
||||
#' @method tan mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
tan.mic <- function(x) {
|
||||
tan(as.double(x))
|
||||
}
|
||||
#' @method cospi mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
cospi.mic <- function(x) {
|
||||
cospi(as.double(x))
|
||||
}
|
||||
#' @method sinpi mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
sinpi.mic <- function(x) {
|
||||
sinpi(as.double(x))
|
||||
}
|
||||
#' @method tanpi mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
tanpi.mic <- function(x) {
|
||||
tanpi(as.double(x))
|
||||
}
|
||||
#' @method acos mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
acos.mic <- function(x) {
|
||||
acos(as.double(x))
|
||||
}
|
||||
#' @method asin mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
asin.mic <- function(x) {
|
||||
asin(as.double(x))
|
||||
}
|
||||
#' @method atan mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
atan.mic <- function(x) {
|
||||
atan(as.double(x))
|
||||
}
|
||||
#' @method cosh mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
cosh.mic <- function(x) {
|
||||
cosh(as.double(x))
|
||||
}
|
||||
#' @method sinh mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
sinh.mic <- function(x) {
|
||||
sinh(as.double(x))
|
||||
}
|
||||
#' @method tanh mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
tanh.mic <- function(x) {
|
||||
tanh(as.double(x))
|
||||
}
|
||||
#' @method acosh mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
acosh.mic <- function(x) {
|
||||
acosh(as.double(x))
|
||||
}
|
||||
#' @method asinh mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
asinh.mic <- function(x) {
|
||||
asinh(as.double(x))
|
||||
}
|
||||
#' @method atanh mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
atanh.mic <- function(x) {
|
||||
atanh(as.double(x))
|
||||
}
|
||||
#' @method lgamma mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
lgamma.mic <- function(x) {
|
||||
lgamma(as.double(x))
|
||||
}
|
||||
#' @method gamma mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
gamma.mic <- function(x) {
|
||||
gamma(as.double(x))
|
||||
}
|
||||
#' @method digamma mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
digamma.mic <- function(x) {
|
||||
digamma(as.double(x))
|
||||
}
|
||||
#' @method trigamma mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
trigamma.mic <- function(x) {
|
||||
trigamma(as.double(x))
|
||||
}
|
||||
#' @method cumsum mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
cumsum.mic <- function(x) {
|
||||
cumsum(as.double(x))
|
||||
}
|
||||
#' @method cumprod mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
cumprod.mic <- function(x) {
|
||||
cumprod(as.double(x))
|
||||
}
|
||||
#' @method cummax mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
cummax.mic <- function(x) {
|
||||
cummax(as.double(x))
|
||||
}
|
||||
#' @method cummin mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
cummin.mic <- function(x) {
|
||||
cummin(as.double(x))
|
||||
}
|
||||
|
||||
# Ops (see ?groupGeneric) -----------------------------------------------
|
||||
|
||||
is_greater <- function(el) {
|
||||
el %like_case% ">[0-9]"
|
||||
}
|
||||
is_lower <- function(el) {
|
||||
el %like_case% "<[0-9]"
|
||||
}
|
||||
|
||||
#' @method + mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`+.mic` <- function(e1, e2) {
|
||||
as.double(e1) + as.double(e2)
|
||||
}
|
||||
|
||||
#' @method - mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`-.mic` <- function(e1, e2) {
|
||||
as.double(e1) - as.double(e2)
|
||||
}
|
||||
|
||||
#' @method * mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`*.mic` <- function(e1, e2) {
|
||||
as.double(e1) * as.double(e2)
|
||||
}
|
||||
|
||||
#' @method / mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`/.mic` <- function(e1, e2) {
|
||||
as.double(e1) / as.double(e2)
|
||||
}
|
||||
|
||||
#' @method ^ mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`^.mic` <- function(e1, e2) {
|
||||
as.double(e1) ^ as.double(e2)
|
||||
}
|
||||
|
||||
#' @method %% mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`%%.mic` <- function(e1, e2) {
|
||||
as.double(e1) %% as.double(e2)
|
||||
}
|
||||
|
||||
#' @method %/% mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`%/%.mic` <- function(e1, e2) {
|
||||
as.double(e1) %/% as.double(e2)
|
||||
}
|
||||
|
||||
#' @method & mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`&.mic` <- function(e1, e2) {
|
||||
as.double(e1) & as.double(e2)
|
||||
}
|
||||
|
||||
#' @method | mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`|.mic` <- function(e1, e2) {
|
||||
as.double(e1) | as.double(e2)
|
||||
}
|
||||
|
||||
#' @method ! mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`!.mic` <- function(x) {
|
||||
!as.double(x)
|
||||
}
|
||||
|
||||
#' @method == mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`==.mic` <- function(e1, e2) {
|
||||
as.double(e1) == as.double(e2)
|
||||
}
|
||||
|
||||
#' @method != mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`!=.mic` <- function(e1, e2) {
|
||||
as.double(e1) != as.double(e2)
|
||||
}
|
||||
|
||||
#' @method < mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`<.mic` <- function(e1, e2) {
|
||||
as.double(e1) < as.double(e2)
|
||||
}
|
||||
|
||||
#' @method <= mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`<=.mic` <- function(e1, e2) {
|
||||
as.double(e1) <= as.double(e2)
|
||||
}
|
||||
|
||||
#' @method >= mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`>=.mic` <- function(e1, e2) {
|
||||
as.double(e1) >= as.double(e2)
|
||||
}
|
||||
|
||||
#' @method > mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
`>.mic` <- function(e1, e2) {
|
||||
as.double(e1) > as.double(e2)
|
||||
# doesn't work...
|
||||
# nolint start
|
||||
# as.double(e1) > as.double(e2) |
|
||||
# (as.double(e1) == as.double(e2) & is_lower(e2) & !is_lower(e1)) |
|
||||
# (as.double(e1) == as.double(e2) & is_greater(e1) & !is_greater(e2))
|
||||
# nolint end
|
||||
}
|
||||
|
||||
# Summary (see ?groupGeneric) -------------------------------------------
|
||||
|
||||
#' @method all mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
all.mic <- function(..., na.rm = FALSE) {
|
||||
all(as.double(c(...)), na.rm = na.rm)
|
||||
}
|
||||
#' @method any mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
any.mic <- function(..., na.rm = FALSE) {
|
||||
any(as.double(c(...)), na.rm = na.rm)
|
||||
}
|
||||
#' @method sum mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
sum.mic <- function(..., na.rm = FALSE) {
|
||||
sum(as.double(c(...)), na.rm = na.rm)
|
||||
}
|
||||
#' @method prod mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
prod.mic <- function(..., na.rm = FALSE) {
|
||||
prod(as.double(c(...)), na.rm = na.rm)
|
||||
}
|
||||
#' @method min mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
min.mic <- function(..., na.rm = FALSE) {
|
||||
min(as.double(c(...)), na.rm = na.rm)
|
||||
}
|
||||
#' @method max mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
max.mic <- function(..., na.rm = FALSE) {
|
||||
max(as.double(c(...)), na.rm = na.rm)
|
||||
}
|
||||
#' @method range mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
range.mic <- function(..., na.rm = FALSE) {
|
||||
range(as.double(c(...)), na.rm = na.rm)
|
||||
}
|
||||
@@ -1,103 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Calculate the Matching Score for Microorganisms
|
||||
#'
|
||||
#' This algorithm is used by [as.mo()] and all the [`mo_*`][mo_property()] functions to determine the most probable match of taxonomic records based on user input.
|
||||
#' @author Dr Matthijs Berends
|
||||
#' @param x Any user input value(s)
|
||||
#' @param n A full taxonomic name, that exists in [`microorganisms$fullname`][microorganisms]
|
||||
#' @section Matching Score for Microorganisms:
|
||||
#' With ambiguous user input in [as.mo()] and all the [`mo_*`][mo_property()] functions, the returned results are chosen based on their matching score using [mo_matching_score()]. This matching score \eqn{m}, is calculated as:
|
||||
#'
|
||||
#' \ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{\ifelse{html}{\figure{mo_matching_score.png}{options: width="300" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}}
|
||||
#'
|
||||
#' where:
|
||||
#'
|
||||
#' * \ifelse{html}{\out{<i>x</i> is the user input;}}{\eqn{x} is the user input;}
|
||||
#' * \ifelse{html}{\out{<i>n</i> is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
|
||||
#' * \ifelse{html}{\out{<i>l<sub>n</sub></i> is the length of <i>n</i>;}}{l_n is the length of \eqn{n};}
|
||||
#' * \ifelse{html}{\out{<i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change <i>x</i> into <i>n</i>;}}{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};}
|
||||
#' * \ifelse{html}{\out{<i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
|
||||
#' * \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
|
||||
#'
|
||||
#' The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. **Group 1** (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is *Enterococcus*, *Staphylococcus* or *Streptococcus*. This group consequently contains all common Gram-negative bacteria, such as *Pseudomonas* and *Legionella* and all species within the order Enterobacterales. **Group 2** consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is *Absidia*, *Acremonium*, *Actinotignum*, *Alternaria*, *Anaerosalibacter*, *Apophysomyces*, *Arachnia*, *Aspergillus*, *Aureobacterium*, *Aureobasidium*, *Bacteroides*, *Basidiobolus*, *Beauveria*, *Blastocystis*, *Branhamella*, *Calymmatobacterium*, *Candida*, *Capnocytophaga*, *Catabacter*, *Chaetomium*, *Chryseobacterium*, *Chryseomonas*, *Chrysonilia*, *Cladophialophora*, *Cladosporium*, *Conidiobolus*, *Cryptococcus*, *Curvularia*, *Exophiala*, *Exserohilum*, *Flavobacterium*, *Fonsecaea*, *Fusarium*, *Fusobacterium*, *Hendersonula*, *Hypomyces*, *Koserella*, *Lelliottia*, *Leptosphaeria*, *Leptotrichia*, *Malassezia*, *Malbranchea*, *Mortierella*, *Mucor*, *Mycocentrospora*, *Mycoplasma*, *Nectria*, *Ochroconis*, *Oidiodendron*, *Phoma*, *Piedraia*, *Pithomyces*, *Pityrosporum*, *Prevotella*, *Pseudallescheria*, *Rhizomucor*, *Rhizopus*, *Rhodotorula*, *Scolecobasidium*, *Scopulariopsis*, *Scytalidium*, *Sporobolomyces*, *Stachybotrys*, *Stomatococcus*, *Treponema*, *Trichoderma*, *Trichophyton*, *Trichosporon*, *Tritirachium* or *Ureaplasma*. **Group 3** consists of all other microorganisms.
|
||||
#'
|
||||
#' All characters in \eqn{x} and \eqn{n} are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.
|
||||
#'
|
||||
#' All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., `"E. coli"` will return the microbial ID of *Escherichia coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Escherichia coli"), 3)`}, a highly prevalent microorganism found in humans) and not *Entamoeba coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Entamoeba coli"), 3)`}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
|
||||
#'
|
||||
#' Since `AMR` version 1.8.1, common microorganism abbreviations are ignored in determining the matching score. These abbreviations are currently: `r vector_and(pkg_env$mo_field_abbreviations, quotes = FALSE)`.
|
||||
#' @export
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @examples
|
||||
#' as.mo("E. coli")
|
||||
#' mo_uncertainties()
|
||||
#'
|
||||
#' mo_matching_score(x = "E. coli",
|
||||
#' n = c("Escherichia coli", "Entamoeba coli"))
|
||||
mo_matching_score <- function(x, n) {
|
||||
meet_criteria(x, allow_class = c("character", "data.frame", "list"))
|
||||
meet_criteria(n, allow_class = "character")
|
||||
|
||||
x <- parse_and_convert(x)
|
||||
# no dots and other non-whitespace characters
|
||||
x <- gsub("[^a-zA-Z0-9 \\(\\)]+", "", x)
|
||||
|
||||
# remove abbreviations known to the field
|
||||
x <- gsub(paste0("(^|[^a-z0-9]+)(",
|
||||
paste0(pkg_env$mo_field_abbreviations, collapse = "|"),
|
||||
")([^a-z0-9]+|$)"),
|
||||
"", x, perl = TRUE, ignore.case = TRUE)
|
||||
|
||||
# only keep one space
|
||||
x <- gsub(" +", " ", x)
|
||||
|
||||
# n is always a taxonomically valid full name
|
||||
if (length(n) == 1) {
|
||||
n <- rep(n, length(x))
|
||||
}
|
||||
if (length(x) == 1) {
|
||||
x <- rep(x, length(n))
|
||||
}
|
||||
|
||||
# length of fullname
|
||||
l_n <- nchar(n)
|
||||
lev <- double(length = length(x))
|
||||
l_n.lev <- double(length = length(x))
|
||||
for (i in seq_len(length(x))) {
|
||||
# determine Levenshtein distance, but maximise to nchar of n
|
||||
lev[i] <- utils::adist(x[i], n[i], ignore.case = FALSE, fixed = TRUE, costs = c(ins = 1, del = 1, sub = 1))
|
||||
# minimum of (l_n, Levenshtein distance)
|
||||
l_n.lev[i] <- min(l_n[i], as.double(lev[i]))
|
||||
}
|
||||
# human pathogenic prevalence (1 to 3), see ?as.mo
|
||||
p_n <- MO_lookup[match(n, MO_lookup$fullname), "prevalence", drop = TRUE]
|
||||
# kingdom index (Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5)
|
||||
k_n <- MO_lookup[match(n, MO_lookup$fullname), "kingdom_index", drop = TRUE]
|
||||
|
||||
# matching score:
|
||||
(l_n - 0.5 * l_n.lev) / (l_n * p_n * k_n)
|
||||
}
|
||||
-761
@@ -1,761 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Get Properties of a Microorganism
|
||||
#'
|
||||
#' Use these functions to return a specific property of a microorganism based on the latest accepted taxonomy. All input values will be evaluated internally with [as.mo()], which makes it possible to use microbial abbreviations, codes and names as input. See *Examples*.
|
||||
#' @param x any [character] (vector) that can be coerced to a valid microorganism code with [as.mo()]. Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, see *Examples*.
|
||||
#' @param property one of the column names of the [microorganisms] data set: `r vector_or(colnames(microorganisms), sort = FALSE, quotes = TRUE)`, or must be `"shortname"`
|
||||
#' @param language language of the returned text, defaults to system language (see [get_AMR_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Also used to translate text like "no growth". Use `language = NULL` or `language = ""` to prevent translation.
|
||||
#' @param ... other arguments passed on to [as.mo()], such as 'allow_uncertain' and 'ignore_pattern'
|
||||
#' @param ab any (vector of) text that can be coerced to a valid antibiotic code with [as.ab()]
|
||||
#' @param open browse the URL using [`browseURL()`][utils::browseURL()]
|
||||
#' @details All functions will return the most recently known taxonomic property according to the Catalogue of Life, except for [mo_ref()], [mo_authors()] and [mo_year()]. Please refer to this example, knowing that *Escherichia blattae* was renamed to *Shimwellia blattae* in 2010:
|
||||
#' - `mo_name("Escherichia blattae")` will return `"Shimwellia blattae"` (with a message about the renaming)
|
||||
#' - `mo_ref("Escherichia blattae")` will return `"Burgess et al., 1973"` (with a message about the renaming)
|
||||
#' - `mo_ref("Shimwellia blattae")` will return `"Priest et al., 2010"` (without a message)
|
||||
#'
|
||||
#' The short name - [mo_shortname()] - almost always returns the first character of the genus and the full species, like `"E. coli"`. Exceptions are abbreviations of staphylococci (such as *"CoNS"*, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as *"GBS"*, Group B Streptococci). Please bear in mind that e.g. *E. coli* could mean *Escherichia coli* (kingdom of Bacteria) as well as *Entamoeba coli* (kingdom of Protozoa). Returning to the full name will be done using [as.mo()] internally, giving priority to bacteria and human pathogens, i.e. `"E. coli"` will be considered *Escherichia coli*. In other words, `mo_fullname(mo_shortname("Entamoeba coli"))` returns `"Escherichia coli"`.
|
||||
#'
|
||||
#' Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions [mo_kingdom()] and [mo_domain()] return the exact same results.
|
||||
#'
|
||||
#' The Gram stain - [mo_gramstain()] - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318)), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive, except for members of the class Negativicutes which are Gram-negative. Members of other bacterial phyla are all considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [mo_is_gram_negative()] and [mo_is_gram_positive()] always return `TRUE` or `FALSE` (except when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
|
||||
#'
|
||||
#' Determination of yeasts - [mo_is_yeast()] - will be based on the taxonomic kingdom and class. *Budding yeasts* are fungi of the phylum Ascomycetes, class Saccharomycetes (also called Hemiascomycetes). *True yeasts* are aggregated into the underlying order Saccharomycetales. Thus, for all microorganisms that are fungi and member of the taxonomic class Saccharomycetes, the function will return `TRUE`. It returns `FALSE` otherwise (except when the input is `NA` or the MO code is `UNKNOWN`).
|
||||
#'
|
||||
#' Intrinsic resistance - [mo_is_intrinsic_resistant()] - will be determined based on the [intrinsic_resistant] data set, which is based on `r format_eucast_version_nr(3.3)`. The [mo_is_intrinsic_resistant()] functions can be vectorised over arguments `x` (input for microorganisms) and over `ab` (input for antibiotics).
|
||||
#'
|
||||
#' All output [will be translated][translate] where possible.
|
||||
#'
|
||||
#' The function [mo_url()] will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.
|
||||
#'
|
||||
#' SNOMED codes - [mo_snomed()] - are from the `r SNOMED_VERSION$current_source`. See *Source* and the [microorganisms] data set for more info.
|
||||
#' @inheritSection mo_matching_score Matching Score for Microorganisms
|
||||
#' @inheritSection catalogue_of_life Catalogue of Life
|
||||
#' @inheritSection as.mo Source
|
||||
#' @rdname mo_property
|
||||
#' @name mo_property
|
||||
#' @return
|
||||
#' - An [integer] in case of [mo_year()]
|
||||
#' - A [list] in case of [mo_taxonomy()] and [mo_info()]
|
||||
#' - A named [character] in case of [mo_url()]
|
||||
#' - A [numeric] in case of [mo_snomed()]
|
||||
#' - A [character] in all other cases
|
||||
#' @export
|
||||
#' @seealso Data set [microorganisms]
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @examples
|
||||
#' # taxonomic tree -----------------------------------------------------------
|
||||
#' mo_kingdom("Klebsiella pneumoniae")
|
||||
#' mo_phylum("Klebsiella pneumoniae")
|
||||
#' mo_class("Klebsiella pneumoniae")
|
||||
#' mo_order("Klebsiella pneumoniae")
|
||||
#' mo_family("Klebsiella pneumoniae")
|
||||
#' mo_genus("Klebsiella pneumoniae")
|
||||
#' mo_species("Klebsiella pneumoniae")
|
||||
#' mo_subspecies("Klebsiella pneumoniae")
|
||||
#'
|
||||
#' # colloquial properties ----------------------------------------------------
|
||||
#' mo_name("Klebsiella pneumoniae")
|
||||
#' mo_fullname("Klebsiella pneumoniae")
|
||||
#' mo_shortname("Klebsiella pneumoniae")
|
||||
#'
|
||||
#' # other properties ---------------------------------------------------------
|
||||
#' mo_gramstain("Klebsiella pneumoniae")
|
||||
#' mo_snomed("Klebsiella pneumoniae")
|
||||
#' mo_type("Klebsiella pneumoniae")
|
||||
#' mo_rank("Klebsiella pneumoniae")
|
||||
#' mo_url("Klebsiella pneumoniae")
|
||||
#' mo_synonyms("Klebsiella pneumoniae")
|
||||
#'
|
||||
#' # scientific reference -----------------------------------------------------
|
||||
#' mo_ref("Klebsiella pneumoniae")
|
||||
#' mo_authors("Klebsiella pneumoniae")
|
||||
#' mo_year("Klebsiella pneumoniae")
|
||||
#' mo_lpsn("Klebsiella pneumoniae")
|
||||
#'
|
||||
#' # abbreviations known in the field -----------------------------------------
|
||||
#' mo_genus("MRSA")
|
||||
#' mo_species("MRSA")
|
||||
#' mo_shortname("VISA")
|
||||
#' mo_gramstain("VISA")
|
||||
#'
|
||||
#' mo_genus("EHEC")
|
||||
#' mo_species("EHEC")
|
||||
#'
|
||||
#' # known subspecies ---------------------------------------------------------
|
||||
#' mo_name("doylei")
|
||||
#' mo_genus("doylei")
|
||||
#' mo_species("doylei")
|
||||
#' mo_subspecies("doylei")
|
||||
#'
|
||||
#' mo_fullname("K. pneu rh")
|
||||
#' mo_shortname("K. pneu rh")
|
||||
#'
|
||||
#' \donttest{
|
||||
#' # Becker classification, see ?as.mo ----------------------------------------
|
||||
#' mo_fullname("S. epi")
|
||||
#' mo_fullname("S. epi", Becker = TRUE)
|
||||
#' mo_shortname("S. epi")
|
||||
#' mo_shortname("S. epi", Becker = TRUE)
|
||||
#'
|
||||
#' # Lancefield classification, see ?as.mo ------------------------------------
|
||||
#' mo_fullname("S. pyo")
|
||||
#' mo_fullname("S. pyo", Lancefield = TRUE)
|
||||
#' mo_shortname("S. pyo")
|
||||
#' mo_shortname("S. pyo", Lancefield = TRUE)
|
||||
#'
|
||||
#'
|
||||
#' # language support --------------------------------------------------------
|
||||
#' mo_gramstain("Klebsiella pneumoniae", language = "de")
|
||||
#' mo_gramstain("Klebsiella pneumoniae", language = "nl")
|
||||
#' mo_gramstain("Klebsiella pneumoniae", language = "es")
|
||||
#'
|
||||
#' # mo_type is equal to mo_kingdom, but mo_kingdom will remain official
|
||||
#' mo_kingdom("Klebsiella pneumoniae")
|
||||
#' mo_type("Klebsiella pneumoniae")
|
||||
#' mo_type("Klebsiella pneumoniae")
|
||||
#'
|
||||
#' mo_fullname("S. pyogenes",
|
||||
#' Lancefield = TRUE,
|
||||
#' language = "de")
|
||||
#' mo_fullname("S. pyogenes",
|
||||
#' Lancefield = TRUE,
|
||||
#' language = "nl")
|
||||
#'
|
||||
#'
|
||||
#' # other --------------------------------------------------------------------
|
||||
#'
|
||||
#' mo_is_yeast(c("Candida", "Trichophyton", "Klebsiella"))
|
||||
#'
|
||||
#' # gram stains and intrinsic resistance can be used as a filter in dplyr verbs
|
||||
#' if (require("dplyr")) {
|
||||
#' example_isolates %>%
|
||||
#' filter(mo_is_gram_positive())
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' filter(mo_is_intrinsic_resistant(ab = "vanco"))
|
||||
#' }
|
||||
#'
|
||||
#'
|
||||
#' # get a list with the complete taxonomy (from kingdom to subspecies)
|
||||
#' mo_taxonomy("Klebsiella pneumoniae")
|
||||
#'
|
||||
#' # get a list with the taxonomy, the authors, Gram-stain,
|
||||
#' # SNOMED codes, and URL to the online database
|
||||
#' mo_info("Klebsiella pneumoniae")
|
||||
#' }
|
||||
mo_name <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_name")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
translate_into_language(mo_validate(x = x, property = "fullname", language = language, ...),
|
||||
language = language,
|
||||
only_unknown = FALSE,
|
||||
only_affect_mo_names = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_fullname <- mo_name
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_shortname <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_shortname")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x.mo <- as.mo(x, language = language, ...)
|
||||
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
replace_empty <- function(x) {
|
||||
x[x == ""] <- "spp."
|
||||
x
|
||||
}
|
||||
|
||||
# get first char of genus and complete species in English
|
||||
genera <- mo_genus(x.mo, language = NULL)
|
||||
shortnames <- paste0(substr(genera, 1, 1), ". ", replace_empty(mo_species(x.mo, language = NULL)))
|
||||
|
||||
# exceptions for where no species is known
|
||||
shortnames[shortnames %like% ".[.] spp[.]"] <- genera[shortnames %like% ".[.] spp[.]"]
|
||||
# exceptions for staphylococci
|
||||
shortnames[shortnames == "S. coagulase-negative"] <- "CoNS"
|
||||
shortnames[shortnames == "S. coagulase-positive"] <- "CoPS"
|
||||
# exceptions for streptococci: Group A Streptococcus -> GAS
|
||||
shortnames[shortnames %like% "S. group [ABCDFGHK]"] <- paste0("G", gsub("S. group ([ABCDFGHK])", "\\1", shortnames[shortnames %like% "S. group [ABCDFGHK]"], perl = TRUE), "S")
|
||||
# unknown species etc.
|
||||
shortnames[shortnames %like% "unknown"] <- paste0("(", trimws(gsub("[^a-zA-Z -]", "", shortnames[shortnames %like% "unknown"], perl = TRUE)), ")")
|
||||
|
||||
shortnames[is.na(x.mo)] <- NA_character_
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
translate_into_language(shortnames, language = language, only_unknown = FALSE, only_affect_mo_names = TRUE)
|
||||
}
|
||||
|
||||
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_subspecies <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_subspecies")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
translate_into_language(mo_validate(x = x, property = "subspecies", language = language, ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_species <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_species")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
translate_into_language(mo_validate(x = x, property = "species", language = language, ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_genus <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_genus")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
translate_into_language(mo_validate(x = x, property = "genus", language = language, ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_family <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_family")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
translate_into_language(mo_validate(x = x, property = "family", language = language, ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_order <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_order")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
translate_into_language(mo_validate(x = x, property = "order", language = language, ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_class <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_class")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
translate_into_language(mo_validate(x = x, property = "class", language = language, ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_phylum <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_phylum")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
translate_into_language(mo_validate(x = x, property = "phylum", language = language, ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_kingdom <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_kingdom")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
translate_into_language(mo_validate(x = x, property = "kingdom", language = language, ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_domain <- mo_kingdom
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_type <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_type")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x.mo <- as.mo(x, language = language, ...)
|
||||
out <- mo_kingdom(x.mo, language = NULL)
|
||||
out[which(mo_is_yeast(x.mo))] <- "Yeasts"
|
||||
translate_into_language(out, language = language, only_unknown = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_gramstain <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_gramstain")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x.mo <- as.mo(x, language = language, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
x <- rep(NA_character_, length(x))
|
||||
# make all bacteria Gram negative
|
||||
x[mo_kingdom(x.mo) == "Bacteria"] <- "Gram-negative"
|
||||
# overwrite these 4 phyla with Gram-positives
|
||||
# Source: https://itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=956097 (Cavalier-Smith, 2002)
|
||||
x[(mo_phylum(x.mo) %in% c("Actinobacteria",
|
||||
"Chloroflexi",
|
||||
"Firmicutes",
|
||||
"Tenericutes") &
|
||||
# but class Negativicutes (of phylum Firmicutes) are Gram-negative!
|
||||
mo_class(x.mo) != "Negativicutes")
|
||||
# and of course our own ID for Gram-positives
|
||||
| x.mo == "B_GRAMP"] <- "Gram-positive"
|
||||
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
translate_into_language(x, language = language, only_unknown = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_is_gram_negative <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_is_gram_negative")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x.mo <- as.mo(x, language = language, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
grams <- mo_gramstain(x.mo, language = NULL)
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
out <- grams == "Gram-negative" & !is.na(grams)
|
||||
out[x.mo %in% c(NA_character_, "UNKNOWN")] <- NA
|
||||
out
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_is_gram_positive <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_is_gram_positive")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x.mo <- as.mo(x, language = language, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
grams <- mo_gramstain(x.mo, language = NULL)
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
out <- grams == "Gram-positive" & !is.na(grams)
|
||||
out[x.mo %in% c(NA_character_, "UNKNOWN")] <- NA
|
||||
out
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_is_yeast <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_is_yeast")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x.mo <- as.mo(x, language = language, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
x.kingdom <- mo_kingdom(x.mo, language = NULL)
|
||||
x.class <- mo_class(x.mo, language = NULL)
|
||||
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
|
||||
out <- rep(FALSE, length(x))
|
||||
out[x.kingdom == "Fungi" & x.class == "Saccharomycetes"] <- TRUE
|
||||
out[x.mo %in% c(NA_character_, "UNKNOWN")] <- NA
|
||||
out
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_is_intrinsic_resistant <- function(x, ab, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_is_intrinsic_resistant")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(ab, allow_NA = FALSE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x <- as.mo(x, language = language, ...)
|
||||
ab <- as.ab(ab, language = NULL, flag_multiple_results = FALSE, info = FALSE)
|
||||
|
||||
if (length(x) == 1 & length(ab) > 1) {
|
||||
x <- rep(x, length(ab))
|
||||
} else if (length(ab) == 1 & length(x) > 1) {
|
||||
ab <- rep(ab, length(x))
|
||||
}
|
||||
if (length(x) != length(ab)) {
|
||||
stop_("length of `x` and `ab` must be equal, or one of them must be of length 1.")
|
||||
}
|
||||
|
||||
# show used version number once per session (pkg_env will reload every session)
|
||||
if (message_not_thrown_before("mo_is_intrinsic_resistant", "version.mo", entire_session = TRUE)) {
|
||||
message_("Determining intrinsic resistance based on ",
|
||||
format_eucast_version_nr(3.3, markdown = FALSE), ". ",
|
||||
font_red("This note will be shown once per session."))
|
||||
}
|
||||
|
||||
# runs against internal vector: INTRINSIC_R (see zzz.R)
|
||||
paste(x, ab) %in% INTRINSIC_R
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_snomed <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_snomed")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
mo_validate(x = x, property = "snomed", language = language, ...)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_ref <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_ref")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
mo_validate(x = x, property = "ref", language = language, ...)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_authors <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_authors")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x <- mo_validate(x = x, property = "ref", language = language, ...)
|
||||
# remove last 4 digits and presumably the comma and space that preceed them
|
||||
x[!is.na(x)] <- gsub(",? ?[0-9]{4}", "", x[!is.na(x)], perl = TRUE)
|
||||
suppressWarnings(x)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_year <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_year")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x <- mo_validate(x = x, property = "ref", language = language, ...)
|
||||
# get last 4 digits
|
||||
x[!is.na(x)] <- gsub(".*([0-9]{4})$", "\\1", x[!is.na(x)], perl = TRUE)
|
||||
suppressWarnings(as.integer(x))
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_lpsn <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_rank")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
mo_validate(x = x, property = "species_id", language = language, ...)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_rank <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_rank")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
mo_validate(x = x, property = "rank", language = language, ...)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_taxonomy <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_taxonomy")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x <- as.mo(x, language = language, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
out <- list(kingdom = mo_kingdom(x, language = language),
|
||||
phylum = mo_phylum(x, language = language),
|
||||
class = mo_class(x, language = language),
|
||||
order = mo_order(x, language = language),
|
||||
family = mo_family(x, language = language),
|
||||
genus = mo_genus(x, language = language),
|
||||
species = mo_species(x, language = language),
|
||||
subspecies = mo_subspecies(x, language = language))
|
||||
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
out
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_synonyms <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_synonyms")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x <- as.mo(x, language = language, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
IDs <- mo_name(x = x, language = NULL)
|
||||
syns <- lapply(IDs, function(newname) {
|
||||
res <- sort(microorganisms.old[which(microorganisms.old$fullname_new == newname), "fullname"])
|
||||
if (length(res) == 0) {
|
||||
NULL
|
||||
} else {
|
||||
res
|
||||
}
|
||||
})
|
||||
if (length(syns) > 1) {
|
||||
names(syns) <- mo_name(x)
|
||||
result <- syns
|
||||
} else {
|
||||
result <- unlist(syns)
|
||||
}
|
||||
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
result
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_info <- function(x, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_info")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x <- as.mo(x, language = language, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
info <- lapply(x, function(y)
|
||||
c(mo_taxonomy(y, language = language),
|
||||
list(synonyms = mo_synonyms(y),
|
||||
gramstain = mo_gramstain(y, language = language),
|
||||
url = unname(mo_url(y, open = FALSE)),
|
||||
ref = mo_ref(y),
|
||||
snomed = unlist(mo_snomed(y)))))
|
||||
if (length(info) > 1) {
|
||||
names(info) <- mo_name(x)
|
||||
result <- info
|
||||
} else {
|
||||
result <- info[[1L]]
|
||||
}
|
||||
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
result
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_url <- function(x, open = FALSE, language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_url")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(open, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
x.mo <- as.mo(x = x, language = language, ... = ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
df <- microorganisms[match(x.mo, microorganisms$mo), c("mo", "fullname", "source", "kingdom", "rank")]
|
||||
df$url <- ifelse(df$source == "LPSN",
|
||||
paste0(CATALOGUE_OF_LIFE$url_LPSN, "/species/", gsub(" ", "-", tolower(df$fullname), fixed = TRUE)),
|
||||
paste0(CATALOGUE_OF_LIFE$url_CoL, "/data/search?type=EXACT&q=", gsub(" ", "%20", df$fullname, fixed = TRUE)))
|
||||
|
||||
genera <- which(df$kingdom == "Bacteria" & df$rank == "genus")
|
||||
df$url[genera] <- gsub("/species/", "/genus/", df$url[genera], fixed = TRUE)
|
||||
subsp <- which(df$kingdom == "Bacteria" & df$rank %in% c("subsp.", "infraspecies"))
|
||||
df$url[subsp] <- gsub("/species/", "/subspecies/", df$url[subsp], fixed = TRUE)
|
||||
|
||||
u <- df$url
|
||||
names(u) <- df$fullname
|
||||
|
||||
if (isTRUE(open)) {
|
||||
if (length(u) > 1) {
|
||||
warning_("in `mo_url()`: only the first URL will be opened, as `browseURL()` only suports one string.")
|
||||
}
|
||||
utils::browseURL(u[1L])
|
||||
}
|
||||
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
u
|
||||
}
|
||||
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_property <- function(x, property = "fullname", language = get_AMR_locale(), ...) {
|
||||
if (missing(x)) {
|
||||
# this tries to find the data and an <mo> column
|
||||
x <- find_mo_col(fn = "mo_property")
|
||||
}
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(property, allow_class = "character", has_length = 1, is_in = colnames(microorganisms))
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
|
||||
translate_into_language(mo_validate(x = x, property = property, language = language, ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
mo_validate <- function(x, property, language, ...) {
|
||||
check_dataset_integrity()
|
||||
dots <- list(...)
|
||||
Becker <- dots$Becker
|
||||
if (is.null(Becker) | property %in% c("kingdom", "phylum", "class", "order", "family", "genus")) {
|
||||
Becker <- FALSE
|
||||
}
|
||||
Lancefield <- dots$Lancefield
|
||||
if (is.null(Lancefield) | property %in% c("kingdom", "phylum", "class", "order", "family", "genus")) {
|
||||
Lancefield <- FALSE
|
||||
}
|
||||
has_Becker_or_Lancefield <- Becker %in% c(TRUE, "all") | Lancefield %in% c(TRUE, "all")
|
||||
|
||||
if (tryCatch(all(x[!is.na(x)] %in% MO_lookup$mo) & !has_Becker_or_Lancefield, error = function(e) FALSE)) {
|
||||
# special case for mo_* functions where class is already <mo>
|
||||
x <- MO_lookup[match(x, MO_lookup$mo), property, drop = TRUE]
|
||||
|
||||
} else {
|
||||
# try to catch an error when inputting an invalid argument
|
||||
# so the 'call.' can be set to FALSE
|
||||
tryCatch(x[1L] %in% MO_lookup[1, property, drop = TRUE],
|
||||
error = function(e) stop(e$message, call. = FALSE))
|
||||
|
||||
if (!all(x[!is.na(x)] %in% MO_lookup[, property, drop = TRUE]) | has_Becker_or_Lancefield) {
|
||||
x <- exec_as.mo(x, property = property, language = language, ...)
|
||||
}
|
||||
}
|
||||
|
||||
if (property == "mo") {
|
||||
return(set_clean_class(x, new_class = c("mo", "character")))
|
||||
} else if (property == "species_id") {
|
||||
return(as.double(x))
|
||||
} else if (property == "snomed") {
|
||||
return(as.double(eval(parse(text = x))))
|
||||
} else {
|
||||
return(x)
|
||||
}
|
||||
}
|
||||
|
||||
find_mo_col <- function(fn) {
|
||||
# this function tries to find an mo column in the data the function was called in,
|
||||
# which is useful when functions are used within dplyr verbs
|
||||
df <- get_current_data(arg_name = "x", call = -3) # will return an error if not found
|
||||
mo <- NULL
|
||||
try({
|
||||
mo <- suppressMessages(search_type_in_df(df, "mo"))
|
||||
}, silent = TRUE)
|
||||
if (!is.null(df) && !is.null(mo) && is.data.frame(df)) {
|
||||
if (message_not_thrown_before(fn = fn)) {
|
||||
message_("Using column '", font_bold(mo), "' as input for `", fn, "()`")
|
||||
}
|
||||
return(df[, mo, drop = TRUE])
|
||||
} else {
|
||||
stop_("argument `x` is missing and no column with info about microorganisms could be found.", call = -2)
|
||||
}
|
||||
}
|
||||
-314
@@ -1,314 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' User-Defined Reference Data Set for Microorganisms
|
||||
#'
|
||||
#' @description These functions can be used to predefine your own reference to be used in [as.mo()] and consequently all [`mo_*`][mo_property()] functions (such as [mo_genus()] and [mo_gramstain()]).
|
||||
#'
|
||||
#' This is **the fastest way** to have your organisation (or analysis) specific codes picked up and translated by this package, since you don't have to bother about it again after setting it up once.
|
||||
#' @param path location of your reference file, this can be any text file (comma-, tab- or pipe-separated) or an Excel file (see *Details*). Can also be `""`, `NULL` or `FALSE` to delete the reference file.
|
||||
#' @param destination destination of the compressed data file, default to the user's home directory.
|
||||
#' @rdname mo_source
|
||||
#' @name mo_source
|
||||
#' @aliases set_mo_source get_mo_source
|
||||
#' @details The reference file can be a text file separated with commas (CSV) or tabs or pipes, an Excel file (either 'xls' or 'xlsx' format) or an \R object file (extension '.rds'). To use an Excel file, you will need to have the `readxl` package installed.
|
||||
#'
|
||||
#' [set_mo_source()] will check the file for validity: it must be a [data.frame], must have a column named `"mo"` which contains values from [`microorganisms$mo`][microorganisms] or [`microorganisms$fullname`][microorganisms] and must have a reference column with your own defined values. If all tests pass, [set_mo_source()] will read the file into \R and will ask to export it to `"~/mo_source.rds"`. The CRAN policy disallows packages to write to the file system, although '*exceptions may be allowed in interactive sessions if the package obtains confirmation from the user*'. For this reason, this function only works in interactive sessions so that the user can **specifically confirm and allow** that this file will be created. The destination of this file can be set with the `destination` argument and defaults to the user's home directory. It can also be set as an \R option, using `options(AMR_mo_source = "my/location/file.rds")`.
|
||||
#'
|
||||
#' The created compressed data file `"mo_source.rds"` will be used at default for MO determination (function [as.mo()] and consequently all `mo_*` functions like [mo_genus()] and [mo_gramstain()]). The location and timestamp of the original file will be saved as an [attribute][base::attributes()] to the compressed data file.
|
||||
#'
|
||||
#' The function [get_mo_source()] will return the data set by reading `"mo_source.rds"` with [readRDS()]. If the original file has changed (by checking the location and timestamp of the original file), it will call [set_mo_source()] to update the data file automatically if used in an interactive session.
|
||||
#'
|
||||
#' Reading an Excel file (`.xlsx`) with only one row has a size of 8-9 kB. The compressed file created with [set_mo_source()] will then have a size of 0.1 kB and can be read by [get_mo_source()] in only a couple of microseconds (millionths of a second).
|
||||
#'
|
||||
#' @section How to Setup:
|
||||
#'
|
||||
#' Imagine this data on a sheet of an Excel file. The first column contains the organisation specific codes, the second column contains valid taxonomic names:
|
||||
#'
|
||||
#' ```
|
||||
#' | A | B |
|
||||
#' --|--------------------|-----------------------|
|
||||
#' 1 | Organisation XYZ | mo |
|
||||
#' 2 | lab_mo_ecoli | Escherichia coli |
|
||||
#' 3 | lab_mo_kpneumoniae | Klebsiella pneumoniae |
|
||||
#' 4 | | |
|
||||
#' ```
|
||||
#'
|
||||
#' We save it as `"home/me/ourcodes.xlsx"`. Now we have to set it as a source:
|
||||
#'
|
||||
#' ```
|
||||
#' set_mo_source("home/me/ourcodes.xlsx")
|
||||
#' #> NOTE: Created mo_source file '/Users/me/mo_source.rds' (0.3 kB) from
|
||||
#' #> '/Users/me/Documents/ourcodes.xlsx' (9 kB), columns
|
||||
#' #> "Organisation XYZ" and "mo"
|
||||
#' ```
|
||||
#'
|
||||
#' It has now created a file `"~/mo_source.rds"` with the contents of our Excel file. Only the first column with foreign values and the 'mo' column will be kept when creating the RDS file.
|
||||
#'
|
||||
#' And now we can use it in our functions:
|
||||
#'
|
||||
#' ```
|
||||
#' as.mo("lab_mo_ecoli")
|
||||
#' #> Class <mo>
|
||||
#' #> [1] B_ESCHR_COLI
|
||||
#'
|
||||
#' mo_genus("lab_mo_kpneumoniae")
|
||||
#' #> [1] "Klebsiella"
|
||||
#'
|
||||
#' # other input values still work too
|
||||
#' as.mo(c("Escherichia coli", "E. coli", "lab_mo_ecoli"))
|
||||
#' #> NOTE: Translation to one microorganism was guessed with uncertainty.
|
||||
#' #> Use mo_uncertainties() to review it.
|
||||
#' #> Class <mo>
|
||||
#' #> [1] B_ESCHR_COLI B_ESCHR_COLI B_ESCHR_COLI
|
||||
#' ```
|
||||
#'
|
||||
#' If we edit the Excel file by, let's say, adding row 4 like this:
|
||||
#'
|
||||
#' ```
|
||||
#' | A | B |
|
||||
#' --|--------------------|-----------------------|
|
||||
#' 1 | Organisation XYZ | mo |
|
||||
#' 2 | lab_mo_ecoli | Escherichia coli |
|
||||
#' 3 | lab_mo_kpneumoniae | Klebsiella pneumoniae |
|
||||
#' 4 | lab_Staph_aureus | Staphylococcus aureus |
|
||||
#' 5 | | |
|
||||
#' ```
|
||||
#'
|
||||
#' ...any new usage of an MO function in this package will update your data file:
|
||||
#'
|
||||
#' ```
|
||||
#' as.mo("lab_mo_ecoli")
|
||||
#' #> NOTE: Updated mo_source file '/Users/me/mo_source.rds' (0.3 kB) from
|
||||
#' #> '/Users/me/Documents/ourcodes.xlsx' (9 kB), columns
|
||||
#' #> "Organisation XYZ" and "mo"
|
||||
#' #> Class <mo>
|
||||
#' #> [1] B_ESCHR_COLI
|
||||
#'
|
||||
#' mo_genus("lab_Staph_aureus")
|
||||
#' #> [1] "Staphylococcus"
|
||||
#' ```
|
||||
#'
|
||||
#' To delete the reference data file, just use `""`, `NULL` or `FALSE` as input for [set_mo_source()]:
|
||||
#'
|
||||
#' ```
|
||||
#' set_mo_source(NULL)
|
||||
#' #> Removed mo_source file '/Users/me/mo_source.rds'
|
||||
#' ```
|
||||
#'
|
||||
#' If the original file (in the previous case an Excel file) is moved or deleted, the `mo_source.rds` file will be removed upon the next use of [as.mo()] or any [`mo_*`][mo_property()] function.
|
||||
#' @export
|
||||
set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_source.rds")) {
|
||||
meet_criteria(path, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(destination, allow_class = "character", has_length = 1)
|
||||
stop_ifnot(destination %like% "[.]rds$", "the `destination` must be a file location with file extension .rds.")
|
||||
|
||||
mo_source_destination <- path.expand(destination)
|
||||
|
||||
stop_ifnot(interactive(), "this function can only be used in interactive mode, since it must ask for the user's permission to write a file to their home folder.")
|
||||
|
||||
if (is.null(path) || path %in% c(FALSE, "")) {
|
||||
pkg_env$mo_source <- NULL
|
||||
if (file.exists(mo_source_destination)) {
|
||||
unlink(mo_source_destination)
|
||||
message_("Removed mo_source file '", font_bold(mo_source_destination), "'",
|
||||
add_fn = font_red,
|
||||
as_note = FALSE)
|
||||
}
|
||||
return(invisible())
|
||||
}
|
||||
|
||||
stop_ifnot(file.exists(path), "file not found: ", path)
|
||||
|
||||
df <- NULL
|
||||
if (path %like% "[.]rds$") {
|
||||
df <- readRDS(path)
|
||||
|
||||
} else if (path %like% "[.]xlsx?$") {
|
||||
# is Excel file (old or new)
|
||||
stop_ifnot_installed("readxl")
|
||||
df <- readxl::read_excel(path)
|
||||
|
||||
} else if (path %like% "[.]tsv$") {
|
||||
df <- utils::read.table(file = path, header = TRUE, sep = "\t", stringsAsFactors = FALSE)
|
||||
|
||||
} else if (path %like% "[.]csv$") {
|
||||
df <- utils::read.table(file = path, header = TRUE, sep = ",", stringsAsFactors = FALSE)
|
||||
|
||||
} else {
|
||||
# try comma first
|
||||
try(
|
||||
df <- utils::read.table(file = path, header = TRUE, sep = ",", stringsAsFactors = FALSE),
|
||||
silent = TRUE)
|
||||
if (!check_validity_mo_source(df, stop_on_error = FALSE)) {
|
||||
# try tab
|
||||
try(
|
||||
df <- utils::read.table(file = path, header = TRUE, sep = "\t", stringsAsFactors = FALSE),
|
||||
silent = TRUE)
|
||||
}
|
||||
if (!check_validity_mo_source(df, stop_on_error = FALSE)) {
|
||||
# try pipe
|
||||
try(
|
||||
df <- utils::read.table(file = path, header = TRUE, sep = "|", stringsAsFactors = FALSE),
|
||||
silent = TRUE)
|
||||
}
|
||||
}
|
||||
|
||||
# check integrity
|
||||
if (is.null(df)) {
|
||||
stop_("the path '", path, "' could not be imported as a dataset.")
|
||||
}
|
||||
check_validity_mo_source(df)
|
||||
|
||||
df <- subset(df, !is.na(mo))
|
||||
|
||||
# keep only first two columns, second must be mo
|
||||
if (colnames(df)[1] == "mo") {
|
||||
df <- df[, c(colnames(df)[2], "mo")]
|
||||
} else {
|
||||
df <- df[, c(colnames(df)[1], "mo")]
|
||||
}
|
||||
|
||||
df <- as.data.frame(df, stringAsFactors = FALSE)
|
||||
df[, "mo"] <- as.mo(df[, "mo", drop = TRUE])
|
||||
|
||||
# success
|
||||
if (file.exists(mo_source_destination)) {
|
||||
action <- "Updated"
|
||||
} else {
|
||||
action <- "Created"
|
||||
# only ask when file is created, not when it is updated
|
||||
txt <- paste0(word_wrap(paste0("This will write create the new file '",
|
||||
mo_source_destination,
|
||||
"', for which your permission is needed.")),
|
||||
"\n\n",
|
||||
word_wrap("Do you agree that this file will be created?"))
|
||||
showQuestion <- import_fn("showQuestion", "rstudioapi", error_on_fail = FALSE)
|
||||
if (!is.null(showQuestion)) {
|
||||
q_continue <- showQuestion("Create new file in home directory", txt)
|
||||
} else {
|
||||
q_continue <- utils::menu(choices = c("OK", "Cancel"), graphics = FALSE, title = txt)
|
||||
}
|
||||
if (q_continue %in% c(FALSE, 2)) {
|
||||
return(invisible())
|
||||
}
|
||||
}
|
||||
attr(df, "mo_source_location") <- path
|
||||
attr(df, "mo_source_destination") <- mo_source_destination
|
||||
attr(df, "mo_source_timestamp") <- file.mtime(path)
|
||||
saveRDS(df, mo_source_destination)
|
||||
pkg_env$mo_source <- df
|
||||
message_(action, " mo_source file '", font_bold(mo_source_destination),
|
||||
"' (", formatted_filesize(mo_source_destination),
|
||||
") from '", font_bold(path),
|
||||
"' (", formatted_filesize(path),
|
||||
'), columns "', colnames(df)[1], '" and "', colnames(df)[2], '"')
|
||||
}
|
||||
|
||||
#' @rdname mo_source
|
||||
#' @export
|
||||
get_mo_source <- function(destination = getOption("AMR_mo_source", "~/mo_source.rds")) {
|
||||
if (!file.exists(path.expand(destination))) {
|
||||
if (interactive()) {
|
||||
# source file might have been deleted, so update reference
|
||||
set_mo_source("")
|
||||
}
|
||||
return(NULL)
|
||||
}
|
||||
if (is.null(pkg_env$mo_source)) {
|
||||
pkg_env$mo_source <- readRDS(path.expand(destination))
|
||||
}
|
||||
|
||||
old_time <- attributes(pkg_env$mo_source)$mo_source_timestamp
|
||||
new_time <- file.mtime(attributes(pkg_env$mo_source)$mo_source_location)
|
||||
if (interactive() && !identical(old_time, new_time)) {
|
||||
# source file was updated, also update reference
|
||||
set_mo_source(attributes(pkg_env$mo_source)$mo_source_location)
|
||||
}
|
||||
pkg_env$mo_source
|
||||
}
|
||||
|
||||
check_validity_mo_source <- function(x, refer_to_name = "`reference_df`", stop_on_error = TRUE) {
|
||||
check_dataset_integrity()
|
||||
|
||||
if (paste(deparse(substitute(x)), collapse = "") == "get_mo_source()") {
|
||||
return(TRUE)
|
||||
}
|
||||
if (is.null(pkg_env$mo_source) && (identical(x, get_mo_source()))) {
|
||||
return(TRUE)
|
||||
}
|
||||
if (is.null(x)) {
|
||||
if (stop_on_error == TRUE) {
|
||||
stop_(refer_to_name, " cannot be NULL", call = FALSE)
|
||||
} else {
|
||||
return(FALSE)
|
||||
}
|
||||
}
|
||||
if (!is.data.frame(x)) {
|
||||
if (stop_on_error == TRUE) {
|
||||
stop_(refer_to_name, " must be a data.frame", call = FALSE)
|
||||
} else {
|
||||
return(FALSE)
|
||||
}
|
||||
}
|
||||
if (!"mo" %in% colnames(x)) {
|
||||
if (stop_on_error == TRUE) {
|
||||
stop_(refer_to_name, " must contain a column 'mo'", call = FALSE)
|
||||
} else {
|
||||
return(FALSE)
|
||||
}
|
||||
}
|
||||
if (!all(x$mo %in% c("", microorganisms$mo, microorganisms$fullname), na.rm = TRUE)) {
|
||||
if (stop_on_error == TRUE) {
|
||||
invalid <- x[which(!x$mo %in% c("", microorganisms$mo, microorganisms$fullname)), , drop = FALSE]
|
||||
if (nrow(invalid) > 1) {
|
||||
plural <- "s"
|
||||
} else {
|
||||
plural <- ""
|
||||
}
|
||||
stop_("Value", plural, " ", vector_and(invalid[, 1, drop = TRUE], quotes = TRUE),
|
||||
" found in ", tolower(refer_to_name),
|
||||
", but with invalid microorganism code", plural, " ", vector_and(invalid$mo, quotes = TRUE),
|
||||
call = FALSE)
|
||||
} else {
|
||||
return(FALSE)
|
||||
}
|
||||
}
|
||||
if (colnames(x)[1] != "mo" & nrow(x) > length(unique(x[, 1, drop = TRUE]))) {
|
||||
if (stop_on_error == TRUE) {
|
||||
stop_(refer_to_name, " contains duplicate values in column '", colnames(x)[1], "'", call = FALSE)
|
||||
} else {
|
||||
return(FALSE)
|
||||
}
|
||||
}
|
||||
if (colnames(x)[2] != "mo" & nrow(x) > length(unique(x[, 2, drop = TRUE]))) {
|
||||
if (stop_on_error == TRUE) {
|
||||
stop_(refer_to_name, " contains duplicate values in column '", colnames(x)[2], "'", call = FALSE)
|
||||
} else {
|
||||
return(FALSE)
|
||||
}
|
||||
}
|
||||
return(TRUE)
|
||||
}
|
||||
@@ -1,172 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Principal Component Analysis (for AMR)
|
||||
#'
|
||||
#' Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels, and automatic filtering on only suitable (i.e. non-empty and numeric) variables.
|
||||
#' @param x a [data.frame] containing [numeric] columns
|
||||
#' @param ... columns of `x` to be selected for PCA, can be unquoted since it supports quasiquotation.
|
||||
#' @inheritParams stats::prcomp
|
||||
#' @details The [pca()] function takes a [data.frame] as input and performs the actual PCA with the \R function [prcomp()].
|
||||
#'
|
||||
#' The result of the [pca()] function is a [prcomp] object, with an additional attribute `non_numeric_cols` which is a vector with the column names of all columns that do not contain [numeric] values. These are probably the groups and labels, and will be used by [ggplot_pca()].
|
||||
#' @return An object of classes [pca] and [prcomp]
|
||||
#' @importFrom stats prcomp
|
||||
#' @export
|
||||
#' @examples
|
||||
#' # `example_isolates` is a data set available in the AMR package.
|
||||
#' # See ?example_isolates.
|
||||
#'
|
||||
#' \donttest{
|
||||
#' if (require("dplyr")) {
|
||||
#' # calculate the resistance per group first
|
||||
#' resistance_data <- example_isolates %>%
|
||||
#' group_by(order = mo_order(mo), # group on anything, like order
|
||||
#' genus = mo_genus(mo)) %>% # and genus as we do here;
|
||||
#' filter(n() >= 30) %>% # filter on only 30 results per group
|
||||
#' summarise_if(is.rsi, resistance) # then get resistance of all drugs
|
||||
#'
|
||||
#' # now conduct PCA for certain antimicrobial agents
|
||||
#' pca_result <- resistance_data %>%
|
||||
#' pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)
|
||||
#'
|
||||
#' pca_result
|
||||
#' summary(pca_result)
|
||||
#'
|
||||
#' # old base R plotting method:
|
||||
#' biplot(pca_result)
|
||||
#' # new ggplot2 plotting method using this package:
|
||||
#' ggplot_pca(pca_result)
|
||||
#'
|
||||
#' if (require("ggplot2")) {
|
||||
#' ggplot_pca(pca_result) +
|
||||
#' scale_colour_viridis_d() +
|
||||
#' labs(title = "Title here")
|
||||
#' }
|
||||
#' }
|
||||
#' }
|
||||
pca <- function(x,
|
||||
...,
|
||||
retx = TRUE,
|
||||
center = TRUE,
|
||||
scale. = TRUE,
|
||||
tol = NULL,
|
||||
rank. = NULL) {
|
||||
meet_criteria(x, allow_class = "data.frame")
|
||||
meet_criteria(retx, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(center, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(scale., allow_class = "logical", has_length = 1)
|
||||
meet_criteria(tol, allow_class = "numeric", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(rank., allow_class = "numeric", has_length = 1, allow_NULL = TRUE)
|
||||
|
||||
# unset data.table, tibble, etc.
|
||||
# also removes groups made by dplyr::group_by
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
||||
x.bak <- x
|
||||
|
||||
# defuse R expressions, this replaces rlang::enquos()
|
||||
dots <- substitute(list(...))
|
||||
if (length(dots) > 1) {
|
||||
new_list <- list(0)
|
||||
for (i in seq_len(length(dots) - 1)) {
|
||||
new_list[[i]] <- tryCatch(eval(dots[[i + 1]], envir = x),
|
||||
error = function(e) stop(e$message, call. = FALSE))
|
||||
if (length(new_list[[i]]) == 1) {
|
||||
if (is.character(new_list[[i]]) & new_list[[i]] %in% colnames(x)) {
|
||||
# this is to support quoted variables: df %pm>% pca("mycol1", "mycol2")
|
||||
new_list[[i]] <- x[, new_list[[i]]]
|
||||
} else {
|
||||
# remove item - it's an argument like `center`
|
||||
new_list[[i]] <- NULL
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
x <- as.data.frame(new_list, stringsAsFactors = FALSE)
|
||||
if (any(vapply(FUN.VALUE = logical(1), x, function(y) !is.numeric(y)))) {
|
||||
warning_("in `pca()`: be sure to first calculate the resistance (or susceptibility) of variables with antimicrobial test results, since PCA works with numeric variables only. See Examples in ?pca.", call = FALSE)
|
||||
}
|
||||
|
||||
# set column names
|
||||
tryCatch(colnames(x) <- as.character(dots)[2:length(dots)],
|
||||
error = function(e) warning("column names could not be set"))
|
||||
|
||||
# keep only numeric columns
|
||||
x <- x[, vapply(FUN.VALUE = logical(1), x, function(y) is.numeric(y))]
|
||||
# bind the data set with the non-numeric columns
|
||||
x <- cbind(x.bak[, vapply(FUN.VALUE = logical(1), x.bak, function(y) !is.numeric(y) & !all(is.na(y))), drop = FALSE], x)
|
||||
}
|
||||
|
||||
x <- pm_ungroup(x) # would otherwise select the grouping vars
|
||||
x <- x[rowSums(is.na(x)) == 0, ] # remove columns containing NAs
|
||||
|
||||
pca_data <- x[, which(vapply(FUN.VALUE = logical(1), x, function(x) is.numeric(x)))]
|
||||
|
||||
message_("Columns selected for PCA: ", vector_and(font_bold(colnames(pca_data), collapse = NULL), quotes = TRUE),
|
||||
". Total observations available: ", nrow(pca_data), ".")
|
||||
|
||||
if (getRversion() < "3.4.0") {
|
||||
# stats::prcomp prior to 3.4.0 does not have the 'rank.' argument
|
||||
pca_model <- prcomp(pca_data, retx = retx, center = center, scale. = scale., tol = tol)
|
||||
} else {
|
||||
pca_model <- prcomp(pca_data, retx = retx, center = center, scale. = scale., tol = tol, rank. = rank.)
|
||||
}
|
||||
groups <- x[, vapply(FUN.VALUE = logical(1), x, function(y) !is.numeric(y) & !all(is.na(y))), drop = FALSE]
|
||||
rownames(groups) <- NULL
|
||||
attr(pca_model, "non_numeric_cols") <- groups
|
||||
class(pca_model) <- c("pca", class(pca_model))
|
||||
pca_model
|
||||
}
|
||||
|
||||
#' @method print pca
|
||||
#' @export
|
||||
#' @noRd
|
||||
print.pca <- function(x, ...) {
|
||||
a <- attributes(x)$non_numeric_cols
|
||||
if (!is.null(a)) {
|
||||
print_pca_group(a)
|
||||
class(x) <- class(x)[class(x) != "pca"]
|
||||
}
|
||||
print(x, ...)
|
||||
}
|
||||
|
||||
#' @method summary pca
|
||||
#' @export
|
||||
#' @noRd
|
||||
summary.pca <- function(object, ...) {
|
||||
a <- attributes(object)$non_numeric_cols
|
||||
if (!is.null(a)) {
|
||||
print_pca_group(a)
|
||||
class(object) <- class(object)[class(object) != "pca"]
|
||||
}
|
||||
summary(object, ...)
|
||||
}
|
||||
|
||||
print_pca_group <- function(a) {
|
||||
grps <- sort(unique(a[, 1, drop = TRUE]))
|
||||
cat("Groups (n=", length(grps), ", named as '", colnames(a)[1], "'):\n", sep = "")
|
||||
print(grps)
|
||||
cat("\n")
|
||||
}
|
||||
@@ -1,762 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Plotting for Classes `rsi`, `mic` and `disk`
|
||||
#'
|
||||
#' Functions to plot classes `rsi`, `mic` and `disk`, with support for base \R and `ggplot2`.
|
||||
|
||||
#' @param x,object values created with [as.mic()], [as.disk()] or [as.rsi()] (or their `random_*` variants, such as [random_mic()])
|
||||
#' @param mo any (vector of) text that can be coerced to a valid microorganism code with [as.mo()]
|
||||
#' @param ab any (vector of) text that can be coerced to a valid antimicrobial code with [as.ab()]
|
||||
#' @param guideline interpretation guideline to use, defaults to the latest included EUCAST guideline, see *Details*
|
||||
#' @param main,title title of the plot
|
||||
#' @param xlab,ylab axis title
|
||||
#' @param colours_RSI colours to use for filling in the bars, must be a vector of three values (in the order R, S and I). The default colours are colour-blind friendly.
|
||||
#' @param language language to be used to translate 'Susceptible', 'Increased exposure'/'Intermediate' and 'Resistant', defaults to system language (see [get_AMR_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Use `language = NULL` or `language = ""` to prevent translation.
|
||||
#' @param expand a [logical] to indicate whether the range on the x axis should be expanded between the lowest and highest value. For MIC values, intermediate values will be factors of 2 starting from the highest MIC value. For disk diameters, the whole diameter range will be filled.
|
||||
#' @details
|
||||
#' The interpretation of "I" will be named "Increased exposure" for all EUCAST guidelines since 2019, and will be named "Intermediate" in all other cases.
|
||||
#'
|
||||
#' For interpreting MIC values as well as disk diffusion diameters, supported guidelines to be used as input for the `guideline` argument are: `r vector_and(AMR::rsi_translation$guideline, quotes = TRUE, reverse = TRUE)`.
|
||||
#'
|
||||
#' Simply using `"CLSI"` or `"EUCAST"` as input will automatically select the latest version of that guideline.
|
||||
#' @name plot
|
||||
#' @rdname plot
|
||||
#' @return The `autoplot()` functions return a [`ggplot`][ggplot2::ggplot()] model that is extendible with any `ggplot2` function.
|
||||
#'
|
||||
#' The `fortify()` functions return a [data.frame] as an extension for usage in the [ggplot2::ggplot()] function.
|
||||
#' @param ... arguments passed on to methods
|
||||
#' @examples
|
||||
#' some_mic_values <- random_mic(size = 100)
|
||||
#' some_disk_values <- random_disk(size = 100, mo = "Escherichia coli", ab = "cipro")
|
||||
#' some_rsi_values <- random_rsi(50, prob_RSI = c(0.30, 0.55, 0.05))
|
||||
#'
|
||||
#' plot(some_mic_values)
|
||||
#' plot(some_disk_values)
|
||||
#' plot(some_rsi_values)
|
||||
#'
|
||||
#' # when providing the microorganism and antibiotic, colours will show interpretations:
|
||||
#' plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
|
||||
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
|
||||
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "uk")
|
||||
#'
|
||||
#' \donttest{
|
||||
#' if (require("ggplot2")) {
|
||||
#' autoplot(some_mic_values)
|
||||
#' autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
|
||||
#' autoplot(some_rsi_values)
|
||||
#' }
|
||||
#' }
|
||||
NULL
|
||||
|
||||
#' @method plot mic
|
||||
#' @importFrom graphics barplot axis mtext legend
|
||||
#' @export
|
||||
#' @rdname plot
|
||||
plot.mic <- function(x,
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
guideline = "EUCAST",
|
||||
main = deparse(substitute(x)),
|
||||
ylab = "Frequency",
|
||||
xlab = "Minimum Inhibitory Concentration (mg/L)",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_AMR_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(guideline, allow_class = "character", has_length = 1)
|
||||
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(expand, allow_class = "logical", has_length = 1)
|
||||
|
||||
# translate if not specifically set
|
||||
if (missing(ylab)) {
|
||||
ylab <- translate_into_language(ylab, language = language)
|
||||
}
|
||||
if (missing(xlab)) {
|
||||
xlab <- translate_into_language(xlab, language = language)
|
||||
}
|
||||
|
||||
if (length(colours_RSI) == 1) {
|
||||
colours_RSI <- rep(colours_RSI, 3)
|
||||
}
|
||||
main <- gsub(" +", " ", paste0(main, collapse = " "))
|
||||
|
||||
x <- plot_prepare_table(x, expand = expand)
|
||||
|
||||
cols_sub <- plot_colours_subtitle_guideline(x = x,
|
||||
mo = mo,
|
||||
ab = ab,
|
||||
guideline = guideline,
|
||||
colours_RSI = colours_RSI,
|
||||
fn = as.mic,
|
||||
language = language,
|
||||
...)
|
||||
barplot(x,
|
||||
col = cols_sub$cols,
|
||||
main = main,
|
||||
ylim = c(0, max(x) * ifelse(any(colours_RSI %in% cols_sub$cols), 1.1, 1)),
|
||||
ylab = ylab,
|
||||
xlab = xlab,
|
||||
axes = FALSE)
|
||||
axis(2, seq(0, max(x)))
|
||||
if (!is.null(cols_sub$sub)) {
|
||||
mtext(side = 3, line = 0.5, adj = 0.5, cex = 0.75, cols_sub$sub)
|
||||
}
|
||||
|
||||
if (any(colours_RSI %in% cols_sub$cols)) {
|
||||
legend_txt <- character(0)
|
||||
legend_col <- character(0)
|
||||
if (any(cols_sub$cols == colours_RSI[2] & cols_sub$count > 0)) {
|
||||
legend_txt <- "Susceptible"
|
||||
legend_col <- colours_RSI[2]
|
||||
}
|
||||
if (any(cols_sub$cols == colours_RSI[3] & cols_sub$count > 0)) {
|
||||
legend_txt <- c(legend_txt, plot_name_of_I(cols_sub$guideline))
|
||||
legend_col <- c(legend_col, colours_RSI[3])
|
||||
}
|
||||
if (any(cols_sub$cols == colours_RSI[1] & cols_sub$count > 0)) {
|
||||
legend_txt <- c(legend_txt, "Resistant")
|
||||
legend_col <- c(legend_col, colours_RSI[1])
|
||||
}
|
||||
|
||||
legend("top",
|
||||
x.intersp = 0.5,
|
||||
legend = translate_into_language(legend_txt, language = language),
|
||||
fill = legend_col,
|
||||
horiz = TRUE,
|
||||
cex = 0.75,
|
||||
box.lwd = 0,
|
||||
box.col = "#FFFFFF55",
|
||||
bg = "#FFFFFF55")
|
||||
}
|
||||
}
|
||||
|
||||
#' @method barplot mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
barplot.mic <- function(height,
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
guideline = "EUCAST",
|
||||
main = deparse(substitute(height)),
|
||||
ylab = "Frequency",
|
||||
xlab = "Minimum Inhibitory Concentration (mg/L)",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_AMR_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(guideline, allow_class = "character", has_length = 1)
|
||||
meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(expand, allow_class = "logical", has_length = 1)
|
||||
|
||||
# translate if not specifically set
|
||||
if (missing(ylab)) {
|
||||
ylab <- translate_into_language(ylab, language = language)
|
||||
}
|
||||
if (missing(xlab)) {
|
||||
xlab <- translate_into_language(xlab, language = language)
|
||||
}
|
||||
|
||||
main <- gsub(" +", " ", paste0(main, collapse = " "))
|
||||
|
||||
plot(x = height,
|
||||
main = main,
|
||||
ylab = ylab,
|
||||
xlab = xlab,
|
||||
mo = mo,
|
||||
ab = ab,
|
||||
guideline = guideline,
|
||||
colours_RSI = colours_RSI,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @method autoplot mic
|
||||
#' @rdname plot
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
autoplot.mic <- function(object,
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
guideline = "EUCAST",
|
||||
title = deparse(substitute(object)),
|
||||
ylab = "Frequency",
|
||||
xlab = "Minimum Inhibitory Concentration (mg/L)",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_AMR_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(guideline, allow_class = "character", has_length = 1)
|
||||
meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(expand, allow_class = "logical", has_length = 1)
|
||||
|
||||
# translate if not specifically set
|
||||
if (missing(ylab)) {
|
||||
ylab <- translate_into_language(ylab, language = language)
|
||||
}
|
||||
if (missing(xlab)) {
|
||||
xlab <- translate_into_language(xlab, language = language)
|
||||
}
|
||||
|
||||
if ("main" %in% names(list(...))) {
|
||||
title <- list(...)$main
|
||||
}
|
||||
if (!is.null(title)) {
|
||||
title <- gsub(" +", " ", paste0(title, collapse = " "))
|
||||
}
|
||||
|
||||
x <- plot_prepare_table(object, expand = expand)
|
||||
cols_sub <- plot_colours_subtitle_guideline(x = x,
|
||||
mo = mo,
|
||||
ab = ab,
|
||||
guideline = guideline,
|
||||
colours_RSI = colours_RSI,
|
||||
fn = as.mic,
|
||||
language = language,
|
||||
...)
|
||||
df <- as.data.frame(x, stringsAsFactors = TRUE)
|
||||
colnames(df) <- c("mic", "count")
|
||||
df$cols <- cols_sub$cols
|
||||
df$cols[df$cols == colours_RSI[1]] <- "Resistant"
|
||||
df$cols[df$cols == colours_RSI[2]] <- "Susceptible"
|
||||
df$cols[df$cols == colours_RSI[3]] <- plot_name_of_I(cols_sub$guideline)
|
||||
df$cols <- factor(translate_into_language(df$cols, language = language),
|
||||
levels = translate_into_language(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
|
||||
language = language),
|
||||
ordered = TRUE)
|
||||
p <- ggplot2::ggplot(df)
|
||||
|
||||
if (any(colours_RSI %in% cols_sub$cols)) {
|
||||
vals <- c("Resistant" = colours_RSI[1],
|
||||
"Susceptible" = colours_RSI[2],
|
||||
"Susceptible, incr. exp." = colours_RSI[3],
|
||||
"Intermediate" = colours_RSI[3])
|
||||
names(vals) <- translate_into_language(names(vals), language = language)
|
||||
p <- p +
|
||||
ggplot2::geom_col(ggplot2::aes(x = mic, y = count, fill = cols)) +
|
||||
# limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
|
||||
ggplot2::scale_fill_manual(values = vals,
|
||||
name = NULL,
|
||||
limits = force)
|
||||
} else {
|
||||
p <- p +
|
||||
ggplot2::geom_col(ggplot2::aes(x = mic, y = count))
|
||||
}
|
||||
|
||||
p +
|
||||
ggplot2::labs(title = title, x = xlab, y = ylab, subtitle = cols_sub$sub)
|
||||
}
|
||||
|
||||
#' @method fortify mic
|
||||
#' @rdname plot
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
fortify.mic <- function(object, ...) {
|
||||
stats::setNames(as.data.frame(plot_prepare_table(object, expand = FALSE)),
|
||||
c("x", "y"))
|
||||
}
|
||||
|
||||
#' @method plot disk
|
||||
#' @export
|
||||
#' @importFrom graphics barplot axis mtext legend
|
||||
#' @rdname plot
|
||||
plot.disk <- function(x,
|
||||
main = deparse(substitute(x)),
|
||||
ylab = "Frequency",
|
||||
xlab = "Disk diffusion diameter (mm)",
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
guideline = "EUCAST",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_AMR_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(guideline, allow_class = "character", has_length = 1)
|
||||
meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(expand, allow_class = "logical", has_length = 1)
|
||||
|
||||
# translate if not specifically set
|
||||
if (missing(ylab)) {
|
||||
ylab <- translate_into_language(ylab, language = language)
|
||||
}
|
||||
if (missing(xlab)) {
|
||||
xlab <- translate_into_language(xlab, language = language)
|
||||
}
|
||||
|
||||
if (length(colours_RSI) == 1) {
|
||||
colours_RSI <- rep(colours_RSI, 3)
|
||||
}
|
||||
main <- gsub(" +", " ", paste0(main, collapse = " "))
|
||||
|
||||
x <- plot_prepare_table(x, expand = expand)
|
||||
|
||||
cols_sub <- plot_colours_subtitle_guideline(x = x,
|
||||
mo = mo,
|
||||
ab = ab,
|
||||
guideline = guideline,
|
||||
colours_RSI = colours_RSI,
|
||||
fn = as.disk,
|
||||
language = language,
|
||||
...)
|
||||
|
||||
barplot(x,
|
||||
col = cols_sub$cols,
|
||||
main = main,
|
||||
ylim = c(0, max(x) * ifelse(any(colours_RSI %in% cols_sub$cols), 1.1, 1)),
|
||||
ylab = ylab,
|
||||
xlab = xlab,
|
||||
axes = FALSE)
|
||||
axis(2, seq(0, max(x)))
|
||||
if (!is.null(cols_sub$sub)) {
|
||||
mtext(side = 3, line = 0.5, adj = 0.5, cex = 0.75, cols_sub$sub)
|
||||
}
|
||||
|
||||
if (any(colours_RSI %in% cols_sub$cols)) {
|
||||
legend_txt <- character(0)
|
||||
legend_col <- character(0)
|
||||
if (any(cols_sub$cols == colours_RSI[1] & cols_sub$count > 0)) {
|
||||
legend_txt <- "Resistant"
|
||||
legend_col <- colours_RSI[1]
|
||||
}
|
||||
if (any(cols_sub$cols == colours_RSI[3] & cols_sub$count > 0)) {
|
||||
legend_txt <- c(legend_txt, plot_name_of_I(cols_sub$guideline))
|
||||
legend_col <- c(legend_col, colours_RSI[3])
|
||||
}
|
||||
if (any(cols_sub$cols == colours_RSI[2] & cols_sub$count > 0)) {
|
||||
legend_txt <- c(legend_txt, "Susceptible")
|
||||
legend_col <- c(legend_col, colours_RSI[2])
|
||||
}
|
||||
legend("top",
|
||||
x.intersp = 0.5,
|
||||
legend = translate_into_language(legend_txt, language = language),
|
||||
fill = legend_col,
|
||||
horiz = TRUE,
|
||||
cex = 0.75,
|
||||
box.lwd = 0,
|
||||
box.col = "#FFFFFF55",
|
||||
bg = "#FFFFFF55")
|
||||
}
|
||||
}
|
||||
|
||||
#' @method barplot disk
|
||||
#' @export
|
||||
#' @noRd
|
||||
barplot.disk <- function(height,
|
||||
main = deparse(substitute(height)),
|
||||
ylab = "Frequency",
|
||||
xlab = "Disk diffusion diameter (mm)",
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
guideline = "EUCAST",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_AMR_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(guideline, allow_class = "character", has_length = 1)
|
||||
meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(expand, allow_class = "logical", has_length = 1)
|
||||
|
||||
# translate if not specifically set
|
||||
if (missing(ylab)) {
|
||||
ylab <- translate_into_language(ylab, language = language)
|
||||
}
|
||||
if (missing(xlab)) {
|
||||
xlab <- translate_into_language(xlab, language = language)
|
||||
}
|
||||
|
||||
main <- gsub(" +", " ", paste0(main, collapse = " "))
|
||||
|
||||
plot(x = height,
|
||||
main = main,
|
||||
ylab = ylab,
|
||||
xlab = xlab,
|
||||
mo = mo,
|
||||
ab = ab,
|
||||
guideline = guideline,
|
||||
colours_RSI = colours_RSI,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @method autoplot disk
|
||||
#' @rdname plot
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
autoplot.disk <- function(object,
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
title = deparse(substitute(object)),
|
||||
ylab = "Frequency",
|
||||
xlab = "Disk diffusion diameter (mm)",
|
||||
guideline = "EUCAST",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_AMR_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(guideline, allow_class = "character", has_length = 1)
|
||||
meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(expand, allow_class = "logical", has_length = 1)
|
||||
|
||||
# translate if not specifically set
|
||||
if (missing(ylab)) {
|
||||
ylab <- translate_into_language(ylab, language = language)
|
||||
}
|
||||
if (missing(xlab)) {
|
||||
xlab <- translate_into_language(xlab, language = language)
|
||||
}
|
||||
|
||||
if ("main" %in% names(list(...))) {
|
||||
title <- list(...)$main
|
||||
}
|
||||
if (!is.null(title)) {
|
||||
title <- gsub(" +", " ", paste0(title, collapse = " "))
|
||||
}
|
||||
|
||||
x <- plot_prepare_table(object, expand = expand)
|
||||
cols_sub <- plot_colours_subtitle_guideline(x = x,
|
||||
mo = mo,
|
||||
ab = ab,
|
||||
guideline = guideline,
|
||||
colours_RSI = colours_RSI,
|
||||
fn = as.disk,
|
||||
language = language,
|
||||
...)
|
||||
df <- as.data.frame(x, stringsAsFactors = TRUE)
|
||||
colnames(df) <- c("disk", "count")
|
||||
df$cols <- cols_sub$cols
|
||||
|
||||
df$cols[df$cols == colours_RSI[1]] <- "Resistant"
|
||||
df$cols[df$cols == colours_RSI[2]] <- "Susceptible"
|
||||
df$cols[df$cols == colours_RSI[3]] <- plot_name_of_I(cols_sub$guideline)
|
||||
df$cols <- factor(translate_into_language(df$cols, language = language),
|
||||
levels = translate_into_language(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
|
||||
language = language),
|
||||
ordered = TRUE)
|
||||
p <- ggplot2::ggplot(df)
|
||||
|
||||
if (any(colours_RSI %in% cols_sub$cols)) {
|
||||
vals <- c("Resistant" = colours_RSI[1],
|
||||
"Susceptible" = colours_RSI[2],
|
||||
"Susceptible, incr. exp." = colours_RSI[3],
|
||||
"Intermediate" = colours_RSI[3])
|
||||
names(vals) <- translate_into_language(names(vals), language = language)
|
||||
p <- p +
|
||||
ggplot2::geom_col(ggplot2::aes(x = disk, y = count, fill = cols)) +
|
||||
# limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
|
||||
ggplot2::scale_fill_manual(values = vals,
|
||||
name = NULL,
|
||||
limits = force)
|
||||
} else {
|
||||
p <- p +
|
||||
ggplot2::geom_col(ggplot2::aes(x = disk, y = count))
|
||||
}
|
||||
|
||||
p +
|
||||
ggplot2::labs(title = title, x = xlab, y = ylab, subtitle = cols_sub$sub)
|
||||
}
|
||||
|
||||
#' @method fortify disk
|
||||
#' @rdname plot
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
fortify.disk <- function(object, ...) {
|
||||
stats::setNames(as.data.frame(plot_prepare_table(object, expand = FALSE)),
|
||||
c("x", "y"))
|
||||
}
|
||||
|
||||
#' @method plot rsi
|
||||
#' @export
|
||||
#' @importFrom graphics plot text axis
|
||||
#' @rdname plot
|
||||
plot.rsi <- function(x,
|
||||
ylab = "Percentage",
|
||||
xlab = "Antimicrobial Interpretation",
|
||||
main = deparse(substitute(x)),
|
||||
language = get_AMR_locale(),
|
||||
...) {
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
|
||||
# translate if not specifically set
|
||||
if (missing(ylab)) {
|
||||
ylab <- translate_into_language(ylab, language = language)
|
||||
}
|
||||
if (missing(xlab)) {
|
||||
xlab <- translate_into_language(xlab, language = language)
|
||||
}
|
||||
|
||||
data <- as.data.frame(table(x), stringsAsFactors = FALSE)
|
||||
colnames(data) <- c("x", "n")
|
||||
data$s <- round((data$n / sum(data$n)) * 100, 1)
|
||||
|
||||
if (!"S" %in% data$x) {
|
||||
data <- rbind(data, data.frame(x = "S", n = 0, s = 0, stringsAsFactors = FALSE),
|
||||
stringsAsFactors = FALSE)
|
||||
}
|
||||
if (!"I" %in% data$x) {
|
||||
data <- rbind(data, data.frame(x = "I", n = 0, s = 0, stringsAsFactors = FALSE),
|
||||
stringsAsFactors = FALSE)
|
||||
}
|
||||
if (!"R" %in% data$x) {
|
||||
data <- rbind(data, data.frame(x = "R", n = 0, s = 0, stringsAsFactors = FALSE),
|
||||
stringsAsFactors = FALSE)
|
||||
}
|
||||
|
||||
data$x <- factor(data$x, levels = c("S", "I", "R"), ordered = TRUE)
|
||||
|
||||
ymax <- pm_if_else(max(data$s) > 95, 105, 100)
|
||||
|
||||
plot(x = data$x,
|
||||
y = data$s,
|
||||
lwd = 2,
|
||||
ylim = c(0, ymax),
|
||||
ylab = ylab,
|
||||
xlab = xlab,
|
||||
main = main,
|
||||
axes = FALSE)
|
||||
# x axis
|
||||
axis(side = 1, at = 1:pm_n_distinct(data$x), labels = levels(data$x), lwd = 0)
|
||||
# y axis, 0-100%
|
||||
axis(side = 2, at = seq(0, 100, 5))
|
||||
|
||||
text(x = data$x,
|
||||
y = data$s + 4,
|
||||
labels = paste0(data$s, "% (n = ", data$n, ")"))
|
||||
}
|
||||
|
||||
|
||||
#' @method barplot rsi
|
||||
#' @importFrom graphics barplot axis
|
||||
#' @export
|
||||
#' @noRd
|
||||
barplot.rsi <- function(height,
|
||||
main = deparse(substitute(height)),
|
||||
xlab = "Antimicrobial Interpretation",
|
||||
ylab = "Frequency",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_AMR_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(expand, allow_class = "logical", has_length = 1)
|
||||
|
||||
# translate if not specifically set
|
||||
if (missing(ylab)) {
|
||||
ylab <- translate_into_language(ylab, language = language)
|
||||
}
|
||||
if (missing(xlab)) {
|
||||
xlab <- translate_into_language(xlab, language = language)
|
||||
}
|
||||
|
||||
if (length(colours_RSI) == 1) {
|
||||
colours_RSI <- rep(colours_RSI, 3)
|
||||
} else {
|
||||
colours_RSI <- c(colours_RSI[2], colours_RSI[3], colours_RSI[1])
|
||||
}
|
||||
main <- gsub(" +", " ", paste0(main, collapse = " "))
|
||||
|
||||
x <- table(height)
|
||||
x <- x[c(1, 2, 3)]
|
||||
barplot(x,
|
||||
col = colours_RSI,
|
||||
xlab = xlab,
|
||||
main = main,
|
||||
ylab = ylab,
|
||||
axes = FALSE)
|
||||
axis(2, seq(0, max(x)))
|
||||
}
|
||||
|
||||
#' @method autoplot rsi
|
||||
#' @rdname plot
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
autoplot.rsi <- function(object,
|
||||
title = deparse(substitute(object)),
|
||||
xlab = "Antimicrobial Interpretation",
|
||||
ylab = "Frequency",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_AMR_locale(),
|
||||
...) {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
|
||||
|
||||
# translate if not specifically set
|
||||
if (missing(ylab)) {
|
||||
ylab <- translate_into_language(ylab, language = language)
|
||||
}
|
||||
if (missing(xlab)) {
|
||||
xlab <- translate_into_language(xlab, language = language)
|
||||
}
|
||||
|
||||
if ("main" %in% names(list(...))) {
|
||||
title <- list(...)$main
|
||||
}
|
||||
if (!is.null(title)) {
|
||||
title <- gsub(" +", " ", paste0(title, collapse = " "))
|
||||
}
|
||||
|
||||
if (length(colours_RSI) == 1) {
|
||||
colours_RSI <- rep(colours_RSI, 3)
|
||||
}
|
||||
|
||||
df <- as.data.frame(table(object), stringsAsFactors = TRUE)
|
||||
colnames(df) <- c("rsi", "count")
|
||||
ggplot2::ggplot(df) +
|
||||
ggplot2::geom_col(ggplot2::aes(x = rsi, y = count, fill = rsi)) +
|
||||
# limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
|
||||
ggplot2::scale_fill_manual(values = c("R" = colours_RSI[1],
|
||||
"S" = colours_RSI[2],
|
||||
"I" = colours_RSI[3]),
|
||||
limits = force) +
|
||||
ggplot2::labs(title = title, x = xlab, y = ylab) +
|
||||
ggplot2::theme(legend.position = "none")
|
||||
}
|
||||
|
||||
#' @method fortify rsi
|
||||
#' @rdname plot
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
fortify.rsi <- function(object, ...) {
|
||||
stats::setNames(as.data.frame(table(object)),
|
||||
c("x", "y"))
|
||||
}
|
||||
|
||||
plot_prepare_table <- function(x, expand) {
|
||||
x <- x[!is.na(x)]
|
||||
stop_if(length(x) == 0, "no observations to plot", call = FALSE)
|
||||
if (is.mic(x)) {
|
||||
if (expand == TRUE) {
|
||||
# expand range for MIC by adding factors of 2 from lowest to highest so all MICs in between also print
|
||||
valid_lvls <- levels(x)
|
||||
extra_range <- max(x) / 2
|
||||
while (min(extra_range) / 2 > min(x)) {
|
||||
extra_range <- c(min(extra_range) / 2, extra_range)
|
||||
}
|
||||
nms <- extra_range
|
||||
extra_range <- rep(0, length(extra_range))
|
||||
names(extra_range) <- nms
|
||||
x <- table(droplevels(x, as.mic = FALSE))
|
||||
extra_range <- extra_range[!names(extra_range) %in% names(x) & names(extra_range) %in% valid_lvls]
|
||||
x <- as.table(c(x, extra_range))
|
||||
} else {
|
||||
x <- table(droplevels(x, as.mic = FALSE))
|
||||
}
|
||||
x <- x[order(as.double(as.mic(names(x))))]
|
||||
} else if (is.disk(x)) {
|
||||
if (expand == TRUE) {
|
||||
# expand range for disks from lowest to highest so all mm's in between also print
|
||||
extra_range <- rep(0, max(x) - min(x) - 1)
|
||||
names(extra_range) <- seq(min(x) + 1, max(x) - 1)
|
||||
x <- table(x)
|
||||
extra_range <- extra_range[!names(extra_range) %in% names(x)]
|
||||
x <- as.table(c(x, extra_range))
|
||||
} else {
|
||||
x <- table(x)
|
||||
}
|
||||
x <- x[order(as.double(names(x)))]
|
||||
}
|
||||
as.table(x)
|
||||
}
|
||||
|
||||
plot_name_of_I <- function(guideline) {
|
||||
if (guideline %unlike% "CLSI" && as.double(gsub("[^0-9]+", "", guideline)) >= 2019) {
|
||||
# interpretation since 2019
|
||||
"Susceptible, incr. exp."
|
||||
} else {
|
||||
# interpretation until 2019
|
||||
"Intermediate"
|
||||
}
|
||||
}
|
||||
|
||||
plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_RSI, fn, language, ...) {
|
||||
guideline <- get_guideline(guideline, AMR::rsi_translation)
|
||||
if (!is.null(mo) && !is.null(ab)) {
|
||||
# interpret and give colour based on MIC values
|
||||
mo <- as.mo(mo)
|
||||
ab <- as.ab(ab)
|
||||
rsi <- suppressWarnings(suppressMessages(as.rsi(fn(names(x)), mo = mo, ab = ab, guideline = guideline, ...)))
|
||||
cols <- character(length = length(rsi))
|
||||
cols[is.na(rsi)] <- "#BEBEBE"
|
||||
cols[rsi == "R"] <- colours_RSI[1]
|
||||
cols[rsi == "S"] <- colours_RSI[2]
|
||||
cols[rsi == "I"] <- colours_RSI[3]
|
||||
moname <- mo_name(mo, language = language)
|
||||
abname <- ab_name(ab, language = language)
|
||||
if (all(cols == "#BEBEBE")) {
|
||||
message_("No ", guideline, " interpretations found for ",
|
||||
ab_name(ab, language = NULL, tolower = TRUE), " in ", moname)
|
||||
guideline_txt <- ""
|
||||
} else {
|
||||
guideline_txt <- guideline
|
||||
if (isTRUE(list(...)$uti)) {
|
||||
guideline_txt <- paste("UTIs,", guideline_txt)
|
||||
}
|
||||
guideline_txt <- paste0("(", guideline_txt, ")")
|
||||
}
|
||||
sub <- bquote(.(abname)~"-"~italic(.(moname))~.(guideline_txt))
|
||||
} else {
|
||||
cols <- "#BEBEBE"
|
||||
sub <- NULL
|
||||
}
|
||||
list(cols = cols, count = as.double(x), sub = sub, guideline = guideline)
|
||||
}
|
||||
-297
@@ -1,297 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Calculate Microbial Resistance
|
||||
#'
|
||||
#' @description These functions can be used to calculate the (co-)resistance or susceptibility of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in `summarise()` from the `dplyr` package and also support grouped variables, see *Examples*.
|
||||
#'
|
||||
#' [resistance()] should be used to calculate resistance, [susceptibility()] should be used to calculate susceptibility.\cr
|
||||
#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with [as.rsi()] if needed. Use multiple columns to calculate (the lack of) co-resistance: the probability where one of two drugs have a resistant or susceptible result. See *Examples*.
|
||||
#' @param minimum the minimum allowed number of available (tested) isolates. Any isolate count lower than `minimum` will return `NA` with a warning. The default number of `30` isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see *Source*.
|
||||
#' @param as_percent a [logical] to indicate whether the output must be returned as a hundred fold with % sign (a character). A value of `0.123456` will then be returned as `"12.3%"`.
|
||||
#' @param only_all_tested (for combination therapies, i.e. using more than one variable for `...`): a [logical] to indicate that isolates must be tested for all antibiotics, see section *Combination Therapy* below
|
||||
#' @param data a [data.frame] containing columns with class [`rsi`] (see [as.rsi()])
|
||||
#' @param translate_ab a column name of the [antibiotics] data set to translate the antibiotic abbreviations to, using [ab_property()]
|
||||
#' @inheritParams ab_property
|
||||
#' @param combine_SI a [logical] to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the argument `combine_IR`, but this now follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is `TRUE`.
|
||||
#' @param combine_IR a [logical] to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see argument `combine_SI`.
|
||||
#' @inheritSection as.rsi Interpretation of R and S/I
|
||||
#' @details
|
||||
#' The function [resistance()] is equal to the function [proportion_R()]. The function [susceptibility()] is equal to the function [proportion_SI()].
|
||||
#'
|
||||
#' **Remember that you should filter your data to let it contain only first isolates!** This is needed to exclude duplicates and to reduce selection bias. Use [first_isolate()] to determine them in your data set.
|
||||
#'
|
||||
#' These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the [`count()`][AMR::count()] functions to count isolates. The function [susceptibility()] is essentially equal to `count_susceptible() / count_all()`. *Low counts can influence the outcome - the `proportion` functions may camouflage this, since they only return the proportion (albeit being dependent on the `minimum` argument).*
|
||||
#'
|
||||
#' The function [proportion_df()] takes any variable from `data` that has an [`rsi`] class (created with [as.rsi()]) and calculates the proportions R, I and S. It also supports grouped variables. The function [rsi_df()] works exactly like [proportion_df()], but adds the number of isolates.
|
||||
#' @section Combination Therapy:
|
||||
#' When using more than one variable for `...` (= combination therapy), use `only_all_tested` to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Drug A and Drug B, about how [susceptibility()] works to calculate the %SI:
|
||||
#'
|
||||
#' ```
|
||||
#' --------------------------------------------------------------------
|
||||
#' only_all_tested = FALSE only_all_tested = TRUE
|
||||
#' ----------------------- -----------------------
|
||||
#' Drug A Drug B include as include as include as include as
|
||||
#' numerator denominator numerator denominator
|
||||
#' -------- -------- ---------- ----------- ---------- -----------
|
||||
#' S or I S or I X X X X
|
||||
#' R S or I X X X X
|
||||
#' <NA> S or I X X - -
|
||||
#' S or I R X X X X
|
||||
#' R R - X - X
|
||||
#' <NA> R - - - -
|
||||
#' S or I <NA> X X - -
|
||||
#' R <NA> - - - -
|
||||
#' <NA> <NA> - - - -
|
||||
#' --------------------------------------------------------------------
|
||||
#' ```
|
||||
#'
|
||||
#' Please note that, in combination therapies, for `only_all_tested = TRUE` applies that:
|
||||
#' ```
|
||||
#' count_S() + count_I() + count_R() = count_all()
|
||||
#' proportion_S() + proportion_I() + proportion_R() = 1
|
||||
#' ```
|
||||
#' and that, in combination therapies, for `only_all_tested = FALSE` applies that:
|
||||
#' ```
|
||||
#' count_S() + count_I() + count_R() >= count_all()
|
||||
#' proportion_S() + proportion_I() + proportion_R() >= 1
|
||||
#' ```
|
||||
#'
|
||||
#' Using `only_all_tested` has no impact when only using one antibiotic as input.
|
||||
#' @source **M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition**, 2014, *Clinical and Laboratory Standards Institute (CLSI)*. <https://clsi.org/standards/products/microbiology/documents/m39/>.
|
||||
#' @seealso [AMR::count()] to count resistant and susceptible isolates.
|
||||
#' @return A [double] or, when `as_percent = TRUE`, a [character].
|
||||
#' @rdname proportion
|
||||
#' @aliases portion
|
||||
#' @name proportion
|
||||
#' @export
|
||||
#' @examples
|
||||
#' # example_isolates is a data set available in the AMR package.
|
||||
#' # run ?example_isolates for more info.
|
||||
#'
|
||||
#' # base R ------------------------------------------------------------
|
||||
#' resistance(example_isolates$AMX) # determines %R
|
||||
#' susceptibility(example_isolates$AMX) # determines %S+I
|
||||
#'
|
||||
#' # be more specific
|
||||
#' proportion_S(example_isolates$AMX)
|
||||
#' proportion_SI(example_isolates$AMX)
|
||||
#' proportion_I(example_isolates$AMX)
|
||||
#' proportion_IR(example_isolates$AMX)
|
||||
#' proportion_R(example_isolates$AMX)
|
||||
#'
|
||||
#' # dplyr -------------------------------------------------------------
|
||||
#' \donttest{
|
||||
#' if (require("dplyr")) {
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(r = resistance(CIP),
|
||||
#' n = n_rsi(CIP)) # n_rsi works like n_distinct in dplyr, see ?n_rsi
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(R = resistance(CIP, as_percent = TRUE),
|
||||
#' SI = susceptibility(CIP, as_percent = TRUE),
|
||||
#' n1 = count_all(CIP), # the actual total; sum of all three
|
||||
#' n2 = n_rsi(CIP), # same - analogous to n_distinct
|
||||
#' total = n()) # NOT the number of tested isolates!
|
||||
#'
|
||||
#' # Calculate co-resistance between amoxicillin/clav acid and gentamicin,
|
||||
#' # so we can see that combination therapy does a lot more than mono therapy:
|
||||
#' example_isolates %>% susceptibility(AMC) # %SI = 76.3%
|
||||
#' example_isolates %>% count_all(AMC) # n = 1879
|
||||
#'
|
||||
#' example_isolates %>% susceptibility(GEN) # %SI = 75.4%
|
||||
#' example_isolates %>% count_all(GEN) # n = 1855
|
||||
#'
|
||||
#' example_isolates %>% susceptibility(AMC, GEN) # %SI = 94.1%
|
||||
#' example_isolates %>% count_all(AMC, GEN) # n = 1939
|
||||
#'
|
||||
#'
|
||||
#' # See Details on how `only_all_tested` works. Example:
|
||||
#' example_isolates %>%
|
||||
#' summarise(numerator = count_susceptible(AMC, GEN),
|
||||
#' denominator = count_all(AMC, GEN),
|
||||
#' proportion = susceptibility(AMC, GEN))
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' summarise(numerator = count_susceptible(AMC, GEN, only_all_tested = TRUE),
|
||||
#' denominator = count_all(AMC, GEN, only_all_tested = TRUE),
|
||||
#' proportion = susceptibility(AMC, GEN, only_all_tested = TRUE))
|
||||
#'
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(cipro_p = susceptibility(CIP, as_percent = TRUE),
|
||||
#' cipro_n = count_all(CIP),
|
||||
#' genta_p = susceptibility(GEN, as_percent = TRUE),
|
||||
#' genta_n = count_all(GEN),
|
||||
#' combination_p = susceptibility(CIP, GEN, as_percent = TRUE),
|
||||
#' combination_n = count_all(CIP, GEN))
|
||||
#'
|
||||
#' # Get proportions S/I/R immediately of all rsi columns
|
||||
#' example_isolates %>%
|
||||
#' select(AMX, CIP) %>%
|
||||
#' proportion_df(translate = FALSE)
|
||||
#'
|
||||
#' # It also supports grouping variables
|
||||
#' # (use rsi_df to also include the count)
|
||||
#' example_isolates %>%
|
||||
#' select(hospital_id, AMX, CIP) %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' rsi_df(translate = FALSE)
|
||||
#' }
|
||||
#' }
|
||||
resistance <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
#' @export
|
||||
susceptibility <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
#' @export
|
||||
proportion_R <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
#' @export
|
||||
proportion_IR <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("I", "R"),
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
#' @export
|
||||
proportion_I <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "I",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
#' @export
|
||||
proportion_SI <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
#' @export
|
||||
proportion_S <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "S",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
#' @export
|
||||
proportion_df <- function(data,
|
||||
translate_ab = "name",
|
||||
language = get_AMR_locale(),
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE) {
|
||||
tryCatch(
|
||||
rsi_calc_df(type = "proportion",
|
||||
data = data,
|
||||
translate_ab = translate_ab,
|
||||
language = language,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR,
|
||||
combine_SI_missing = missing(combine_SI)),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
-155
@@ -1,155 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Random MIC Values/Disk Zones/RSI Generation
|
||||
#'
|
||||
#' These functions can be used for generating random MIC values and disk diffusion diameters, for AMR data analysis practice. By providing a microorganism and antimicrobial agent, the generated results will reflect reality as much as possible.
|
||||
#' @param size desired size of the returned vector. If used in a [data.frame] call or `dplyr` verb, will get the current (group) size if left blank.
|
||||
#' @param mo any [character] that can be coerced to a valid microorganism code with [as.mo()]
|
||||
#' @param ab any [character] that can be coerced to a valid antimicrobial agent code with [as.ab()]
|
||||
#' @param prob_RSI a vector of length 3: the probabilities for "R" (1st value), "S" (2nd value) and "I" (3rd value)
|
||||
#' @param ... ignored, only in place to allow future extensions
|
||||
#' @details The base \R function [sample()] is used for generating values.
|
||||
#'
|
||||
#' Generated values are based on the EUCAST `r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))` guideline as implemented in the [rsi_translation] data set. To create specific generated values per bug or drug, set the `mo` and/or `ab` argument.
|
||||
#' @return class `<mic>` for [random_mic()] (see [as.mic()]) and class `<disk>` for [random_disk()] (see [as.disk()])
|
||||
#' @name random
|
||||
#' @rdname random
|
||||
#' @export
|
||||
#' @examples
|
||||
#' random_mic(25)
|
||||
#' random_disk(25)
|
||||
#' random_rsi(25)
|
||||
#'
|
||||
#' \donttest{
|
||||
#' # make the random generation more realistic by setting a bug and/or drug:
|
||||
#' random_mic(25, "Klebsiella pneumoniae") # range 0.0625-64
|
||||
#' random_mic(25, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16
|
||||
#' random_mic(25, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
|
||||
#'
|
||||
#' random_disk(25, "Klebsiella pneumoniae") # range 8-50
|
||||
#' random_disk(25, "Klebsiella pneumoniae", "ampicillin") # range 11-17
|
||||
#' random_disk(25, "Streptococcus pneumoniae", "ampicillin") # range 12-27
|
||||
#' }
|
||||
random_mic <- function(size = NULL, mo = NULL, ab = NULL, ...) {
|
||||
meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE, allow_NULL = TRUE)
|
||||
meet_criteria(mo, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
if (is.null(size)) {
|
||||
size <- NROW(get_current_data(arg_name = "size", call = -3))
|
||||
}
|
||||
random_exec("MIC", size = size, mo = mo, ab = ab)
|
||||
}
|
||||
|
||||
#' @rdname random
|
||||
#' @export
|
||||
random_disk <- function(size = NULL, mo = NULL, ab = NULL, ...) {
|
||||
meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE, allow_NULL = TRUE)
|
||||
meet_criteria(mo, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
if (is.null(size)) {
|
||||
size <- NROW(get_current_data(arg_name = "size", call = -3))
|
||||
}
|
||||
random_exec("DISK", size = size, mo = mo, ab = ab)
|
||||
}
|
||||
|
||||
#' @rdname random
|
||||
#' @export
|
||||
random_rsi <- function(size = NULL, prob_RSI = c(0.33, 0.33, 0.33), ...) {
|
||||
meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE, allow_NULL = TRUE)
|
||||
meet_criteria(prob_RSI, allow_class = c("numeric", "integer"), has_length = 3)
|
||||
if (is.null(size)) {
|
||||
size <- NROW(get_current_data(arg_name = "size", call = -3))
|
||||
}
|
||||
sample(as.rsi(c("R", "S", "I")), size = size, replace = TRUE, prob = prob_RSI)
|
||||
}
|
||||
|
||||
random_exec <- function(type, size, mo = NULL, ab = NULL) {
|
||||
check_dataset_integrity()
|
||||
df <- rsi_translation %pm>%
|
||||
pm_filter(guideline %like% "EUCAST") %pm>%
|
||||
pm_arrange(pm_desc(guideline)) %pm>%
|
||||
subset(guideline == max(guideline) &
|
||||
method == type)
|
||||
|
||||
if (!is.null(mo)) {
|
||||
mo_coerced <- as.mo(mo)
|
||||
mo_include <- c(mo_coerced,
|
||||
as.mo(mo_genus(mo_coerced)),
|
||||
as.mo(mo_family(mo_coerced)),
|
||||
as.mo(mo_order(mo_coerced)))
|
||||
df_new <- df %pm>%
|
||||
subset(mo %in% mo_include)
|
||||
if (nrow(df_new) > 0) {
|
||||
df <- df_new
|
||||
} else {
|
||||
warning_("in `random_", tolower(type), "()`: no rows found that match mo '", mo, "', ignoring argument `mo`")
|
||||
}
|
||||
}
|
||||
|
||||
if (!is.null(ab)) {
|
||||
ab_coerced <- as.ab(ab)
|
||||
df_new <- df %pm>%
|
||||
subset(ab %in% ab_coerced)
|
||||
if (nrow(df_new) > 0) {
|
||||
df <- df_new
|
||||
} else {
|
||||
warning_("in `random_", tolower(type), "()`: no rows found that match ab '", ab, "', ignoring argument `ab`")
|
||||
}
|
||||
}
|
||||
|
||||
if (type == "MIC") {
|
||||
# set range
|
||||
mic_range <- c(0.001, 0.002, 0.005, 0.010, 0.025, 0.0625, 0.125, 0.250, 0.5, 1, 2, 4, 8, 16, 32, 64, 128, 256)
|
||||
|
||||
# get highest/lowest +/- random 1 to 3 higher factors of two
|
||||
max_range <- mic_range[min(length(mic_range),
|
||||
which(mic_range == max(df$breakpoint_R)) + sample(c(1:3), 1))]
|
||||
min_range <- mic_range[max(1,
|
||||
which(mic_range == min(df$breakpoint_S)) - sample(c(1:3), 1))]
|
||||
|
||||
mic_range_new <- mic_range[mic_range <= max_range & mic_range >= min_range]
|
||||
if (length(mic_range_new) == 0) {
|
||||
mic_range_new <- mic_range
|
||||
}
|
||||
out <- as.mic(sample(mic_range_new, size = size, replace = TRUE))
|
||||
# 50% chance that lowest will get <= and highest will get >=
|
||||
if (stats::runif(1) > 0.5) {
|
||||
out[out == min(out)] <- paste0("<=", out[out == min(out)])
|
||||
}
|
||||
if (stats::runif(1) > 0.5) {
|
||||
out[out == max(out)] <- paste0(">=", out[out == max(out)])
|
||||
}
|
||||
return(out)
|
||||
} else if (type == "DISK") {
|
||||
set_range <- seq(from = as.integer(min(df$breakpoint_R) / 1.25),
|
||||
to = as.integer(max(df$breakpoint_S) * 1.25),
|
||||
by = 1)
|
||||
out <- sample(set_range, size = size, replace = TRUE)
|
||||
out[out < 6] <- sample(c(6:10), length(out[out < 6]), replace = TRUE)
|
||||
out[out > 50] <- sample(c(40:50), length(out[out > 50]), replace = TRUE)
|
||||
return(as.disk(out))
|
||||
}
|
||||
}
|
||||
@@ -1,398 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Predict Antimicrobial Resistance
|
||||
#'
|
||||
#' Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns `se_min` and `se_max`. See *Examples* for a real live example.
|
||||
#' @param object model data to be plotted
|
||||
#' @param col_ab column name of `x` containing antimicrobial interpretations (`"R"`, `"I"` and `"S"`)
|
||||
#' @param col_date column name of the date, will be used to calculate years if this column doesn't consist of years already, defaults to the first column of with a date class
|
||||
#' @param year_min lowest year to use in the prediction model, dafaults to the lowest year in `col_date`
|
||||
#' @param year_max highest year to use in the prediction model, defaults to 10 years after today
|
||||
#' @param year_every unit of sequence between lowest year found in the data and `year_max`
|
||||
#' @param minimum minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.
|
||||
#' @param model the statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using `glm(..., family = binomial)`, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See *Details* for all valid options.
|
||||
#' @param I_as_S a [logical] to indicate whether values `"I"` should be treated as `"S"` (will otherwise be treated as `"R"`). The default, `TRUE`, follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section *Interpretation of S, I and R* below.
|
||||
#' @param preserve_measurements a [logical] to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be `NA`.
|
||||
#' @param info a [logical] to indicate whether textual analysis should be printed with the name and [summary()] of the statistical model.
|
||||
#' @param main title of the plot
|
||||
#' @param ribbon a [logical] to indicate whether a ribbon should be shown (default) or error bars
|
||||
#' @param ... arguments passed on to functions
|
||||
#' @inheritSection as.rsi Interpretation of R and S/I
|
||||
#' @inheritParams first_isolate
|
||||
#' @inheritParams graphics::plot
|
||||
#' @details Valid options for the statistical model (argument `model`) are:
|
||||
#' - `"binomial"` or `"binom"` or `"logit"`: a generalised linear regression model with binomial distribution
|
||||
#' - `"loglin"` or `"poisson"`: a generalised log-linear regression model with poisson distribution
|
||||
#' - `"lin"` or `"linear"`: a linear regression model
|
||||
#' @return A [data.frame] with extra class [`resistance_predict`] with columns:
|
||||
#' - `year`
|
||||
#' - `value`, the same as `estimated` when `preserve_measurements = FALSE`, and a combination of `observed` and `estimated` otherwise
|
||||
#' - `se_min`, the lower bound of the standard error with a minimum of `0` (so the standard error will never go below 0%)
|
||||
#' - `se_max` the upper bound of the standard error with a maximum of `1` (so the standard error will never go above 100%)
|
||||
#' - `observations`, the total number of available observations in that year, i.e. \eqn{S + I + R}
|
||||
#' - `observed`, the original observed resistant percentages
|
||||
#' - `estimated`, the estimated resistant percentages, calculated by the model
|
||||
#'
|
||||
#' Furthermore, the model itself is available as an attribute: `attributes(x)$model`, see *Examples*.
|
||||
#' @seealso The [proportion()] functions to calculate resistance
|
||||
#'
|
||||
#' Models: [lm()] [glm()]
|
||||
#' @rdname resistance_predict
|
||||
#' @export
|
||||
#' @importFrom stats predict glm lm
|
||||
#' @examples
|
||||
#' x <- resistance_predict(example_isolates,
|
||||
#' col_ab = "AMX",
|
||||
#' year_min = 2010,
|
||||
#' model = "binomial")
|
||||
#' plot(x)
|
||||
#' \donttest{
|
||||
#' if (require("ggplot2")) {
|
||||
#' ggplot_rsi_predict(x)
|
||||
#' }
|
||||
#'
|
||||
#' # using dplyr:
|
||||
#' if (require("dplyr")) {
|
||||
#' x <- example_isolates %>%
|
||||
#' filter_first_isolate() %>%
|
||||
#' filter(mo_genus(mo) == "Staphylococcus") %>%
|
||||
#' resistance_predict("PEN", model = "binomial")
|
||||
#' plot(x)
|
||||
#'
|
||||
#' # get the model from the object
|
||||
#' mymodel <- attributes(x)$model
|
||||
#' summary(mymodel)
|
||||
#' }
|
||||
#'
|
||||
#' # create nice plots with ggplot2 yourself
|
||||
#' if (require("dplyr") & require("ggplot2")) {
|
||||
#'
|
||||
#' data <- example_isolates %>%
|
||||
#' filter(mo == as.mo("E. coli")) %>%
|
||||
#' resistance_predict(col_ab = "AMX",
|
||||
#' col_date = "date",
|
||||
#' model = "binomial",
|
||||
#' info = FALSE,
|
||||
#' minimum = 15)
|
||||
#' head(data)
|
||||
#' autoplot(data)
|
||||
#' }
|
||||
#' }
|
||||
resistance_predict <- function(x,
|
||||
col_ab,
|
||||
col_date = NULL,
|
||||
year_min = NULL,
|
||||
year_max = NULL,
|
||||
year_every = 1,
|
||||
minimum = 30,
|
||||
model = NULL,
|
||||
I_as_S = TRUE,
|
||||
preserve_measurements = TRUE,
|
||||
info = interactive(),
|
||||
...) {
|
||||
meet_criteria(x, allow_class = "data.frame")
|
||||
meet_criteria(col_ab, allow_class = "character", has_length = 1, is_in = colnames(x))
|
||||
meet_criteria(col_date, allow_class = "character", has_length = 1, is_in = colnames(x), allow_NULL = TRUE)
|
||||
meet_criteria(year_min, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(year_max, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(year_every, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
|
||||
meet_criteria(model, allow_class = c("character", "function"), has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(I_as_S, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(preserve_measurements, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(info, allow_class = "logical", has_length = 1)
|
||||
|
||||
stop_if(is.null(model), 'choose a regression model with the `model` argument, e.g. resistance_predict(..., model = "binomial")')
|
||||
|
||||
dots <- unlist(list(...))
|
||||
if (length(dots) != 0) {
|
||||
# backwards compatibility with old arguments
|
||||
dots.names <- names(dots)
|
||||
if ("tbl" %in% dots.names) {
|
||||
x <- dots[which(dots.names == "tbl")]
|
||||
}
|
||||
if ("I_as_R" %in% dots.names) {
|
||||
warning_("in `resistance_predict()`: I_as_R is deprecated - use I_as_S instead.")
|
||||
}
|
||||
}
|
||||
|
||||
# -- date
|
||||
if (is.null(col_date)) {
|
||||
col_date <- search_type_in_df(x = x, type = "date")
|
||||
stop_if(is.null(col_date), "`col_date` must be set")
|
||||
}
|
||||
stop_ifnot(col_date %in% colnames(x),
|
||||
"column '", col_date, "' not found")
|
||||
|
||||
# no grouped tibbles
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
||||
|
||||
year <- function(x) {
|
||||
# don't depend on lubridate or so, would be overkill for only this function
|
||||
if (all(grepl("^[0-9]{4}$", x))) {
|
||||
as.integer(x)
|
||||
} else {
|
||||
as.integer(format(as.Date(x), "%Y"))
|
||||
}
|
||||
}
|
||||
|
||||
df <- x
|
||||
df[, col_ab] <- droplevels(as.rsi(df[, col_ab, drop = TRUE]))
|
||||
if (I_as_S == TRUE) {
|
||||
# then I as S
|
||||
df[, col_ab] <- gsub("I", "S", df[, col_ab, drop = TRUE])
|
||||
} else {
|
||||
# then I as R
|
||||
df[, col_ab] <- gsub("I", "R", df[, col_ab, drop = TRUE])
|
||||
}
|
||||
df[, col_ab] <- ifelse(is.na(df[, col_ab, drop = TRUE]), 0, df[, col_ab, drop = TRUE])
|
||||
|
||||
# remove rows with NAs
|
||||
df <- subset(df, !is.na(df[, col_ab, drop = TRUE]))
|
||||
df$year <- year(df[, col_date, drop = TRUE])
|
||||
df <- as.data.frame(rbind(table(df[, c("year", col_ab)])),
|
||||
stringsAsFactors = FALSE)
|
||||
df$year <- as.integer(rownames(df))
|
||||
rownames(df) <- NULL
|
||||
|
||||
df <- subset(df, sum(df$R + df$S, na.rm = TRUE) >= minimum)
|
||||
# nolint start
|
||||
df_matrix <- as.matrix(df[, c("R", "S"), drop = FALSE])
|
||||
# nolint end
|
||||
|
||||
stop_if(NROW(df) == 0, "there are no observations")
|
||||
|
||||
year_lowest <- min(df$year)
|
||||
if (is.null(year_min)) {
|
||||
year_min <- year_lowest
|
||||
} else {
|
||||
year_min <- max(year_min, year_lowest, na.rm = TRUE)
|
||||
}
|
||||
if (is.null(year_max)) {
|
||||
year_max <- year(Sys.Date()) + 10
|
||||
}
|
||||
|
||||
years <- list(year = seq(from = year_min, to = year_max, by = year_every))
|
||||
|
||||
if (model %in% c("binomial", "binom", "logit")) {
|
||||
model <- "binomial"
|
||||
model_lm <- with(df, glm(df_matrix ~ year, family = binomial))
|
||||
if (info == TRUE) {
|
||||
cat("\nLogistic regression model (logit) with binomial distribution")
|
||||
cat("\n------------------------------------------------------------\n")
|
||||
print(summary(model_lm))
|
||||
}
|
||||
|
||||
predictmodel <- predict(model_lm, newdata = years, type = "response", se.fit = TRUE)
|
||||
prediction <- predictmodel$fit
|
||||
se <- predictmodel$se.fit
|
||||
|
||||
} else if (model %in% c("loglin", "poisson")) {
|
||||
model <- "poisson"
|
||||
model_lm <- with(df, glm(R ~ year, family = poisson))
|
||||
if (info == TRUE) {
|
||||
cat("\nLog-linear regression model (loglin) with poisson distribution")
|
||||
cat("\n--------------------------------------------------------------\n")
|
||||
print(summary(model_lm))
|
||||
}
|
||||
|
||||
predictmodel <- predict(model_lm, newdata = years, type = "response", se.fit = TRUE)
|
||||
prediction <- predictmodel$fit
|
||||
se <- predictmodel$se.fit
|
||||
|
||||
} else if (model %in% c("lin", "linear")) {
|
||||
model <- "linear"
|
||||
model_lm <- with(df, lm((R / (R + S)) ~ year))
|
||||
if (info == TRUE) {
|
||||
cat("\nLinear regression model")
|
||||
cat("\n-----------------------\n")
|
||||
print(summary(model_lm))
|
||||
}
|
||||
|
||||
predictmodel <- predict(model_lm, newdata = years, se.fit = TRUE)
|
||||
prediction <- predictmodel$fit
|
||||
se <- predictmodel$se.fit
|
||||
|
||||
} else {
|
||||
stop("no valid model selected. See ?resistance_predict.")
|
||||
}
|
||||
|
||||
# prepare the output dataframe
|
||||
df_prediction <- data.frame(year = unlist(years),
|
||||
value = prediction,
|
||||
se_min = prediction - se,
|
||||
se_max = prediction + se,
|
||||
stringsAsFactors = FALSE)
|
||||
|
||||
if (model == "poisson") {
|
||||
df_prediction$value <- as.integer(format(df_prediction$value, scientific = FALSE))
|
||||
df_prediction$se_min <- as.integer(df_prediction$se_min)
|
||||
df_prediction$se_max <- as.integer(df_prediction$se_max)
|
||||
|
||||
} else {
|
||||
# se_max not above 1
|
||||
df_prediction$se_max <- ifelse(df_prediction$se_max > 1, 1, df_prediction$se_max)
|
||||
}
|
||||
# se_min not below 0
|
||||
df_prediction$se_min <- ifelse(df_prediction$se_min < 0, 0, df_prediction$se_min)
|
||||
|
||||
df_observations <- data.frame(year = df$year,
|
||||
observations = df$R + df$S,
|
||||
observed = df$R / (df$R + df$S),
|
||||
stringsAsFactors = FALSE)
|
||||
df_prediction <- df_prediction %pm>%
|
||||
pm_left_join(df_observations, by = "year")
|
||||
df_prediction$estimated <- df_prediction$value
|
||||
|
||||
if (preserve_measurements == TRUE) {
|
||||
# replace estimated data by observed data
|
||||
df_prediction$value <- ifelse(!is.na(df_prediction$observed), df_prediction$observed, df_prediction$value)
|
||||
df_prediction$se_min <- ifelse(!is.na(df_prediction$observed), NA, df_prediction$se_min)
|
||||
df_prediction$se_max <- ifelse(!is.na(df_prediction$observed), NA, df_prediction$se_max)
|
||||
}
|
||||
|
||||
df_prediction$value <- ifelse(df_prediction$value > 1, 1, ifelse(df_prediction$value < 0, 0, df_prediction$value))
|
||||
df_prediction <- df_prediction[order(df_prediction$year), ]
|
||||
|
||||
structure(
|
||||
.Data = df_prediction,
|
||||
class = c("resistance_predict", "data.frame"),
|
||||
I_as_S = I_as_S,
|
||||
model_title = model,
|
||||
model = model_lm,
|
||||
ab = col_ab
|
||||
)
|
||||
}
|
||||
|
||||
#' @rdname resistance_predict
|
||||
#' @export
|
||||
rsi_predict <- resistance_predict
|
||||
|
||||
#' @method plot resistance_predict
|
||||
#' @export
|
||||
#' @importFrom graphics plot axis arrows points
|
||||
#' @rdname resistance_predict
|
||||
plot.resistance_predict <- function(x, main = paste("Resistance Prediction of", x_name), ...) {
|
||||
x_name <- paste0(ab_name(attributes(x)$ab), " (", attributes(x)$ab, ")")
|
||||
meet_criteria(main, allow_class = "character", has_length = 1)
|
||||
|
||||
if (attributes(x)$I_as_S == TRUE) {
|
||||
ylab <- "%R"
|
||||
} else {
|
||||
ylab <- "%IR"
|
||||
}
|
||||
|
||||
plot(x = x$year,
|
||||
y = x$value,
|
||||
ylim = c(0, 1),
|
||||
yaxt = "n", # no y labels
|
||||
pch = 19, # closed dots
|
||||
ylab = paste0("Percentage (", ylab, ")"),
|
||||
xlab = "Year",
|
||||
main = main,
|
||||
sub = paste0("(n = ", sum(x$observations, na.rm = TRUE),
|
||||
", model: ", attributes(x)$model_title, ")"),
|
||||
cex.sub = 0.75)
|
||||
|
||||
|
||||
axis(side = 2, at = seq(0, 1, 0.1), labels = paste0(0:10 * 10, "%"))
|
||||
|
||||
# hack for error bars: https://stackoverflow.com/a/22037078/4575331
|
||||
arrows(x0 = x$year,
|
||||
y0 = x$se_min,
|
||||
x1 = x$year,
|
||||
y1 = x$se_max,
|
||||
length = 0.05, angle = 90, code = 3, lwd = 1.5)
|
||||
|
||||
# overlay grey points for prediction
|
||||
points(x = subset(x, is.na(observations))$year,
|
||||
y = subset(x, is.na(observations))$value,
|
||||
pch = 19,
|
||||
col = "grey40")
|
||||
}
|
||||
|
||||
#' @rdname resistance_predict
|
||||
#' @export
|
||||
ggplot_rsi_predict <- function(x,
|
||||
main = paste("Resistance Prediction of", x_name),
|
||||
ribbon = TRUE,
|
||||
...) {
|
||||
x_name <- paste0(ab_name(attributes(x)$ab), " (", attributes(x)$ab, ")")
|
||||
meet_criteria(main, allow_class = "character", has_length = 1)
|
||||
meet_criteria(ribbon, allow_class = "logical", has_length = 1)
|
||||
|
||||
stop_ifnot_installed("ggplot2")
|
||||
stop_ifnot(inherits(x, "resistance_predict"), "`x` must be a resistance prediction model created with resistance_predict()")
|
||||
|
||||
if (attributes(x)$I_as_S == TRUE) {
|
||||
ylab <- "%R"
|
||||
} else {
|
||||
ylab <- "%IR"
|
||||
}
|
||||
|
||||
p <- ggplot2::ggplot(as.data.frame(x, stringsAsFactors = FALSE),
|
||||
ggplot2::aes(x = year, y = value)) +
|
||||
ggplot2::geom_point(data = subset(x, !is.na(observations)),
|
||||
size = 2) +
|
||||
scale_y_percent(limits = c(0, 1)) +
|
||||
ggplot2::labs(title = main,
|
||||
y = paste0("Percentage (", ylab, ")"),
|
||||
x = "Year",
|
||||
caption = paste0("(n = ", sum(x$observations, na.rm = TRUE),
|
||||
", model: ", attributes(x)$model_title, ")"))
|
||||
|
||||
if (ribbon == TRUE) {
|
||||
p <- p + ggplot2::geom_ribbon(ggplot2::aes(ymin = se_min, ymax = se_max), alpha = 0.25)
|
||||
} else {
|
||||
p <- p + ggplot2::geom_errorbar(ggplot2::aes(ymin = se_min, ymax = se_max), na.rm = TRUE, width = 0.5)
|
||||
}
|
||||
p <- p +
|
||||
# overlay grey points for prediction
|
||||
ggplot2::geom_point(data = subset(x, is.na(observations)),
|
||||
size = 2,
|
||||
colour = "grey40")
|
||||
p
|
||||
}
|
||||
|
||||
#' @method autoplot resistance_predict
|
||||
#' @rdname resistance_predict
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
autoplot.resistance_predict <- function(object,
|
||||
main = paste("Resistance Prediction of", x_name),
|
||||
ribbon = TRUE,
|
||||
...) {
|
||||
x_name <- paste0(ab_name(attributes(object)$ab), " (", attributes(object)$ab, ")")
|
||||
meet_criteria(main, allow_class = "character", has_length = 1)
|
||||
meet_criteria(ribbon, allow_class = "logical", has_length = 1)
|
||||
ggplot_rsi_predict(x = object, main = main, ribbon = ribbon, ...)
|
||||
}
|
||||
|
||||
#' @method fortify resistance_predict
|
||||
#' @noRd
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
fortify.resistance_predict <- function(model, data, ...) {
|
||||
as.data.frame(model)
|
||||
}
|
||||
-365
@@ -1,365 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
dots2vars <- function(...) {
|
||||
# this function is to give more informative output about
|
||||
# variable names in count_* and proportion_* functions
|
||||
dots <- substitute(list(...))
|
||||
as.character(dots)[2:length(dots)]
|
||||
}
|
||||
|
||||
rsi_calc <- function(...,
|
||||
ab_result,
|
||||
minimum = 0,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE,
|
||||
only_count = FALSE) {
|
||||
meet_criteria(ab_result, allow_class = c("character", "numeric", "integer"), has_length = c(1, 2, 3), .call_depth = 1)
|
||||
meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE, .call_depth = 1)
|
||||
meet_criteria(as_percent, allow_class = "logical", has_length = 1, .call_depth = 1)
|
||||
meet_criteria(only_all_tested, allow_class = "logical", has_length = 1, .call_depth = 1)
|
||||
meet_criteria(only_count, allow_class = "logical", has_length = 1, .call_depth = 1)
|
||||
|
||||
data_vars <- dots2vars(...)
|
||||
|
||||
dots_df <- switch(1, ...)
|
||||
if (is.data.frame(dots_df)) {
|
||||
# make sure to remove all other classes like tibbles, data.tables, etc
|
||||
dots_df <- as.data.frame(dots_df, stringsAsFactors = FALSE)
|
||||
}
|
||||
|
||||
dots <- eval(substitute(alist(...)))
|
||||
stop_if(length(dots) == 0, "no variables selected", call = -2)
|
||||
|
||||
stop_if("also_single_tested" %in% names(dots),
|
||||
"`also_single_tested` was replaced by `only_all_tested`.\n",
|
||||
"Please read Details in the help page (`?proportion`) as this may have a considerable impact on your analysis.", call = -2)
|
||||
ndots <- length(dots)
|
||||
|
||||
if (is.data.frame(dots_df)) {
|
||||
# data.frame passed with other columns, like: example_isolates %pm>% proportion_S(AMC, GEN)
|
||||
|
||||
dots <- as.character(dots)
|
||||
# remove first element, it's the data.frame
|
||||
if (length(dots) == 1) {
|
||||
dots <- character(0)
|
||||
} else {
|
||||
dots <- dots[2:length(dots)]
|
||||
}
|
||||
if (length(dots) == 0 | all(dots == "df")) {
|
||||
# for complete data.frames, like example_isolates %pm>% select(AMC, GEN) %pm>% proportion_S()
|
||||
# and the old rsi function, which has "df" as name of the first argument
|
||||
x <- dots_df
|
||||
} else {
|
||||
# get dots that are in column names already, and the ones that will be once evaluated using dots_df or global env
|
||||
# this is to support susceptibility(example_isolates, AMC, any_of(some_vector_with_AB_names))
|
||||
dots <- c(dots[dots %in% colnames(dots_df)],
|
||||
eval(parse(text = dots[!dots %in% colnames(dots_df)]), envir = dots_df, enclos = globalenv()))
|
||||
dots_not_exist <- dots[!dots %in% colnames(dots_df)]
|
||||
stop_if(length(dots_not_exist) > 0, "column(s) not found: ", vector_and(dots_not_exist, quotes = TRUE), call = -2)
|
||||
x <- dots_df[, dots, drop = FALSE]
|
||||
}
|
||||
} else if (ndots == 1) {
|
||||
# only 1 variable passed (can also be data.frame), like: proportion_S(example_isolates$AMC) and example_isolates$AMC %pm>% proportion_S()
|
||||
x <- dots_df
|
||||
} else {
|
||||
# multiple variables passed without pipe, like: proportion_S(example_isolates$AMC, example_isolates$GEN)
|
||||
x <- NULL
|
||||
try(x <- as.data.frame(dots, stringsAsFactors = FALSE), silent = TRUE)
|
||||
if (is.null(x)) {
|
||||
# support for example_isolates %pm>% group_by(hospital_id) %pm>% summarise(amox = susceptibility(GEN, AMX))
|
||||
x <- as.data.frame(list(...), stringsAsFactors = FALSE)
|
||||
}
|
||||
}
|
||||
|
||||
if (is.null(x)) {
|
||||
warning_("argument is NULL (check if columns exist): returning NA")
|
||||
if (as_percent == TRUE) {
|
||||
return(NA_character_)
|
||||
} else {
|
||||
return(NA_real_)
|
||||
}
|
||||
}
|
||||
|
||||
print_warning <- FALSE
|
||||
|
||||
ab_result <- as.rsi(ab_result)
|
||||
|
||||
if (is.data.frame(x)) {
|
||||
rsi_integrity_check <- character(0)
|
||||
for (i in seq_len(ncol(x))) {
|
||||
# check integrity of columns: force <rsi> class
|
||||
if (!is.rsi(x[, i, drop = TRUE])) {
|
||||
rsi_integrity_check <- c(rsi_integrity_check, as.character(x[, i, drop = TRUE]))
|
||||
x[, i] <- suppressWarnings(as.rsi(x[, i, drop = TRUE])) # warning will be given later
|
||||
print_warning <- TRUE
|
||||
}
|
||||
}
|
||||
if (length(rsi_integrity_check) > 0) {
|
||||
# this will give a warning for invalid results, of all input columns (so only 1 warning)
|
||||
rsi_integrity_check <- as.rsi(rsi_integrity_check)
|
||||
}
|
||||
|
||||
x_transposed <- as.list(as.data.frame(t(x), stringsAsFactors = FALSE))
|
||||
if (only_all_tested == TRUE) {
|
||||
# no NAs in any column
|
||||
y <- apply(X = as.data.frame(lapply(x, as.integer), stringsAsFactors = FALSE),
|
||||
MARGIN = 1,
|
||||
FUN = min)
|
||||
numerator <- sum(as.integer(y) %in% as.integer(ab_result), na.rm = TRUE)
|
||||
denominator <- sum(vapply(FUN.VALUE = logical(1), x_transposed, function(y) !(any(is.na(y)))))
|
||||
} else {
|
||||
# may contain NAs in any column
|
||||
other_values <- setdiff(c(NA, levels(ab_result)), ab_result)
|
||||
numerator <- sum(vapply(FUN.VALUE = logical(1), x_transposed, function(y) any(y %in% ab_result, na.rm = TRUE)))
|
||||
denominator <- sum(vapply(FUN.VALUE = logical(1), x_transposed, function(y) !(all(y %in% other_values) & any(is.na(y)))))
|
||||
}
|
||||
} else {
|
||||
# x is not a data.frame
|
||||
if (!is.rsi(x)) {
|
||||
x <- as.rsi(x)
|
||||
print_warning <- TRUE
|
||||
}
|
||||
numerator <- sum(x %in% ab_result, na.rm = TRUE)
|
||||
denominator <- sum(x %in% levels(ab_result), na.rm = TRUE)
|
||||
}
|
||||
|
||||
if (print_warning == TRUE) {
|
||||
if (message_not_thrown_before("rsi_calc")) {
|
||||
warning_("Increase speed by transforming to class <rsi> on beforehand:\n",
|
||||
" your_data %>% mutate_if(is.rsi.eligible, as.rsi)\n",
|
||||
" your_data %>% mutate(across(where(is.rsi.eligible), as.rsi))",
|
||||
call = FALSE)
|
||||
}
|
||||
}
|
||||
|
||||
if (only_count == TRUE) {
|
||||
return(numerator)
|
||||
}
|
||||
|
||||
if (denominator < minimum) {
|
||||
if (data_vars != "") {
|
||||
data_vars <- paste(" for", data_vars)
|
||||
# also add group name if used in dplyr::group_by()
|
||||
cur_group <- import_fn("cur_group", "dplyr", error_on_fail = FALSE)
|
||||
if (!is.null(cur_group)) {
|
||||
group_df <- tryCatch(cur_group(), error = function(e) data.frame())
|
||||
if (NCOL(group_df) > 0) {
|
||||
# transform factors to characters
|
||||
group <- vapply(FUN.VALUE = character(1), group_df, function(x) {
|
||||
if (is.numeric(x)) {
|
||||
format(x)
|
||||
} else if (is.logical(x)) {
|
||||
as.character(x)
|
||||
} else {
|
||||
paste0('"', x, '"')
|
||||
}
|
||||
})
|
||||
data_vars <- paste0(data_vars, " in group: ", paste0(names(group), " = ", group, collapse = ", "))
|
||||
}
|
||||
}
|
||||
}
|
||||
warning_("Introducing NA: ",
|
||||
ifelse(denominator == 0, "no", paste("only", denominator)),
|
||||
" results available",
|
||||
data_vars,
|
||||
" (`minimum` = ", minimum, ").", call = FALSE)
|
||||
fraction <- NA_real_
|
||||
} else {
|
||||
fraction <- numerator / denominator
|
||||
fraction[is.nan(fraction)] <- NA_real_
|
||||
}
|
||||
|
||||
if (as_percent == TRUE) {
|
||||
percentage(fraction, digits = 1)
|
||||
} else {
|
||||
fraction
|
||||
}
|
||||
}
|
||||
|
||||
rsi_calc_df <- function(type, # "proportion", "count" or "both"
|
||||
data,
|
||||
translate_ab = "name",
|
||||
language = get_AMR_locale(),
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE,
|
||||
combine_SI_missing = FALSE) {
|
||||
meet_criteria(type, is_in = c("proportion", "count", "both"), has_length = 1, .call_depth = 1)
|
||||
meet_criteria(data, allow_class = "data.frame", contains_column_class = "rsi", .call_depth = 1)
|
||||
meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE, .call_depth = 1)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE, .call_depth = 1)
|
||||
meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE, .call_depth = 1)
|
||||
meet_criteria(as_percent, allow_class = "logical", has_length = 1, .call_depth = 1)
|
||||
meet_criteria(combine_SI, allow_class = "logical", has_length = 1, .call_depth = 1)
|
||||
meet_criteria(combine_SI_missing, allow_class = "logical", has_length = 1, .call_depth = 1)
|
||||
|
||||
check_dataset_integrity()
|
||||
|
||||
if (isTRUE(combine_IR) & isTRUE(combine_SI_missing)) {
|
||||
combine_SI <- FALSE
|
||||
}
|
||||
stop_if(isTRUE(combine_SI) & isTRUE(combine_IR), "either `combine_SI` or `combine_IR` can be TRUE, not both", call = -2)
|
||||
|
||||
translate_ab <- get_translate_ab(translate_ab)
|
||||
|
||||
# select only groups and antibiotics
|
||||
if (is_null_or_grouped_tbl(data)) {
|
||||
data_has_groups <- TRUE
|
||||
groups <- setdiff(names(attributes(data)$groups), ".rows")
|
||||
data <- data[, c(groups, colnames(data)[vapply(FUN.VALUE = logical(1), data, is.rsi)]), drop = FALSE]
|
||||
} else {
|
||||
data_has_groups <- FALSE
|
||||
data <- data[, colnames(data)[vapply(FUN.VALUE = logical(1), data, is.rsi)], drop = FALSE]
|
||||
}
|
||||
|
||||
data <- as.data.frame(data, stringsAsFactors = FALSE)
|
||||
if (isTRUE(combine_SI) | isTRUE(combine_IR)) {
|
||||
for (i in seq_len(ncol(data))) {
|
||||
if (is.rsi(data[, i, drop = TRUE])) {
|
||||
data[, i] <- as.character(data[, i, drop = TRUE])
|
||||
if (isTRUE(combine_SI)) {
|
||||
data[, i] <- gsub("(I|S)", "SI", data[, i, drop = TRUE])
|
||||
} else if (isTRUE(combine_IR)) {
|
||||
data[, i] <- gsub("(I|R)", "IR", data[, i, drop = TRUE])
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
sum_it <- function(.data) {
|
||||
out <- data.frame(antibiotic = character(0),
|
||||
interpretation = character(0),
|
||||
value = double(0),
|
||||
isolates = integer(0),
|
||||
stringsAsFactors = FALSE)
|
||||
if (data_has_groups) {
|
||||
group_values <- unique(.data[, which(colnames(.data) %in% groups), drop = FALSE])
|
||||
rownames(group_values) <- NULL
|
||||
.data <- .data[, which(!colnames(.data) %in% groups), drop = FALSE]
|
||||
}
|
||||
for (i in seq_len(ncol(.data))) {
|
||||
values <- .data[, i, drop = TRUE]
|
||||
if (isTRUE(combine_SI)) {
|
||||
values <- factor(values, levels = c("SI", "R"), ordered = TRUE)
|
||||
} else if (isTRUE(combine_IR)) {
|
||||
values <- factor(values, levels = c("S", "IR"), ordered = TRUE)
|
||||
} else {
|
||||
values <- factor(values, levels = c("S", "I", "R"), ordered = TRUE)
|
||||
}
|
||||
col_results <- as.data.frame(as.matrix(table(values)), stringsAsFactors = FALSE)
|
||||
col_results$interpretation <- rownames(col_results)
|
||||
col_results$isolates <- col_results[, 1, drop = TRUE]
|
||||
if (NROW(col_results) > 0 && sum(col_results$isolates, na.rm = TRUE) > 0) {
|
||||
if (sum(col_results$isolates, na.rm = TRUE) >= minimum) {
|
||||
col_results$value <- col_results$isolates / sum(col_results$isolates, na.rm = TRUE)
|
||||
} else {
|
||||
col_results$value <- rep(NA_real_, NROW(col_results))
|
||||
}
|
||||
out_new <- data.frame(antibiotic = ifelse(isFALSE(translate_ab),
|
||||
colnames(.data)[i],
|
||||
ab_property(colnames(.data)[i], property = translate_ab, language = language)),
|
||||
interpretation = col_results$interpretation,
|
||||
value = col_results$value,
|
||||
isolates = col_results$isolates,
|
||||
stringsAsFactors = FALSE)
|
||||
if (data_has_groups) {
|
||||
if (nrow(group_values) < nrow(out_new)) {
|
||||
# repeat group_values for the number of rows in out_new
|
||||
repeated <- rep(seq_len(nrow(group_values)),
|
||||
each = nrow(out_new) / nrow(group_values))
|
||||
group_values <- group_values[repeated, , drop = FALSE]
|
||||
}
|
||||
out_new <- cbind(group_values, out_new)
|
||||
}
|
||||
out <- rbind(out, out_new, stringsAsFactors = FALSE)
|
||||
}
|
||||
}
|
||||
out
|
||||
}
|
||||
|
||||
# based on pm_apply_grouped_function
|
||||
apply_group <- function(.data, fn, groups, drop = FALSE, ...) {
|
||||
grouped <- pm_split_into_groups(.data, groups, drop)
|
||||
res <- do.call(rbind, unname(lapply(grouped, fn, ...)))
|
||||
if (any(groups %in% colnames(res))) {
|
||||
class(res) <- c("grouped_data", class(res))
|
||||
res <- pm_set_groups(res, groups[groups %in% colnames(res)])
|
||||
}
|
||||
res
|
||||
}
|
||||
|
||||
if (data_has_groups) {
|
||||
out <- apply_group(data, "sum_it", groups)
|
||||
} else {
|
||||
out <- sum_it(data)
|
||||
}
|
||||
|
||||
# apply factors for right sorting in interpretation
|
||||
if (isTRUE(combine_SI)) {
|
||||
out$interpretation <- factor(out$interpretation, levels = c("SI", "R"), ordered = TRUE)
|
||||
} else if (isTRUE(combine_IR)) {
|
||||
out$interpretation <- factor(out$interpretation, levels = c("S", "IR"), ordered = TRUE)
|
||||
} else {
|
||||
# don't use as.rsi() here, as it would add the class <rsi> and we would like
|
||||
# the same data structure as output, regardless of input
|
||||
out$interpretation <- factor(out$interpretation, levels = c("S", "I", "R"), ordered = TRUE)
|
||||
}
|
||||
|
||||
if (data_has_groups) {
|
||||
# ordering by the groups and two more: "antibiotic" and "interpretation"
|
||||
out <- pm_ungroup(out[do.call("order", out[, seq_len(length(groups) + 2)]), ])
|
||||
} else {
|
||||
out <- out[order(out$antibiotic, out$interpretation), ]
|
||||
}
|
||||
|
||||
if (type == "proportion") {
|
||||
out <- subset(out, select = -c(isolates))
|
||||
} else if (type == "count") {
|
||||
out$value <- out$isolates
|
||||
out <- subset(out, select = -c(isolates))
|
||||
}
|
||||
|
||||
rownames(out) <- NULL
|
||||
class(out) <- c("rsi_df", class(out))
|
||||
out
|
||||
}
|
||||
|
||||
get_translate_ab <- function(translate_ab) {
|
||||
translate_ab <- as.character(translate_ab)[1L]
|
||||
if (translate_ab %in% c("TRUE", "official")) {
|
||||
return("name")
|
||||
} else if (translate_ab %in% c(NA_character_, "FALSE")) {
|
||||
return(FALSE)
|
||||
} else {
|
||||
translate_ab <- tolower(translate_ab)
|
||||
stop_ifnot(translate_ab %in% colnames(AMR::antibiotics),
|
||||
"invalid value for 'translate_ab', this must be a column name of the antibiotics data set\n",
|
||||
"or TRUE (equals 'name') or FALSE to not translate at all.",
|
||||
call = FALSE)
|
||||
translate_ab
|
||||
}
|
||||
}
|
||||
-45
@@ -1,45 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' @rdname proportion
|
||||
#' @export
|
||||
rsi_df <- function(data,
|
||||
translate_ab = "name",
|
||||
language = get_AMR_locale(),
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE) {
|
||||
rsi_calc_df(type = "both",
|
||||
data = data,
|
||||
translate_ab = translate_ab,
|
||||
language = language,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR,
|
||||
combine_SI_missing = missing(combine_SI))
|
||||
|
||||
}
|
||||
@@ -1,70 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Skewness of the Sample
|
||||
#'
|
||||
#' @description Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.
|
||||
#'
|
||||
#' When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0.
|
||||
#' @param x a vector of values, a [matrix] or a [data.frame]
|
||||
#' @param na.rm a [logical] value indicating whether `NA` values should be stripped before the computation proceeds
|
||||
#' @seealso [kurtosis()]
|
||||
#' @rdname skewness
|
||||
#' @export
|
||||
#' @examples
|
||||
#' skewness(runif(1000))
|
||||
skewness <- function(x, na.rm = FALSE) {
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
UseMethod("skewness")
|
||||
}
|
||||
|
||||
#' @method skewness default
|
||||
#' @rdname skewness
|
||||
#' @export
|
||||
skewness.default <- function(x, na.rm = FALSE) {
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
x <- as.vector(x)
|
||||
if (na.rm == TRUE) {
|
||||
x <- x[!is.na(x)]
|
||||
}
|
||||
n <- length(x)
|
||||
(sum((x - mean(x))^3) / n) / (sum((x - mean(x)) ^ 2) / n) ^ (3 / 2)
|
||||
}
|
||||
|
||||
#' @method skewness matrix
|
||||
#' @rdname skewness
|
||||
#' @export
|
||||
skewness.matrix <- function(x, na.rm = FALSE) {
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
apply(x, 2, skewness.default, na.rm = na.rm)
|
||||
}
|
||||
|
||||
#' @method skewness data.frame
|
||||
#' @rdname skewness
|
||||
#' @export
|
||||
skewness.data.frame <- function(x, na.rm = FALSE) {
|
||||
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
|
||||
vapply(FUN.VALUE = double(1), x, skewness.default, na.rm = na.rm)
|
||||
}
|
||||
Binary file not shown.
-215
@@ -1,215 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Translate Strings from the AMR Package
|
||||
#'
|
||||
#' For language-dependent output of AMR functions, like [mo_name()], [mo_gramstain()], [mo_type()] and [ab_name()].
|
||||
#' @param x text to translate
|
||||
#' @param lang language to choose. Use one of these supported language names or ISO-639-1 codes: `r paste0('"', sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), '" ("' , LANGUAGES_SUPPORTED, '")', collapse = ", ")`.
|
||||
#' @details The currently `r length(LANGUAGES_SUPPORTED)` supported languages are `r vector_and(sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), quotes = FALSE, sort = FALSE)`. All these languages have translations available for all antimicrobial agents and colloquial microorganism names.
|
||||
#'
|
||||
#' Please read about adding or updating a language in [our Wiki](https://github.com/msberends/AMR/wiki/).
|
||||
#'
|
||||
#' ## Changing the Default Language
|
||||
#' The system language will be used at default (as returned by `Sys.getenv("LANG")` or, if `LANG` is not set, [Sys.getlocale("LC_COLLATE")]), if that language is supported. But the language to be used can be overwritten in two ways and will be checked in this order:
|
||||
#'
|
||||
#' 1. Setting the R option `AMR_locale`, either by using `set_AMR_locale()` or by running e.g. `options(AMR_locale = "de")`.
|
||||
#'
|
||||
#' Note that setting an \R option only works in the same session. Save the command `options(AMR_locale = "(your language)")` to your `.Rprofile` file to apply it for every session.
|
||||
#' 2. Setting the system variable `LANGUAGE` or `LANG`, e.g. by adding `LANGUAGE="de_DE.utf8"` to your `.Renviron` file in your home directory.
|
||||
#'
|
||||
#' Thus, if the R option `AMR_locale` is set, the system variables `LANGUAGE` and `LANG` will be ignored.
|
||||
#' @rdname translate
|
||||
#' @name translate
|
||||
#' @export
|
||||
#' @examples
|
||||
#' # Current settings (based on system language)
|
||||
#' ab_name("Ciprofloxacin")
|
||||
#' mo_name("Coagulase-negative Staphylococcus")
|
||||
#'
|
||||
#' # setting another language
|
||||
#' set_AMR_locale("Greek")
|
||||
#' ab_name("Ciprofloxacin")
|
||||
#' mo_name("Coagulase-negative Staphylococcus")
|
||||
#'
|
||||
#' set_AMR_locale("Spanish")
|
||||
#' ab_name("Ciprofloxacin")
|
||||
#' mo_name("Coagulase-negative Staphylococcus")
|
||||
#'
|
||||
#' # set_AMR_locale() understands endonyms, English exonyms, and ISO-639-1:
|
||||
#' set_AMR_locale("Deutsch")
|
||||
#' set_AMR_locale("German")
|
||||
#' set_AMR_locale("de")
|
||||
#'
|
||||
#' # reset to system default
|
||||
#' reset_AMR_locale()
|
||||
get_AMR_locale <- function() {
|
||||
if (!is.null(getOption("AMR_locale", default = NULL))) {
|
||||
return(validate_language(getOption("AMR_locale"), extra_txt = "set with `options(AMR_locale = ...)`"))
|
||||
}
|
||||
|
||||
lang <- ""
|
||||
# now check the LANGUAGE system variable - return it if set
|
||||
if (!identical("", Sys.getenv("LANGUAGE"))) {
|
||||
lang <- Sys.getenv("LANGUAGE")
|
||||
}
|
||||
if (!identical("", Sys.getenv("LANG"))) {
|
||||
lang <- Sys.getenv("LANG")
|
||||
}
|
||||
if (lang == "") {
|
||||
lang <- Sys.getlocale("LC_COLLATE")
|
||||
}
|
||||
|
||||
lang <- find_language(lang)
|
||||
if (lang != "en" && interactive() && message_not_thrown_before("get_AMR_locale", entire_session = TRUE)) {
|
||||
message_("Assuming the ", LANGUAGES_SUPPORTED_NAMES[[lang]]$exonym, " language (",
|
||||
LANGUAGES_SUPPORTED_NAMES[[lang]]$endonym, ") for the AMR package. Change this with `set_AMR_locale()`. ",
|
||||
"This note will be shown once per session.")
|
||||
}
|
||||
lang
|
||||
}
|
||||
|
||||
#' @rdname translate
|
||||
#' @export
|
||||
set_AMR_locale <- function(lang) {
|
||||
lang <- validate_language(lang)
|
||||
options(AMR_locale = lang)
|
||||
message_("Using the ", LANGUAGES_SUPPORTED_NAMES[[lang]]$exonym, " language (", LANGUAGES_SUPPORTED_NAMES[[lang]]$endonym, ") for the AMR package for this session.")
|
||||
}
|
||||
|
||||
#' @rdname translate
|
||||
#' @export
|
||||
reset_AMR_locale <- function() {
|
||||
options(AMR_locale = NULL)
|
||||
}
|
||||
|
||||
#' @rdname translate
|
||||
#' @export
|
||||
translate_AMR <- function(x, language = get_AMR_locale()) {
|
||||
translate_into_language(x, language = language)
|
||||
}
|
||||
|
||||
validate_language <- function(language, extra_txt = character(0)) {
|
||||
if (trimws(tolower(language)) %in% c("en", "english", "", "false", NA)) {
|
||||
return("en")
|
||||
}
|
||||
lang <- find_language(language, fallback = FALSE)
|
||||
stop_ifnot(length(lang) > 0 && lang %in% LANGUAGES_SUPPORTED,
|
||||
"unsupported language for AMR package", extra_txt, ": \"", language, "\". Use one of these language names or ISO-639-1 codes: ",
|
||||
paste0('"', vapply(FUN.VALUE = character(1), LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]),
|
||||
'" ("' , LANGUAGES_SUPPORTED, '")', collapse = ", "),
|
||||
call = FALSE)
|
||||
lang
|
||||
}
|
||||
|
||||
find_language <- function(lang, fallback = TRUE) {
|
||||
lang <- Map(function(l, n, check = lang) {
|
||||
grepl(paste0("^(", l[1], "|", l[2], "|",
|
||||
n, "(_|$)|", toupper(n), "(_|$))"),
|
||||
check,
|
||||
ignore.case = FALSE,
|
||||
perl = TRUE,
|
||||
useBytes = FALSE)
|
||||
},
|
||||
LANGUAGES_SUPPORTED_NAMES,
|
||||
LANGUAGES_SUPPORTED,
|
||||
USE.NAMES = TRUE)
|
||||
lang <- names(which(lang == TRUE))
|
||||
if (isTRUE(fallback) && length(lang) == 0) {
|
||||
# other language -> set to English
|
||||
lang <- "en"
|
||||
}
|
||||
lang
|
||||
}
|
||||
|
||||
# translate strings based on inst/translations.tsv
|
||||
translate_into_language <- function(from,
|
||||
language = get_AMR_locale(),
|
||||
only_unknown = FALSE,
|
||||
only_affect_ab_names = FALSE,
|
||||
only_affect_mo_names = FALSE) {
|
||||
|
||||
if (is.null(language)) {
|
||||
return(from)
|
||||
}
|
||||
if (language %in% c("en", "", NA)) {
|
||||
return(from)
|
||||
}
|
||||
|
||||
df_trans <- TRANSLATIONS # internal data file
|
||||
from.bak <- from
|
||||
from_unique <- unique(from)
|
||||
from_unique_translated <- from_unique
|
||||
|
||||
# get ISO-639-1 of language
|
||||
lang <- validate_language(language)
|
||||
# only keep lines where translation is available for this language
|
||||
df_trans <- df_trans[which(!is.na(df_trans[, lang, drop = TRUE])), , drop = FALSE]
|
||||
# and where the original string is not equal to the string in the target language
|
||||
df_trans <- df_trans[which(df_trans[, "pattern", drop = TRUE] != df_trans[, lang, drop = TRUE]), , drop = FALSE]
|
||||
if (only_unknown == TRUE) {
|
||||
df_trans <- subset(df_trans, pattern %like% "unknown")
|
||||
}
|
||||
if (only_affect_ab_names == TRUE) {
|
||||
df_trans <- subset(df_trans, affect_ab_name == TRUE)
|
||||
}
|
||||
if (only_affect_mo_names == TRUE) {
|
||||
df_trans <- subset(df_trans, affect_mo_name == TRUE)
|
||||
}
|
||||
if (NROW(df_trans) == 0) {
|
||||
return(from)
|
||||
}
|
||||
|
||||
# default: case sensitive if value if 'case_sensitive' is missing:
|
||||
df_trans$case_sensitive[is.na(df_trans$case_sensitive)] <- TRUE
|
||||
# default: not using regular expressions if 'regular_expr' is missing:
|
||||
df_trans$regular_expr[is.na(df_trans$regular_expr)] <- FALSE
|
||||
|
||||
# check if text to look for is in one of the patterns
|
||||
any_form_in_patterns <- tryCatch(
|
||||
any(from_unique %like% paste0("(", paste(gsub(" +\\(.*", "", df_trans$pattern), collapse = "|"), ")")),
|
||||
error = function(e) {
|
||||
warning_("Translation not possible. Please open an issue on GitHub (https://github.com/msberends/AMR/issues).")
|
||||
return(FALSE)
|
||||
})
|
||||
|
||||
if (NROW(df_trans) == 0 | !any_form_in_patterns) {
|
||||
return(from)
|
||||
}
|
||||
|
||||
lapply(seq_len(nrow(df_trans)),
|
||||
function(i) from_unique_translated <<- gsub(pattern = df_trans$pattern[i],
|
||||
replacement = df_trans[i, lang, drop = TRUE],
|
||||
x = from_unique_translated,
|
||||
ignore.case = !df_trans$case_sensitive[i] & df_trans$regular_expr[i],
|
||||
fixed = !df_trans$regular_expr[i],
|
||||
perl = df_trans$regular_expr[i]))
|
||||
|
||||
# force UTF-8 for diacritics
|
||||
from_unique_translated <- enc2utf8(from_unique_translated)
|
||||
|
||||
# a kind of left join to get all results back
|
||||
from_unique_translated[match(from.bak, from_unique)]
|
||||
}
|
||||
@@ -1,86 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
# These are all S3 implementations for the vctrs package,
|
||||
# that is used internally by tidyverse packages such as dplyr.
|
||||
# They are to convert AMR-specific classes to bare characters and integers.
|
||||
# All of them will be exported using s3_register() in R/zzz.R when loading the package.
|
||||
|
||||
# see https://github.com/tidyverse/dplyr/issues/5955 why this is required
|
||||
|
||||
# S3: ab_selector
|
||||
vec_ptype2.character.ab_selector <- function(x, y, ...) {
|
||||
x
|
||||
}
|
||||
vec_ptype2.ab_selector.character <- function(x, y, ...) {
|
||||
y
|
||||
}
|
||||
vec_cast.character.ab_selector <- function(x, to, ...) {
|
||||
unclass(x)
|
||||
}
|
||||
|
||||
# S3: ab_selector_any_all
|
||||
vec_ptype2.logical.ab_selector_any_all <- function(x, y, ...) {
|
||||
x
|
||||
}
|
||||
vec_ptype2.ab_selector_any_all.logical <- function(x, y, ...) {
|
||||
y
|
||||
}
|
||||
vec_cast.logical.ab_selector_any_all <- function(x, to, ...) {
|
||||
unclass(x)
|
||||
}
|
||||
|
||||
# S3: ab
|
||||
vec_ptype2.character.ab <- function(x, y, ...) {
|
||||
x
|
||||
}
|
||||
vec_ptype2.ab.character <- function(x, y, ...) {
|
||||
y
|
||||
}
|
||||
vec_cast.character.ab <- function(x, to, ...) {
|
||||
unclass(x)
|
||||
}
|
||||
|
||||
# S3: mo
|
||||
vec_ptype2.character.mo <- function(x, y, ...) {
|
||||
x
|
||||
}
|
||||
vec_ptype2.mo.character <- function(x, y, ...) {
|
||||
y
|
||||
}
|
||||
vec_cast.character.mo <- function(x, to, ...) {
|
||||
unclass(x)
|
||||
}
|
||||
|
||||
# S3: disk
|
||||
vec_ptype2.integer.disk <- function(x, y, ...) {
|
||||
x
|
||||
}
|
||||
vec_ptype2.disk.integer <- function(x, y, ...) {
|
||||
y
|
||||
}
|
||||
vec_cast.integer.disk <- function(x, to, ...) {
|
||||
unclass(x)
|
||||
}
|
||||
@@ -1,46 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' WHOCC: WHO Collaborating Centre for Drug Statistics Methodology
|
||||
#'
|
||||
#' All antimicrobial drugs and their official names, ATC codes, ATC groups and defined daily dose (DDD) are included in this package, using the WHO Collaborating Centre for Drug Statistics Methodology.
|
||||
#' @section WHOCC:
|
||||
#' \if{html}{\figure{logo_who.png}{options: height="60" style=margin-bottom:"5"} \cr}
|
||||
#' This package contains **all ~550 antibiotic, antimycotic and antiviral drugs** and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <https://www.whocc.no>) and the Pharmaceuticals Community Register of the European Commission (<https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm>).
|
||||
#'
|
||||
#' These have become the gold standard for international drug utilisation monitoring and research.
|
||||
#'
|
||||
#' The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.
|
||||
#'
|
||||
#' **NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.** See <https://www.whocc.no/copyright_disclaimer/.>
|
||||
|
||||
#' @name WHOCC
|
||||
#' @rdname WHOCC
|
||||
#' @examples
|
||||
#' as.ab("meropenem")
|
||||
#' ab_name("J01DH02")
|
||||
#'
|
||||
#' ab_tradenames("flucloxacillin")
|
||||
NULL
|
||||
@@ -1,160 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
# set up package environment, used by numerous AMR functions
|
||||
pkg_env <- new.env(hash = FALSE)
|
||||
pkg_env$mo_failed <- character(0)
|
||||
pkg_env$mo_field_abbreviations <- c("AIEC", "ATEC", "BORSA", "CRSM", "DAEC", "EAEC",
|
||||
"EHEC", "EIEC", "EPEC", "ETEC", "GISA", "MRPA",
|
||||
"MRSA", "MRSE", "MSSA", "MSSE", "NMEC", "PISP",
|
||||
"PRSP", "STEC", "UPEC", "VISA", "VISP", "VRE",
|
||||
"VRSA", "VRSP")
|
||||
|
||||
# determine info icon for messages
|
||||
utf8_supported <- isTRUE(base::l10n_info()$`UTF-8`)
|
||||
is_latex <- tryCatch(import_fn("is_latex_output", "knitr", error_on_fail = FALSE)(),
|
||||
error = function(e) FALSE)
|
||||
if (utf8_supported && !is_latex) {
|
||||
# \u2139 is a symbol officially named 'information source'
|
||||
pkg_env$info_icon <- "\u2139"
|
||||
} else {
|
||||
pkg_env$info_icon <- "i"
|
||||
}
|
||||
|
||||
.onLoad <- function(...) {
|
||||
# Support for tibble headers (type_sum) and tibble columns content (pillar_shaft)
|
||||
# without the need to depend on other packages. This was suggested by the
|
||||
# developers of the vctrs package:
|
||||
# https://github.com/r-lib/vctrs/blob/05968ce8e669f73213e3e894b5f4424af4f46316/R/register-s3.R
|
||||
s3_register("pillar::pillar_shaft", "ab")
|
||||
s3_register("pillar::pillar_shaft", "mo")
|
||||
s3_register("pillar::pillar_shaft", "rsi")
|
||||
s3_register("pillar::pillar_shaft", "mic")
|
||||
s3_register("pillar::pillar_shaft", "disk")
|
||||
s3_register("tibble::type_sum", "ab")
|
||||
s3_register("tibble::type_sum", "mo")
|
||||
s3_register("tibble::type_sum", "rsi")
|
||||
s3_register("tibble::type_sum", "mic")
|
||||
s3_register("tibble::type_sum", "disk")
|
||||
# Support for frequency tables from the cleaner package
|
||||
s3_register("cleaner::freq", "mo")
|
||||
s3_register("cleaner::freq", "rsi")
|
||||
# Support for skim() from the skimr package
|
||||
if (pkg_is_available("skimr", also_load = FALSE, min_version = "2.0.0")) {
|
||||
s3_register("skimr::get_skimmers", "mo")
|
||||
s3_register("skimr::get_skimmers", "rsi")
|
||||
s3_register("skimr::get_skimmers", "mic")
|
||||
s3_register("skimr::get_skimmers", "disk")
|
||||
}
|
||||
# Support for autoplot() from the ggplot2 package
|
||||
s3_register("ggplot2::autoplot", "rsi")
|
||||
s3_register("ggplot2::autoplot", "mic")
|
||||
s3_register("ggplot2::autoplot", "disk")
|
||||
s3_register("ggplot2::autoplot", "resistance_predict")
|
||||
# Support for fortify from the ggplot2 package
|
||||
s3_register("ggplot2::fortify", "rsi")
|
||||
s3_register("ggplot2::fortify", "mic")
|
||||
s3_register("ggplot2::fortify", "disk")
|
||||
# Support vctrs package for use in e.g. dplyr verbs
|
||||
s3_register("vctrs::vec_ptype2", "ab.character")
|
||||
s3_register("vctrs::vec_ptype2", "character.ab")
|
||||
s3_register("vctrs::vec_cast", "character.ab")
|
||||
s3_register("vctrs::vec_ptype2", "mo.character")
|
||||
s3_register("vctrs::vec_ptype2", "character.mo")
|
||||
s3_register("vctrs::vec_cast", "character.mo")
|
||||
s3_register("vctrs::vec_ptype2", "ab_selector.character")
|
||||
s3_register("vctrs::vec_ptype2", "character.ab_selector")
|
||||
s3_register("vctrs::vec_cast", "character.ab_selector")
|
||||
s3_register("vctrs::vec_ptype2", "ab_selector_any_all.logical")
|
||||
s3_register("vctrs::vec_ptype2", "logical.ab_selector_any_all")
|
||||
s3_register("vctrs::vec_cast", "logical.ab_selector_any_all")
|
||||
s3_register("vctrs::vec_ptype2", "disk.integer")
|
||||
s3_register("vctrs::vec_ptype2", "integer.disk")
|
||||
s3_register("vctrs::vec_cast", "integer.disk")
|
||||
|
||||
# if mo source exists, fire it up (see mo_source())
|
||||
try({
|
||||
if (file.exists(getOption("AMR_mo_source", "~/mo_source.rds"))) {
|
||||
invisible(get_mo_source())
|
||||
}
|
||||
}, silent = TRUE)
|
||||
|
||||
|
||||
# reference data - they have additional columns compared to `antibiotics` and `microorganisms` to improve speed
|
||||
# they cannott be part of R/sysdata.rda since CRAN thinks it would make the package too large (+3 MB)
|
||||
assign(x = "AB_lookup", value = create_AB_lookup(), envir = asNamespace("AMR"))
|
||||
assign(x = "MO_lookup", value = create_MO_lookup(), envir = asNamespace("AMR"))
|
||||
assign(x = "MO.old_lookup", value = create_MO.old_lookup(), envir = asNamespace("AMR"))
|
||||
# for mo_is_intrinsic_resistant() - saves a lot of time when executed on this vector
|
||||
assign(x = "INTRINSIC_R", value = create_intr_resistance(), envir = asNamespace("AMR"))
|
||||
}
|
||||
|
||||
# Helper functions --------------------------------------------------------
|
||||
|
||||
create_AB_lookup <- function() {
|
||||
cbind(AMR::antibiotics, AB_LOOKUP)
|
||||
}
|
||||
|
||||
create_MO_lookup <- function() {
|
||||
MO_lookup <- AMR::microorganisms
|
||||
|
||||
MO_lookup$kingdom_index <- NA_real_
|
||||
MO_lookup[which(MO_lookup$kingdom == "Bacteria" | MO_lookup$mo == "UNKNOWN"), "kingdom_index"] <- 1
|
||||
MO_lookup[which(MO_lookup$kingdom == "Fungi"), "kingdom_index"] <- 2
|
||||
MO_lookup[which(MO_lookup$kingdom == "Protozoa"), "kingdom_index"] <- 3
|
||||
MO_lookup[which(MO_lookup$kingdom == "Archaea"), "kingdom_index"] <- 4
|
||||
# all the rest
|
||||
MO_lookup[which(is.na(MO_lookup$kingdom_index)), "kingdom_index"] <- 5
|
||||
|
||||
# use this paste instead of `fullname` to work with Viridans Group Streptococci, etc.
|
||||
if (length(MO_FULLNAME_LOWER) == nrow(MO_lookup)) {
|
||||
MO_lookup$fullname_lower <- MO_FULLNAME_LOWER
|
||||
} else {
|
||||
MO_lookup$fullname_lower <- ""
|
||||
warning("MO table updated - Run: source(\"data-raw/_internals.R\")", call. = FALSE)
|
||||
}
|
||||
|
||||
# add a column with only "e coli" like combinations
|
||||
MO_lookup$g_species <- gsub("^([a-z])[a-z]+ ([a-z]+) ?.*", "\\1 \\2", MO_lookup$fullname_lower, perl = TRUE)
|
||||
|
||||
# so arrange data on prevalence first, then kingdom, then full name
|
||||
MO_lookup[order(MO_lookup$prevalence, MO_lookup$kingdom_index, MO_lookup$fullname_lower), ]
|
||||
}
|
||||
|
||||
create_MO.old_lookup <- function() {
|
||||
MO.old_lookup <- AMR::microorganisms.old
|
||||
MO.old_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", tolower(trimws(MO.old_lookup$fullname))))
|
||||
|
||||
# add a column with only "e coli"-like combinations
|
||||
MO.old_lookup$g_species <- trimws(gsub("^([a-z])[a-z]+ ([a-z]+) ?.*", "\\1 \\2", MO.old_lookup$fullname_lower))
|
||||
|
||||
# so arrange data on prevalence first, then full name
|
||||
MO.old_lookup[order(MO.old_lookup$prevalence, MO.old_lookup$fullname_lower), ]
|
||||
}
|
||||
|
||||
create_intr_resistance <- function() {
|
||||
# for mo_is_intrinsic_resistant() - saves a lot of time when executed on this vector
|
||||
paste(AMR::intrinsic_resistant$mo, AMR::intrinsic_resistant$ab)
|
||||
}
|
||||
@@ -1,54 +1,226 @@
|
||||
% AMR (for R)
|
||||
|
||||
# `AMR` (for R)
|
||||
The `AMR` package for R is a powerful tool for antimicrobial resistance (AMR) analysis. It provides extensive features for handling microbial and antimicrobial data. However, for those who work primarily in Python, we now have a more intuitive option available: the [`AMR` Python package](https://pypi.org/project/AMR/).
|
||||
|
||||
|
||||
[](https://www.codefactor.io/repository/github/msberends/amr)
|
||||
[](https://app.codecov.io/gh/msberends/AMR?branch=main)
|
||||
This Python package is a wrapper around the `AMR` R package. It uses the `rpy2` package internally. Despite the need to have R installed, Python users can now easily work with AMR data directly through Python code.
|
||||
|
||||
<img src="https://msberends.github.io/AMR/AMR_intro.svg" align="center" height="300px" />
|
||||
# Prerequisites
|
||||
|
||||
`AMR` is a free, open-source and independent R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. It is currently being used in over 175 countries.
|
||||
|
||||
After installing this package, R knows ~71,000 distinct microbial species and all ~570 antibiotic, antimycotic, and antiviral drugs by name and code (including ATC, WHONET/EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. Antimicrobial names and group names are available in Danish, Dutch, English, French, German, Italian, Portuguese and Spanish.
|
||||
This package was only tested with a [virtual environment (venv)](https://docs.python.org/3/library/venv.html). You can set up such an environment by running:
|
||||
|
||||
This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen. This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation.
|
||||
```python
|
||||
# linux and macOS:
|
||||
python -m venv /path/to/new/virtual/environment
|
||||
|
||||
This is the development source of the `AMR` package for R. Not a developer? Then please visit our website [https://msberends.github.io/AMR/](https://msberends.github.io/AMR/) to read more about this package.
|
||||
|
||||
*NOTE: this source code is on GitHub (https://github.com/msberends/AMR), but also automatically mirrored to our university's Gitea server (https://git.web.rug.nl/P281424/AMR) and to GitLab (https://gitlab.com/msberends/AMR).*
|
||||
|
||||
### How to get this package
|
||||
Please see [our website](https://msberends.github.io/AMR/#get-this-package).
|
||||
|
||||
You can install or update the `AMR` package from CRAN using:
|
||||
|
||||
```r
|
||||
install.packages("AMR")
|
||||
# Windows:
|
||||
python -m venv C:\path\to\new\virtual\environment
|
||||
```
|
||||
|
||||
It will be downloaded and installed automatically. For RStudio, click on the menu *Tools* > *Install Packages...* and then type in "AMR" and press <kbd>Install</kbd>.
|
||||
Then you can [activate the environment](https://docs.python.org/3/library/venv.html#how-venvs-work), after which the venv is ready to work with.
|
||||
|
||||
### Copyright
|
||||
# Install AMR
|
||||
|
||||
This R package is licensed under the [GNU General Public License (GPL) v2.0](https://github.com/msberends/AMR/blob/main/LICENSE). In a nutshell, this means that this package:
|
||||
1. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
|
||||
|
||||
- May be used for commercial purposes
|
||||
```bash
|
||||
pip install AMR
|
||||
```
|
||||
|
||||
- May be used for private purposes
|
||||
2. Make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
|
||||
|
||||
- May **not** be used for patent purposes
|
||||
For Linux:
|
||||
|
||||
- May be modified, although:
|
||||
```bash
|
||||
# Ubuntu / Debian
|
||||
sudo apt install r-base
|
||||
# Fedora:
|
||||
sudo dnf install R
|
||||
# CentOS/RHEL
|
||||
sudo yum install R
|
||||
```
|
||||
|
||||
For macOS (using [Homebrew](https://brew.sh)):
|
||||
|
||||
```bash
|
||||
brew install r
|
||||
```
|
||||
|
||||
For Windows, visit the [CRAN download page](https://cran.r-project.org) to download and install R.
|
||||
|
||||
- Modifications **must** be released under the same license when distributing the package
|
||||
- Changes made to the code **must** be documented
|
||||
# Examples of Usage
|
||||
|
||||
- May be distributed, although:
|
||||
## Cleaning Taxonomy
|
||||
|
||||
- Source code **must** be made available when the package is distributed
|
||||
- A copy of the license and copyright notice **must** be included with the package.
|
||||
Here’s an example that demonstrates how to clean microorganism and drug names using the `AMR` Python package:
|
||||
|
||||
- Comes with a LIMITATION of liability
|
||||
```python
|
||||
import pandas as pd
|
||||
import AMR
|
||||
|
||||
- Comes with NO warranty
|
||||
# Sample data
|
||||
data = {
|
||||
"MOs": ['E. coli', 'ESCCOL', 'esco', 'Esche coli'],
|
||||
"Drug": ['Cipro', 'CIP', 'J01MA02', 'Ciproxin']
|
||||
}
|
||||
df = pd.DataFrame(data)
|
||||
|
||||
# Use AMR functions to clean microorganism and drug names
|
||||
df['MO_clean'] = AMR.mo_name(df['MOs'])
|
||||
df['Drug_clean'] = AMR.ab_name(df['Drug'])
|
||||
|
||||
# Display the results
|
||||
print(df)
|
||||
```
|
||||
|
||||
| MOs | Drug | MO_clean | Drug_clean |
|
||||
|-------------|-----------|--------------------|---------------|
|
||||
| E. coli | Cipro | Escherichia coli | Ciprofloxacin |
|
||||
| ESCCOL | CIP | Escherichia coli | Ciprofloxacin |
|
||||
| esco | J01MA02 | Escherichia coli | Ciprofloxacin |
|
||||
| Esche coli | Ciproxin | Escherichia coli | Ciprofloxacin |
|
||||
|
||||
### Explanation
|
||||
|
||||
* **mo_name:** This function standardises microorganism names. Here, different variations of *Escherichia coli* (such as "E. coli", "ESCCOL", "esco", and "Esche coli") are all converted into the correct, standardised form, "Escherichia coli".
|
||||
|
||||
* **ab_name**: Similarly, this function standardises antimicrobial names. The different representations of ciprofloxacin (e.g., "Cipro", "CIP", "J01MA02", and "Ciproxin") are all converted to the standard name, "Ciprofloxacin".
|
||||
|
||||
## Calculating AMR
|
||||
|
||||
```python
|
||||
import AMR
|
||||
import pandas as pd
|
||||
|
||||
df = AMR.example_isolates
|
||||
result = AMR.resistance(df["AMX"])
|
||||
print(result)
|
||||
```
|
||||
|
||||
```
|
||||
[0.59555556]
|
||||
```
|
||||
|
||||
## Generating Antibiograms
|
||||
|
||||
One of the core functions of the `AMR` package is generating an antibiogram, a table that summarises the antimicrobial susceptibility of bacterial isolates. Here’s how you can generate an antibiogram from Python:
|
||||
|
||||
```python
|
||||
result2a = AMR.antibiogram(df[["mo", "AMX", "CIP", "TZP"]])
|
||||
print(result2a)
|
||||
```
|
||||
|
||||
| Pathogen | Amoxicillin | Ciprofloxacin | Piperacillin/tazobactam |
|
||||
|-----------------|-----------------|-----------------|--------------------------|
|
||||
| CoNS | 7% (10/142) | 73% (183/252) | 30% (10/33) |
|
||||
| E. coli | 50% (196/392) | 88% (399/456) | 94% (393/416) |
|
||||
| K. pneumoniae | 0% (0/58) | 96% (53/55) | 89% (47/53) |
|
||||
| P. aeruginosa | 0% (0/30) | 100% (30/30) | None |
|
||||
| P. mirabilis | None | 94% (34/36) | None |
|
||||
| S. aureus | 6% (8/131) | 90% (171/191) | None |
|
||||
| S. epidermidis | 1% (1/91) | 64% (87/136) | None |
|
||||
| S. hominis | None | 80% (56/70) | None |
|
||||
| S. pneumoniae | 100% (112/112) | None | 100% (112/112) |
|
||||
|
||||
|
||||
```python
|
||||
result2b = AMR.antibiogram(df[["mo", "AMX", "CIP", "TZP"]], mo_transform = "gramstain")
|
||||
print(result2b)
|
||||
```
|
||||
|
||||
| Pathogen | Amoxicillin | Ciprofloxacin | Piperacillin/tazobactam |
|
||||
|----------------|-----------------|------------------|--------------------------|
|
||||
| Gram-negative | 36% (226/631) | 91% (621/684) | 88% (565/641) |
|
||||
| Gram-positive | 43% (305/703) | 77% (560/724) | 86% (296/345) |
|
||||
|
||||
|
||||
In this example, we generate an antibiogram by selecting various antibiotics.
|
||||
|
||||
## Taxonomic Data Sets Now in Python!
|
||||
|
||||
As a Python user, you might like that the most important data sets of the `AMR` R package, `microorganisms`, `antimicrobials`, `clinical_breakpoints`, and `example_isolates`, are now available as regular Python data frames:
|
||||
|
||||
```python
|
||||
AMR.microorganisms
|
||||
```
|
||||
|
||||
| mo | fullname | status | kingdom | gbif | gbif_parent | gbif_renamed_to | prevalence |
|
||||
|--------------|------------------------------------|----------|----------|-----------|-------------|-----------------|------------|
|
||||
| B_GRAMN | (unknown Gram-negatives) | unknown | Bacteria | None | None | None | 2.0 |
|
||||
| B_GRAMP | (unknown Gram-positives) | unknown | Bacteria | None | None | None | 2.0 |
|
||||
| B_ANAER-NEG | (unknown anaerobic Gram-negatives) | unknown | Bacteria | None | None | None | 2.0 |
|
||||
| B_ANAER-POS | (unknown anaerobic Gram-positives) | unknown | Bacteria | None | None | None | 2.0 |
|
||||
| B_ANAER | (unknown anaerobic bacteria) | unknown | Bacteria | None | None | None | 2.0 |
|
||||
| ... | ... | ... | ... | ... | ... | ... | ... |
|
||||
| B_ZYMMN_POMC | Zymomonas pomaceae | accepted | Bacteria | 10744418 | 3221412 | None | 2.0 |
|
||||
| B_ZYMPH | Zymophilus | synonym | Bacteria | None | 9475166 | None | 2.0 |
|
||||
| B_ZYMPH_PCVR | Zymophilus paucivorans | synonym | Bacteria | None | None | None | 2.0 |
|
||||
| B_ZYMPH_RFFN | Zymophilus raffinosivorans | synonym | Bacteria | None | None | None | 2.0 |
|
||||
| F_ZYZYG | Zyzygomyces | unknown | Fungi | None | 7581 | None | 2.0 |
|
||||
|
||||
```python
|
||||
AMR.antimicrobials
|
||||
```
|
||||
|
||||
| ab | cid | name | group | oral_ddd | oral_units | iv_ddd | iv_units |
|
||||
|-----|-------------|----------------------|----------------------------|----------|------------|--------|----------|
|
||||
| AMA | 4649.0 | 4-aminosalicylic acid| Antimycobacterials | 12.00 | g | NaN | None |
|
||||
| ACM | 6450012.0 | Acetylmidecamycin | Macrolides/lincosamides | NaN | None | NaN | None |
|
||||
| ASP | 49787020.0 | Acetylspiramycin | Macrolides/lincosamides | NaN | None | NaN | None |
|
||||
| ALS | 8954.0 | Aldesulfone sodium | Other antibacterials | 0.33 | g | NaN | None |
|
||||
| AMK | 37768.0 | Amikacin | Aminoglycosides | NaN | None | 1.0 | g |
|
||||
| ... | ... | ... | ... | ... | ... | ... | ... |
|
||||
| VIR | 11979535.0 | Virginiamycine | Other antibacterials | NaN | None | NaN | None |
|
||||
| VOR | 71616.0 | Voriconazole | Antifungals/antimycotics | 0.40 | g | 0.4 | g |
|
||||
| XBR | 72144.0 | Xibornol | Other antibacterials | NaN | None | NaN | None |
|
||||
| ZID | 77846445.0 | Zidebactam | Other antibacterials | NaN | None | NaN | None |
|
||||
| ZFD | NaN | Zoliflodacin | None | NaN | None | NaN | None |
|
||||
|
||||
|
||||
# Installation Channels
|
||||
|
||||
## Stable Release (CRAN)
|
||||
|
||||
The default `AMR` Python package uses the latest stable version of the `AMR` R package, published on CRAN. After running `pip install AMR`, import it as usual:
|
||||
|
||||
```python
|
||||
import AMR
|
||||
|
||||
AMR.example_isolates
|
||||
```
|
||||
|
||||
## Development Version (GitHub)
|
||||
|
||||
To use the latest development version of the `AMR` R package (sourced directly from GitHub), import the `beta` sub-package and alias it as `AMR`:
|
||||
|
||||
```python
|
||||
import AMR.beta as AMR
|
||||
|
||||
AMR.example_isolates
|
||||
```
|
||||
|
||||
Aliasing with `as AMR` keeps all downstream code identical to the stable import. Switching between the stable release and the development version requires changing only the import line — nothing else in your script needs to change.
|
||||
|
||||
# SIR Classification with `as_sir()`
|
||||
|
||||
## Using `enforce_method`
|
||||
|
||||
The `as_sir()` function in R uses S3 method dispatch to select the correct calculation method based on the input class: `<mic>` for MIC values and `<disk>` for disk diffusion values. Because Python objects do not carry R class attributes through the `rpy2` bridge, this automatic dispatch may not resolve correctly.
|
||||
|
||||
To explicitly specify the input type, use the `enforce_method` argument:
|
||||
|
||||
```python
|
||||
# Treat the column as MIC values — maps to R's as.sir.mic()
|
||||
AMR.as_sir(df["MIC_col"], mo="E. coli", ab="AMX", guideline="EUCAST", enforce_method="mic")
|
||||
|
||||
# Treat the column as disk diffusion values — maps to R's as.sir.disk()
|
||||
AMR.as_sir(df["disk_col"], mo="E. coli", ab="AMX", guideline="EUCAST", enforce_method="disk")
|
||||
```
|
||||
|
||||
Without `enforce_method`, R falls back to class-based dispatch on the raw Python input, which may fail or return unexpected results. Always supply `enforce_method` when calling `as_sir()` from Python.
|
||||
|
||||
# Conclusion
|
||||
|
||||
With the `AMR` Python package, Python users can now effortlessly call R functions from the `AMR` R package. This eliminates the need for complex `rpy2` configurations and provides a clean, easy-to-use interface for antimicrobial resistance analysis. The examples provided above demonstrate how this can be applied to typical workflows, such as standardising microorganism and antimicrobial names or calculating resistance.
|
||||
|
||||
By just running `import AMR`, users can seamlessly integrate the robust features of the R `AMR` package into Python workflows.
|
||||
|
||||
Whether you're cleaning data or analysing resistance patterns, the `AMR` Python package makes it easy to work with AMR data in Python.
|
||||
|
||||
-226
@@ -1,226 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
title: "AMR (for R)"
|
||||
url: "https://msberends.github.io/AMR/"
|
||||
|
||||
template:
|
||||
bootstrap: 5
|
||||
bootswatch: "flatly"
|
||||
assets: "pkgdown/logos" # use logos in this folder
|
||||
bslib:
|
||||
code_font: {google: "Fira Code"}
|
||||
# body-text-align: "justify"
|
||||
line-height-base: 1.75
|
||||
# the green "success" colour of this bootstrap theme should be the same as the green in our logo
|
||||
success: "#128f76"
|
||||
link-color: "#128f76"
|
||||
navbar-padding-y: "0.5rem"
|
||||
opengraph:
|
||||
twitter:
|
||||
creator: "@msberends"
|
||||
site: "@univgroningen"
|
||||
card: summary_large_image
|
||||
|
||||
news:
|
||||
one_page: true
|
||||
cran_dates: true
|
||||
|
||||
footer:
|
||||
structure:
|
||||
left: [devtext]
|
||||
right: [logo]
|
||||
components:
|
||||
devtext: '<code>AMR</code> (for R). Developed at the <a target="_blank" href="https://www.rug.nl">University of Groningen</a> in collaboration with non-profit organisations<br><a target="_blank" href="https://www.certe.nl">Certe Medical Diagnostics and Advice Foundation</a> and <a target="_blank" href="https://www.umcg.nl">University Medical Center Groningen</a>.'
|
||||
logo: '<a target="_blank" href="https://www.rug.nl"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/logos/logo_rug.png" style="max-width: 200px;"></a>'
|
||||
|
||||
home:
|
||||
sidebar:
|
||||
structure: [toc, links, authors, citation]
|
||||
|
||||
navbar:
|
||||
title: "AMR (for R)"
|
||||
left:
|
||||
- text: "Home"
|
||||
icon: "fa-home"
|
||||
href: "index.html"
|
||||
- text: "How to"
|
||||
icon: "fa-question-circle"
|
||||
menu:
|
||||
- text: "Conduct AMR analysis"
|
||||
icon: "fa-directions"
|
||||
href: "articles/AMR.html"
|
||||
- text: "Predict antimicrobial resistance"
|
||||
icon: "fa-dice"
|
||||
href: "articles/resistance_predict.html"
|
||||
- text: "Data sets for download / own use"
|
||||
icon: "fa-database"
|
||||
href: "articles/datasets.html"
|
||||
- text: "Conduct principal component analysis for AMR"
|
||||
icon: "fa-compress"
|
||||
href: "articles/PCA.html"
|
||||
- text: "Determine multi-drug resistance (MDR)"
|
||||
icon: "fa-skull-crossbones"
|
||||
href: "articles/MDR.html"
|
||||
- text: "Work with WHONET data"
|
||||
icon: "fa-globe-americas"
|
||||
href: "articles/WHONET.html"
|
||||
- text: "Import data from SPSS/SAS/Stata"
|
||||
icon: "fa-file-upload"
|
||||
href: "articles/SPSS.html"
|
||||
- text: "Apply EUCAST rules"
|
||||
icon: "fa-exchange-alt"
|
||||
href: "articles/EUCAST.html"
|
||||
- text: "Get properties of a microorganism"
|
||||
icon: "fa-bug"
|
||||
href: "reference/mo_property.html" # reference instead of an article
|
||||
- text: "Get properties of an antibiotic"
|
||||
icon: "fa-capsules"
|
||||
href: "reference/ab_property.html" # reference instead of an article
|
||||
# - text: "Other: benchmarks"
|
||||
# icon: "fa-shipping-fast"
|
||||
# href: "articles/benchmarks.html"
|
||||
- text: "Manual"
|
||||
icon: "fa-book-open"
|
||||
href: "reference/index.html"
|
||||
- text: "Authors"
|
||||
icon: "fa-users"
|
||||
href: "authors.html"
|
||||
- text: "Changelog"
|
||||
icon: "far fa-newspaper"
|
||||
href: "news/index.html"
|
||||
right:
|
||||
- text: "Source Code"
|
||||
icon: "fab fa-github"
|
||||
href: "https://github.com/msberends/AMR"
|
||||
# - text: "Survey"
|
||||
# icon: "fa-clipboard-list"
|
||||
# href: "survey.html"
|
||||
|
||||
reference:
|
||||
- title: "Preparing data: microorganisms"
|
||||
desc: >
|
||||
These functions are meant to get taxonomically valid properties of microorganisms from any input.
|
||||
Use `mo_source()` to teach this package how to translate your own codes to valid microorganism codes.
|
||||
contents:
|
||||
- "`as.mo`"
|
||||
- "`mo_property`"
|
||||
- "`mo_source`"
|
||||
|
||||
- title: "Preparing data: antibiotics"
|
||||
desc: >
|
||||
Use these functions to get valid properties of antibiotics from any input or to clean your input.
|
||||
You can even retrieve drug names and doses from clinical text records, using `ab_from_text()`.
|
||||
contents:
|
||||
- "`as.ab`"
|
||||
- "`ab_property`"
|
||||
- "`ab_from_text`"
|
||||
- "`atc_online_property`"
|
||||
|
||||
- title: "Preparing data: antimicrobial resistance"
|
||||
desc: >
|
||||
With `as.mic()` and `as.disk()` you can transform your raw input to valid MIC or disk diffusion values.
|
||||
Use `as.rsi()` for cleaning raw data to let it only contain "R", "I" and "S", or to interpret MIC or disk diffusion values as R/SI based on the lastest EUCAST and CLSI guidelines.
|
||||
Afterwards, you can extend antibiotic interpretations by applying [EUCAST rules](https://www.eucast.org/expert_rules_and_intrinsic_resistance/) with `eucast_rules()`.
|
||||
contents:
|
||||
- "`as.rsi`"
|
||||
- "`as.mic`"
|
||||
- "`as.disk`"
|
||||
- "`eucast_rules`"
|
||||
- "`custom_eucast_rules`"
|
||||
|
||||
- title: "Analysing data: antimicrobial resistance"
|
||||
desc: >
|
||||
Use these function for the analysis part. You can use `susceptibility()` or `resistance()` on any antibiotic column.
|
||||
Be sure to first select the isolates that are appropiate for analysis, by using `first_isolate()` or `is_new_episode()`.
|
||||
You can also filter your data on certain resistance in certain antibiotic classes (`carbapenems()`, `aminoglycosides()`), or determine multi-drug resistant microorganisms (MDRO, `mdro()`).
|
||||
contents:
|
||||
- "`proportion`"
|
||||
- "`count`"
|
||||
- "`is_new_episode`"
|
||||
- "`first_isolate`"
|
||||
- "`key_antimicrobials`"
|
||||
- "`mdro`"
|
||||
- "`count`"
|
||||
- "`plot`"
|
||||
- "`ggplot_rsi`"
|
||||
- "`bug_drug_combinations`"
|
||||
- "`antibiotic_class_selectors`"
|
||||
- "`resistance_predict`"
|
||||
- "`guess_ab_col`"
|
||||
|
||||
- title: "Background information on included data"
|
||||
desc: >
|
||||
Some pages about our package and its external sources. Be sure to read our [How To's](./../articles/index.html)
|
||||
for more information about how to work with functions in this package.
|
||||
contents:
|
||||
- "`AMR`"
|
||||
- "`example_isolates`"
|
||||
- "`microorganisms`"
|
||||
- "`microorganisms.codes`"
|
||||
- "`microorganisms.old`"
|
||||
- "`antibiotics`"
|
||||
- "`intrinsic_resistant`"
|
||||
- "`dosage`"
|
||||
- "`catalogue_of_life`"
|
||||
- "`catalogue_of_life_version`"
|
||||
- "`WHOCC`"
|
||||
- "`example_isolates_unclean`"
|
||||
- "`rsi_translation`"
|
||||
- "`WHONET`"
|
||||
|
||||
- title: "Other: miscellaneous functions"
|
||||
desc: >
|
||||
These functions are mostly for internal use, but some of
|
||||
them may also be suitable for your analysis. Especially the
|
||||
'like' function can be useful: `if (x %like% y) {...}`.
|
||||
contents:
|
||||
- "`age_groups`"
|
||||
- "`age`"
|
||||
- "`availability`"
|
||||
- "`get_AMR_locale`"
|
||||
- "`ggplot_pca`"
|
||||
- "`italicise_taxonomy`"
|
||||
- "`join`"
|
||||
- "`like`"
|
||||
- "`mo_matching_score`"
|
||||
- "`pca`"
|
||||
- "`random`"
|
||||
|
||||
- title: "Other: statistical tests"
|
||||
desc: >
|
||||
Some statistical tests or methods are not part of base R and were added to this package for convenience.
|
||||
contents:
|
||||
- "`g.test`"
|
||||
- "`kurtosis`"
|
||||
- "`skewness`"
|
||||
|
||||
- title: "Other: deprecated functions"
|
||||
desc: >
|
||||
These functions are deprecated, meaning that they will still
|
||||
work but show a warning with every use and will be removed
|
||||
in a future version.
|
||||
contents:
|
||||
- "`AMR-deprecated`"
|
||||
-39
@@ -1,39 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
codecov:
|
||||
require_ci_to_pass: no # allow fail
|
||||
branch: main
|
||||
|
||||
comment: no
|
||||
|
||||
coverage:
|
||||
precision: 1
|
||||
round: up
|
||||
range: "0...100"
|
||||
status:
|
||||
project: no
|
||||
patch: no
|
||||
changes: no
|
||||
@@ -1,2 +0,0 @@
|
||||
Extra release for fixing image options, as requested by CRAN team on 17 February 2022 (Kurt Hornik).
|
||||
|
||||
File diff suppressed because one or more lines are too long
Binary file not shown.
Binary file not shown.
Binary file not shown.
-92370
File diff suppressed because one or more lines are too long
File diff suppressed because it is too large
Load Diff
@@ -1,83 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
# some old R instances have trouble installing tinytest, so we ship it too
|
||||
install.packages("data-raw/tinytest_1.3.1.tar.gz", dependencies = c("Depends", "Imports", "LinkingTo"))
|
||||
install.packages(getwd(), repos = NULL, type = "source")
|
||||
# install.packages("data-raw/AMR_latest.tar.gz", dependencies = FALSE)
|
||||
|
||||
pkg_suggests <- gsub("[^a-zA-Z0-9]+", "",
|
||||
unlist(strsplit(unlist(packageDescription("AMR",
|
||||
fields = c("Suggests", "Enhances", "LinkingTo"))),
|
||||
split = ", ?")))
|
||||
pkg_suggests <- unname(pkg_suggests[!is.na(pkg_suggests)])
|
||||
cat("################################################\n")
|
||||
cat("Packages listed in Suggests/Enhances:", paste(pkg_suggests, collapse = ", "), "\n")
|
||||
cat("################################################\n")
|
||||
|
||||
if (.Platform$OS.type != "unix") {
|
||||
# no compiling on Windows here
|
||||
options(install.packages.compile.from.source = FALSE)
|
||||
}
|
||||
|
||||
to_install <- pkg_suggests[!pkg_suggests %in% rownames(utils::installed.packages())]
|
||||
if (length(to_install) == 0) {
|
||||
message("\nNothing to install\n")
|
||||
}
|
||||
for (i in seq_len(length(to_install))) {
|
||||
cat("Installing package", to_install[i], "\n")
|
||||
tryCatch(install.packages(to_install[i],
|
||||
type = "source",
|
||||
repos = "https://cran.rstudio.com/",
|
||||
dependencies = c("Depends", "Imports", "LinkingTo"),
|
||||
quiet = FALSE),
|
||||
# message = function(m) invisible(),
|
||||
warning = function(w) message(w$message),
|
||||
error = function(e) message(e$message))
|
||||
if (.Platform$OS.type != "unix" && !to_install[i] %in% rownames(utils::installed.packages())) {
|
||||
tryCatch(install.packages(to_install[i],
|
||||
type = "binary",
|
||||
repos = "https://cran.rstudio.com/",
|
||||
dependencies = c("Depends", "Imports", "LinkingTo"),
|
||||
quiet = FALSE),
|
||||
# message = function(m) invisible(),
|
||||
warning = function(w) message(w$message),
|
||||
error = function(e) message(e$message))
|
||||
}
|
||||
}
|
||||
|
||||
to_update <- as.data.frame(utils::old.packages(repos = "https://cran.rstudio.com/"), stringsAsFactors = FALSE)
|
||||
to_update <- to_update[which(to_update$Package %in% pkg_suggests), "Package", drop = TRUE]
|
||||
if (length(to_update) == 0) {
|
||||
message("\nNothing to update\n")
|
||||
}
|
||||
for (i in seq_len(length(to_update))) {
|
||||
cat("Updating package '", to_update[i], "' v", as.character(packageVersion(to_update[i])), "\n", sep = "")
|
||||
tryCatch(update.packages(to_update[i], repos = "https://cran.rstudio.com/", ask = FALSE),
|
||||
# message = function(m) invisible(),
|
||||
warning = function(w) message(w$message),
|
||||
error = function(e) message(e$message))
|
||||
cat("Updated to '", to_update[i], "' v", as.character(packageVersion(to_update[i])), "\n", sep = "")
|
||||
}
|
||||
@@ -1,342 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
# Run this file to update the package using:
|
||||
# source("data-raw/_internals.R")
|
||||
|
||||
library(dplyr, warn.conflicts = FALSE)
|
||||
devtools::load_all(quiet = TRUE)
|
||||
|
||||
set_AMR_locale("en")
|
||||
|
||||
old_globalenv <- ls(envir = globalenv())
|
||||
|
||||
# Save internal data to R/sysdata.rda -------------------------------------
|
||||
|
||||
# See 'data-raw/eucast_rules.tsv' for the EUCAST reference file
|
||||
EUCAST_RULES_DF <- utils::read.delim(file = "data-raw/eucast_rules.tsv",
|
||||
skip = 10,
|
||||
sep = "\t",
|
||||
stringsAsFactors = FALSE,
|
||||
header = TRUE,
|
||||
strip.white = TRUE,
|
||||
na = c(NA, "", NULL)) %>%
|
||||
# take the order of the reference.rule_group column in the original data file
|
||||
mutate(reference.rule_group = factor(reference.rule_group,
|
||||
levels = unique(reference.rule_group),
|
||||
ordered = TRUE),
|
||||
sorting_rule = ifelse(grepl("^Table", reference.rule, ignore.case = TRUE), 1, 2)) %>%
|
||||
arrange(reference.rule_group,
|
||||
reference.version,
|
||||
sorting_rule,
|
||||
reference.rule) %>%
|
||||
mutate(reference.rule_group = as.character(reference.rule_group)) %>%
|
||||
select(-sorting_rule)
|
||||
|
||||
# vectors of CoNS and CoPS, improves speed in as.mo()
|
||||
create_species_cons_cops <- function(type = c("CoNS", "CoPS")) {
|
||||
# Determination of which staphylococcal species are CoNS/CoPS according to:
|
||||
# - Becker et al. 2014, PMID 25278577
|
||||
# - Becker et al. 2019, PMID 30872103
|
||||
# - Becker et al. 2020, PMID 32056452
|
||||
# this function returns class <mo>
|
||||
MO_staph <- AMR::microorganisms
|
||||
MO_staph <- MO_staph[which(MO_staph$genus == "Staphylococcus"), , drop = FALSE]
|
||||
if (type == "CoNS") {
|
||||
MO_staph[which(MO_staph$species %in% c("coagulase-negative", "argensis", "arlettae",
|
||||
"auricularis", "borealis", "caeli", "capitis", "caprae",
|
||||
"carnosus", "casei", "chromogenes", "cohnii", "condimenti",
|
||||
"croceilyticus",
|
||||
"debuckii", "devriesei", "edaphicus", "epidermidis",
|
||||
"equorum", "felis", "fleurettii", "gallinarum",
|
||||
"haemolyticus", "hominis", "jettensis", "kloosii",
|
||||
"lentus", "lugdunensis", "massiliensis", "microti",
|
||||
"muscae", "nepalensis", "pasteuri", "petrasii",
|
||||
"pettenkoferi", "piscifermentans", "pragensis", "pseudoxylosus",
|
||||
"pulvereri", "rostri", "saccharolyticus", "saprophyticus",
|
||||
"sciuri", "simulans", "stepanovicii", "succinus",
|
||||
"ureilyticus",
|
||||
"vitulinus", "vitulus", "warneri", "xylosus",
|
||||
"caledonicus", "canis",
|
||||
"durrellii", "lloydii")
|
||||
| (MO_staph$species == "schleiferi" & MO_staph$subspecies %in% c("schleiferi", ""))),
|
||||
"mo", drop = TRUE]
|
||||
} else if (type == "CoPS") {
|
||||
MO_staph[which(MO_staph$species %in% c("coagulase-positive", "coagulans",
|
||||
"agnetis", "argenteus",
|
||||
"cornubiensis",
|
||||
"delphini", "lutrae",
|
||||
"hyicus", "intermedius",
|
||||
"pseudintermedius", "pseudointermedius",
|
||||
"schweitzeri", "simiae",
|
||||
"roterodami")
|
||||
| (MO_staph$species == "schleiferi" & MO_staph$subspecies == "coagulans")),
|
||||
"mo", drop = TRUE]
|
||||
}
|
||||
}
|
||||
create_MO_fullname_lower <- function() {
|
||||
MO_lookup <- AMR::microorganisms
|
||||
# use this paste instead of `fullname` to work with Viridans Group Streptococci, etc.
|
||||
MO_lookup$fullname_lower <- tolower(trimws(paste(MO_lookup$genus,
|
||||
MO_lookup$species,
|
||||
MO_lookup$subspecies)))
|
||||
ind <- MO_lookup$genus == "" | grepl("^[(]unknown ", MO_lookup$fullname, perl = TRUE)
|
||||
MO_lookup[ind, "fullname_lower"] <- tolower(MO_lookup[ind, "fullname"])
|
||||
MO_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", MO_lookup$fullname_lower, perl = TRUE))
|
||||
MO_lookup$fullname_lower
|
||||
}
|
||||
MO_CONS <- create_species_cons_cops("CoNS")
|
||||
MO_COPS <- create_species_cons_cops("CoPS")
|
||||
MO_STREP_ABCG <- as.mo(MO_lookup[which(MO_lookup$genus == "Streptococcus"), "mo", drop = TRUE], Lancefield = TRUE) %in% c("B_STRPT_GRPA", "B_STRPT_GRPB", "B_STRPT_GRPC", "B_STRPT_GRPG")
|
||||
MO_FULLNAME_LOWER <- create_MO_fullname_lower()
|
||||
MO_PREVALENT_GENERA <- c("Absidia", "Acholeplasma", "Acremonium", "Actinotignum", "Aedes", "Alistipes", "Alloprevotella",
|
||||
"Alternaria", "Anaerosalibacter", "Ancylostoma", "Angiostrongylus", "Anisakis", "Anopheles",
|
||||
"Apophysomyces", "Arachnia", "Aspergillus", "Aureobasidium", "Bacteroides", "Basidiobolus",
|
||||
"Beauveria", "Bergeyella", "Blastocystis", "Blastomyces", "Borrelia", "Brachyspira", "Branhamella",
|
||||
"Butyricimonas", "Candida", "Capillaria", "Capnocytophaga", "Catabacter", "Cetobacterium", "Chaetomium",
|
||||
"Chlamydia", "Chlamydophila", "Chryseobacterium", "Chrysonilia", "Cladophialophora", "Cladosporium",
|
||||
"Conidiobolus", "Contracaecum", "Cordylobia", "Cryptococcus", "Curvularia", "Deinococcus", "Demodex",
|
||||
"Dermatobia", "Diphyllobothrium", "Dirofilaria", "Dysgonomonas", "Echinostoma", "Elizabethkingia",
|
||||
"Empedobacter", "Enterobius", "Exophiala", "Exserohilum", "Fasciola", "Flavobacterium", "Fonsecaea",
|
||||
"Fusarium", "Fusobacterium", "Giardia", "Haloarcula", "Halobacterium", "Halococcus", "Hendersonula",
|
||||
"Heterophyes", "Histoplasma", "Hymenolepis", "Hypomyces", "Hysterothylacium", "Lelliottia",
|
||||
"Leptosphaeria", "Leptotrichia", "Lucilia", "Lumbricus", "Malassezia", "Malbranchea", "Metagonimus",
|
||||
"Microsporum", "Mortierella", "Mucor", "Mycocentrospora", "Mycoplasma", "Myroides", "Necator",
|
||||
"Nectria", "Ochroconis", "Odoribacter", "Oesophagostomum", "Oidiodendron", "Opisthorchis",
|
||||
"Ornithobacterium", "Parabacteroides", "Pediculus", "Pedobacter", "Phlebotomus", "Phocaeicola",
|
||||
"Phocanema", "Phoma", "Piedraia", "Pithomyces", "Pityrosporum", "Porphyromonas", "Prevotella",
|
||||
"Pseudallescheria", "Pseudoterranova", "Pulex", "Rhizomucor", "Rhizopus", "Rhodotorula", "Riemerella",
|
||||
"Saccharomyces", "Sarcoptes", "Scolecobasidium", "Scopulariopsis", "Scytalidium", "Sphingobacterium",
|
||||
"Spirometra", "Spiroplasma", "Sporobolomyces", "Stachybotrys", "Streptobacillus", "Strongyloides",
|
||||
"Syngamus", "Taenia", "Tannerella", "Tenacibaculum", "Terrimonas", "Toxocara", "Treponema", "Trichinella",
|
||||
"Trichobilharzia", "Trichoderma", "Trichomonas", "Trichophyton", "Trichosporon", "Trichostrongylus",
|
||||
"Trichuris", "Tritirachium", "Trombicula", "Tunga", "Ureaplasma", "Victivallis", "Wautersiella",
|
||||
"Weeksella", "Wuchereria")
|
||||
|
||||
# antibiotic groups
|
||||
# (these will also be used for eucast_rules() and understanding data-raw/eucast_rules.tsv)
|
||||
globalenv_before_ab <- c(ls(envir = globalenv()), "globalenv_before_ab")
|
||||
AB_AMINOGLYCOSIDES <- antibiotics %>% filter(group %like% "aminoglycoside") %>% pull(ab)
|
||||
AB_AMINOPENICILLINS <- as.ab(c("AMP", "AMX"))
|
||||
AB_ANTIFUNGALS <- AB_lookup %>% filter(group %like% "antifungal") %>% pull(ab)
|
||||
AB_ANTIMYCOBACTERIALS <- AB_lookup %>% filter(group %like% "antimycobacterial") %>% pull(ab)
|
||||
AB_CARBAPENEMS <- antibiotics %>% filter(group %like% "carbapenem") %>% pull(ab)
|
||||
AB_CEPHALOSPORINS <- antibiotics %>% filter(group %like% "cephalosporin") %>% pull(ab)
|
||||
AB_CEPHALOSPORINS_1ST <- antibiotics %>% filter(group %like% "cephalosporin.*1") %>% pull(ab)
|
||||
AB_CEPHALOSPORINS_2ND <- antibiotics %>% filter(group %like% "cephalosporin.*2") %>% pull(ab)
|
||||
AB_CEPHALOSPORINS_3RD <- antibiotics %>% filter(group %like% "cephalosporin.*3") %>% pull(ab)
|
||||
AB_CEPHALOSPORINS_4TH <- antibiotics %>% filter(group %like% "cephalosporin.*4") %>% pull(ab)
|
||||
AB_CEPHALOSPORINS_5TH <- antibiotics %>% filter(group %like% "cephalosporin.*5") %>% pull(ab)
|
||||
AB_CEPHALOSPORINS_EXCEPT_CAZ <- AB_CEPHALOSPORINS[AB_CEPHALOSPORINS != "CAZ"]
|
||||
AB_FLUOROQUINOLONES <- antibiotics %>% filter(atc_group2 %like% "fluoroquinolone" | (group %like% "quinolone" & is.na(atc_group2))) %>% pull(ab)
|
||||
AB_GLYCOPEPTIDES <- antibiotics %>% filter(group %like% "glycopeptide") %>% pull(ab)
|
||||
AB_LIPOGLYCOPEPTIDES <- as.ab(c("DAL", "ORI", "TLV")) # dalba/orita/tela
|
||||
AB_GLYCOPEPTIDES_EXCEPT_LIPO <- AB_GLYCOPEPTIDES[!AB_GLYCOPEPTIDES %in% AB_LIPOGLYCOPEPTIDES]
|
||||
AB_LINCOSAMIDES <- antibiotics %>% filter(atc_group2 %like% "lincosamide" | (group %like% "lincosamide" & is.na(atc_group2))) %>% pull(ab)
|
||||
AB_MACROLIDES <- antibiotics %>% filter(atc_group2 %like% "macrolide" | (group %like% "macrolide" & is.na(atc_group2))) %>% pull(ab)
|
||||
AB_OXAZOLIDINONES <- antibiotics %>% filter(group %like% "oxazolidinone") %>% pull(ab)
|
||||
AB_PENICILLINS <- antibiotics %>% filter(group %like% "penicillin") %>% pull(ab)
|
||||
AB_POLYMYXINS <- antibiotics %>% filter(group %like% "polymyxin") %>% pull(ab)
|
||||
AB_QUINOLONES <- antibiotics %>% filter(group %like% "quinolone") %>% pull(ab)
|
||||
AB_STREPTOGRAMINS <- antibiotics %>% filter(atc_group2 %like% "streptogramin") %>% pull(ab)
|
||||
AB_TETRACYCLINES <- antibiotics %>% filter(group %like% "tetracycline") %>% pull(ab)
|
||||
AB_TETRACYCLINES_EXCEPT_TGC <- AB_TETRACYCLINES[AB_TETRACYCLINES != "TGC"]
|
||||
AB_TRIMETHOPRIMS <- antibiotics %>% filter(group %like% "trimethoprim") %>% pull(ab)
|
||||
AB_UREIDOPENICILLINS <- as.ab(c("PIP", "TZP", "AZL", "MEZ"))
|
||||
AB_BETALACTAMS <- c(AB_PENICILLINS, AB_CEPHALOSPORINS, AB_CARBAPENEMS)
|
||||
# this will be used for documentation:
|
||||
DEFINED_AB_GROUPS <- ls(envir = globalenv())
|
||||
DEFINED_AB_GROUPS <- DEFINED_AB_GROUPS[!DEFINED_AB_GROUPS %in% globalenv_before_ab]
|
||||
create_AB_lookup <- function() {
|
||||
AB_lookup <- AMR::antibiotics
|
||||
AB_lookup$generalised_name <- generalise_antibiotic_name(AB_lookup$name)
|
||||
AB_lookup$generalised_synonyms <- lapply(AB_lookup$synonyms, generalise_antibiotic_name)
|
||||
AB_lookup$generalised_abbreviations <- lapply(AB_lookup$abbreviations, generalise_antibiotic_name)
|
||||
AB_lookup$generalised_loinc <- lapply(AB_lookup$loinc, generalise_antibiotic_name)
|
||||
AB_lookup$generalised_all <- unname(lapply(as.list(as.data.frame(t(AB_lookup[,
|
||||
c("ab", "atc", "cid", "name",
|
||||
colnames(AB_lookup)[colnames(AB_lookup) %like% "generalised"]),
|
||||
drop = FALSE]),
|
||||
stringsAsFactors = FALSE)),
|
||||
function(x) {
|
||||
x <- generalise_antibiotic_name(unname(unlist(x)))
|
||||
x[x != ""]
|
||||
}))
|
||||
AB_lookup[, colnames(AB_lookup)[colnames(AB_lookup) %like% "^generalised"]]
|
||||
}
|
||||
AB_LOOKUP <- create_AB_lookup()
|
||||
|
||||
# Export to package as internal data ----
|
||||
usethis::use_data(EUCAST_RULES_DF,
|
||||
MO_CONS,
|
||||
MO_COPS,
|
||||
MO_STREP_ABCG,
|
||||
MO_FULLNAME_LOWER,
|
||||
MO_PREVALENT_GENERA,
|
||||
AB_LOOKUP,
|
||||
AB_AMINOGLYCOSIDES,
|
||||
AB_AMINOPENICILLINS,
|
||||
AB_ANTIFUNGALS,
|
||||
AB_ANTIMYCOBACTERIALS,
|
||||
AB_CARBAPENEMS,
|
||||
AB_CEPHALOSPORINS,
|
||||
AB_CEPHALOSPORINS_1ST,
|
||||
AB_CEPHALOSPORINS_2ND,
|
||||
AB_CEPHALOSPORINS_3RD,
|
||||
AB_CEPHALOSPORINS_4TH,
|
||||
AB_CEPHALOSPORINS_5TH,
|
||||
AB_CEPHALOSPORINS_EXCEPT_CAZ,
|
||||
AB_FLUOROQUINOLONES,
|
||||
AB_LIPOGLYCOPEPTIDES,
|
||||
AB_GLYCOPEPTIDES,
|
||||
AB_GLYCOPEPTIDES_EXCEPT_LIPO,
|
||||
AB_LINCOSAMIDES,
|
||||
AB_MACROLIDES,
|
||||
AB_OXAZOLIDINONES,
|
||||
AB_PENICILLINS,
|
||||
AB_POLYMYXINS,
|
||||
AB_QUINOLONES,
|
||||
AB_STREPTOGRAMINS,
|
||||
AB_TETRACYCLINES,
|
||||
AB_TETRACYCLINES_EXCEPT_TGC,
|
||||
AB_TRIMETHOPRIMS,
|
||||
AB_UREIDOPENICILLINS,
|
||||
AB_BETALACTAMS,
|
||||
DEFINED_AB_GROUPS,
|
||||
internal = TRUE,
|
||||
overwrite = TRUE,
|
||||
version = 2,
|
||||
compress = "xz")
|
||||
|
||||
# Export data sets to the repository in different formats -----------------
|
||||
|
||||
write_md5 <- function(object) {
|
||||
conn <- file(paste0("data-raw/", deparse(substitute(object)), ".md5"))
|
||||
writeLines(digest::digest(object, "md5"), conn)
|
||||
close(conn)
|
||||
}
|
||||
changed_md5 <- function(object) {
|
||||
tryCatch({
|
||||
conn <- file(paste0("data-raw/", deparse(substitute(object)), ".md5"))
|
||||
compared <- digest::digest(object, "md5") != readLines(con = conn)
|
||||
close(conn)
|
||||
compared
|
||||
}, error = function(e) TRUE)
|
||||
}
|
||||
|
||||
# give official names to ABs and MOs
|
||||
rsi <- AMR::rsi_translation %>%
|
||||
mutate(mo_name = mo_name(mo, language = NULL), .after = mo) %>%
|
||||
mutate(ab_name = ab_name(ab, language = NULL), .after = ab)
|
||||
if (changed_md5(rsi)) {
|
||||
usethis::ui_info(paste0("Saving {usethis::ui_value('rsi_translation')} to {usethis::ui_value('/data-raw/')}"))
|
||||
write_md5(rsi)
|
||||
try(saveRDS(rsi, "data-raw/rsi_translation.rds", version = 2, compress = "xz"), silent = TRUE)
|
||||
try(write.table(rsi, "data-raw/rsi_translation.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
|
||||
try(haven::write_sas(rsi, "data-raw/rsi_translation.sas"), silent = TRUE)
|
||||
try(haven::write_sav(rsi, "data-raw/rsi_translation.sav"), silent = TRUE)
|
||||
try(haven::write_dta(rsi, "data-raw/rsi_translation.dta"), silent = TRUE)
|
||||
try(openxlsx::write.xlsx(rsi, "data-raw/rsi_translation.xlsx"), silent = TRUE)
|
||||
}
|
||||
|
||||
mo <- dplyr::mutate_if(microorganisms, ~!is.numeric(.), as.character)
|
||||
if (changed_md5(mo)) {
|
||||
usethis::ui_info(paste0("Saving {usethis::ui_value('microorganisms')} to {usethis::ui_value('/data-raw/')}"))
|
||||
write_md5(mo)
|
||||
try(saveRDS(mo, "data-raw/microorganisms.rds", version = 2, compress = "xz"), silent = TRUE)
|
||||
try(write.table(mo, "data-raw/microorganisms.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
|
||||
try(haven::write_sas(dplyr::select(mo, -snomed), "data-raw/microorganisms.sas"), silent = TRUE)
|
||||
try(haven::write_sav(dplyr::select(mo, -snomed), "data-raw/microorganisms.sav"), silent = TRUE)
|
||||
try(haven::write_dta(dplyr::select(mo, -snomed), "data-raw/microorganisms.dta"), silent = TRUE)
|
||||
try(openxlsx::write.xlsx(dplyr::select(mo, -snomed), "data-raw/microorganisms.xlsx"), silent = TRUE)
|
||||
}
|
||||
|
||||
if (changed_md5(microorganisms.old)) {
|
||||
usethis::ui_info(paste0("Saving {usethis::ui_value('microorganisms.old')} to {usethis::ui_value('/data-raw/')}"))
|
||||
write_md5(microorganisms.old)
|
||||
try(saveRDS(microorganisms.old, "data-raw/microorganisms.old.rds", version = 2, compress = "xz"), silent = TRUE)
|
||||
try(write.table(microorganisms.old, "data-raw/microorganisms.old.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
|
||||
try(haven::write_sas(microorganisms.old, "data-raw/microorganisms.old.sas"), silent = TRUE)
|
||||
try(haven::write_sav(microorganisms.old, "data-raw/microorganisms.old.sav"), silent = TRUE)
|
||||
try(haven::write_dta(microorganisms.old, "data-raw/microorganisms.old.dta"), silent = TRUE)
|
||||
try(openxlsx::write.xlsx(microorganisms.old, "data-raw/microorganisms.old.xlsx"), silent = TRUE)
|
||||
}
|
||||
|
||||
ab <- dplyr::mutate_if(antibiotics, ~!is.numeric(.), as.character)
|
||||
if (changed_md5(ab)) {
|
||||
usethis::ui_info(paste0("Saving {usethis::ui_value('antibiotics')} to {usethis::ui_value('/data-raw/')}"))
|
||||
write_md5(ab)
|
||||
try(saveRDS(ab, "data-raw/antibiotics.rds", version = 2, compress = "xz"), silent = TRUE)
|
||||
try(write.table(ab, "data-raw/antibiotics.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
|
||||
try(haven::write_sas(ab, "data-raw/antibiotics.sas"), silent = TRUE)
|
||||
try(haven::write_sav(ab, "data-raw/antibiotics.sav"), silent = TRUE)
|
||||
try(haven::write_dta(ab, "data-raw/antibiotics.dta"), silent = TRUE)
|
||||
try(openxlsx::write.xlsx(ab, "data-raw/antibiotics.xlsx"), silent = TRUE)
|
||||
}
|
||||
|
||||
av <- dplyr::mutate_if(antivirals, ~!is.numeric(.), as.character)
|
||||
if (changed_md5(av)) {
|
||||
usethis::ui_info(paste0("Saving {usethis::ui_value('antivirals')} to {usethis::ui_value('/data-raw/')}"))
|
||||
write_md5(av)
|
||||
try(saveRDS(av, "data-raw/antivirals.rds", version = 2, compress = "xz"), silent = TRUE)
|
||||
try(write.table(av, "data-raw/antivirals.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
|
||||
try(haven::write_sas(av, "data-raw/antivirals.sas"), silent = TRUE)
|
||||
try(haven::write_sav(av, "data-raw/antivirals.sav"), silent = TRUE)
|
||||
try(haven::write_dta(av, "data-raw/antivirals.dta"), silent = TRUE)
|
||||
try(openxlsx::write.xlsx(av, "data-raw/antivirals.xlsx"), silent = TRUE)
|
||||
}
|
||||
|
||||
# give official names to ABs and MOs
|
||||
intrinsicR <- data.frame(microorganism = mo_name(intrinsic_resistant$mo, language = NULL),
|
||||
antibiotic = ab_name(intrinsic_resistant$ab, language = NULL),
|
||||
stringsAsFactors = FALSE)
|
||||
if (changed_md5(intrinsicR)) {
|
||||
usethis::ui_info(paste0("Saving {usethis::ui_value('intrinsic_resistant')} to {usethis::ui_value('/data-raw/')}"))
|
||||
write_md5(intrinsicR)
|
||||
try(saveRDS(intrinsicR, "data-raw/intrinsic_resistant.rds", version = 2, compress = "xz"), silent = TRUE)
|
||||
try(write.table(intrinsicR, "data-raw/intrinsic_resistant.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
|
||||
try(haven::write_sas(intrinsicR, "data-raw/intrinsic_resistant.sas"), silent = TRUE)
|
||||
try(haven::write_sav(intrinsicR, "data-raw/intrinsic_resistant.sav"), silent = TRUE)
|
||||
try(haven::write_dta(intrinsicR, "data-raw/intrinsic_resistant.dta"), silent = TRUE)
|
||||
try(openxlsx::write.xlsx(intrinsicR, "data-raw/intrinsic_resistant.xlsx"), silent = TRUE)
|
||||
}
|
||||
|
||||
if (changed_md5(dosage)) {
|
||||
usethis::ui_info(paste0("Saving {usethis::ui_value('dosage')} to {usethis::ui_value('/data-raw/')}"))
|
||||
write_md5(dosage)
|
||||
try(saveRDS(dosage, "data-raw/dosage.rds", version = 2, compress = "xz"), silent = TRUE)
|
||||
try(write.table(dosage, "data-raw/dosage.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
|
||||
try(haven::write_sas(dosage, "data-raw/dosage.sas"), silent = TRUE)
|
||||
try(haven::write_sav(dosage, "data-raw/dosage.sav"), silent = TRUE)
|
||||
try(haven::write_dta(dosage, "data-raw/dosage.dta"), silent = TRUE)
|
||||
try(openxlsx::write.xlsx(dosage, "data-raw/dosage.xlsx"), silent = TRUE)
|
||||
}
|
||||
|
||||
reset_AMR_locale()
|
||||
|
||||
# remove leftovers from global env
|
||||
current_globalenv <- ls(envir = globalenv())
|
||||
rm(list = current_globalenv[!current_globalenv %in% old_globalenv])
|
||||
rm(current_globalenv)
|
||||
@@ -1,82 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2022 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
# Run this file to update the languages used in the packages:
|
||||
# source("data-raw/_language_update.R")
|
||||
|
||||
if (!file.exists("DESCRIPTION") || !"Package: AMR" %in% readLines("DESCRIPTION")) {
|
||||
stop("Be sure to run this script in the root location of the AMR package folder.\n",
|
||||
"Working directory expected to contain the DESCRIPTION file of the AMR package.\n",
|
||||
"Current working directory: ", getwd(),
|
||||
call. = FALSE)
|
||||
}
|
||||
|
||||
# save old global env to restore later
|
||||
lang_env <- new.env(hash = FALSE)
|
||||
|
||||
# load current internal data into new env
|
||||
load("R/sysdata.rda", envir = lang_env)
|
||||
|
||||
# replace language objects with updates
|
||||
message("Reading translation file...")
|
||||
lang_env$TRANSLATIONS <- utils::read.delim(file = "data-raw/translations.tsv",
|
||||
sep = "\t",
|
||||
stringsAsFactors = FALSE,
|
||||
header = TRUE,
|
||||
blank.lines.skip = TRUE,
|
||||
fill = TRUE,
|
||||
strip.white = TRUE,
|
||||
encoding = "UTF-8",
|
||||
fileEncoding = "UTF-8",
|
||||
na.strings = c(NA, "", NULL),
|
||||
allowEscapes = TRUE, # else "\\1" will be imported as "\\\\1"
|
||||
quote = "")
|
||||
|
||||
lang_env$LANGUAGES_SUPPORTED_NAMES <- c(list(en = list(exonym = "English", endonym = "English")),
|
||||
lapply(lang_env$TRANSLATIONS[, which(nchar(colnames(lang_env$TRANSLATIONS)) == 2)],
|
||||
function(x) list(exonym = x[1], endonym = x[2])))
|
||||
|
||||
lang_env$LANGUAGES_SUPPORTED <- names(lang_env$LANGUAGES_SUPPORTED_NAMES)
|
||||
|
||||
# save env to internal package data
|
||||
# usethis::use_data() does not allow to save a list :(
|
||||
message("Saving to internal data...")
|
||||
save(list = names(lang_env),
|
||||
file = "R/sysdata.rda",
|
||||
ascii = FALSE,
|
||||
version = 2,
|
||||
compress = "xz",
|
||||
envir = lang_env)
|
||||
|
||||
rm(lang_env)
|
||||
|
||||
if ("roxygen2" %in% utils::installed.packages()) {
|
||||
message("Updating package documentation...")
|
||||
suppressMessages(roxygen2::roxygenise(package.dir = "."))
|
||||
} else {
|
||||
message("NOTE: please install the roxygen2 package to update package documentation, and run this script again.")
|
||||
}
|
||||
|
||||
message("Done!")
|
||||
@@ -1 +0,0 @@
|
||||
4f082a7952a37133305f64d6f711e81e
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
@@ -1,519 +0,0 @@
|
||||
"ab" "cid" "name" "group" "atc" "atc_group1" "atc_group2" "abbreviations" "synonyms" "oral_ddd" "oral_units" "iv_ddd" "iv_units" "loinc"
|
||||
"AMA" 4649 "4-aminosalicylic acid" "Antimycobacterials" "J04AA01" "Drugs for treatment of tuberculosis" "Aminosalicylic acid and derivatives" "" "c(\"aminopar\", \"aminosalicylic\", \"aminosalicylic acid\", \"aminosalyl\", \"aminox\", \"apacil\", \"deapasil\", \"entepas\", \"ferrosan\", \"gabbropas\", \"helipidyl\", \"hellipidyl\", \"neopasalate\", \"osacyl\", \"pamacyl\", \"pamisyl\", \"paramycin\", \"parasal\", \"parasalicil\", \"parasalindon\", \"pasalon\", \"pasara\", \"pascorbic\", \"pasdium\", \"paser granules\", \"paskalium\", \"pasmed\", \"pasnodia\", \"pasolac\", \"propasa\", \"rezipas\", \"teebacin\", \"wln: zr cq dvq\")" 12 "g" "character(0)"
|
||||
"FCT" 3366 "5-fluorocytosine" "Antifungals/antimycotics" "D01AE21" "Antifungals for topical use" "Other antifungals for topical use" "c(\"5flc\", \"fcu\", \"fluo\", \"fluy\")" "c(\"alcobon\", \"ancobon\", \"ancotil\", \"ancotyl\", \"flucitosina\", \"flucystine\", \"flucytosin\", \"flucytosine\", \"flucytosinum\", \"flucytosone\", \"fluocytosine\", \"fluorcytosine\")" "c(\"10974-4\", \"23805-5\", \"25142-1\", \"25143-9\", \"3639-2\", \"46218-4\")"
|
||||
"ACM" 6450012 "Acetylmidecamycin" "Macrolides/lincosamides" "" "" ""
|
||||
"ASP" 49787020 "Acetylspiramycin" "Macrolides/lincosamides" "" "c(\"acetylspiramycin\", \"foromacidin b\", \"spiramycin ii\")" "character(0)"
|
||||
"ALS" 8954 "Aldesulfone sodium" "Other antibacterials" "J04BA03" "Drugs for treatment of lepra" "Drugs for treatment of lepra" "" "c(\"adesulfone sodium\", \"aldapsone\", \"aldesulfona sodica\", \"aldesulfone\", \"aldesulfone sodique\", \"aldesulfone sodium\", \"diamidin\", \"diasone\", \"diasone sodium\", \"diazon\", \"novotrone\", \"sodium aldesulphone\", \"sodium sulfoxone\", \"sulfoxone sodium\")" 0.33 "g" "character(0)"
|
||||
"AMK" 37768 "Amikacin" "Aminoglycosides" "c(\"D06AX12\", \"J01GB06\", \"S01AA21\")" "Aminoglycoside antibacterials" "Other aminoglycosides" "c(\"ak\", \"ami\", \"amik\", \"amk\", \"an\")" "c(\"amicacin\", \"amikacillin\", \"amikacin\", \"amikacin base\", \"amikacin dihydrate\", \"amikacin sulfate\", \"amikacina\", \"amikacine\", \"amikacinum\", \"amikavet\", \"amikin\", \"amiklin\", \"amikozit\", \"amukin\", \"arikace\", \"briclin\", \"lukadin\", \"mikavir\", \"pierami\", \"potentox\")" 1 "g" "c(\"13546-7\", \"15098-7\", \"17798-0\", \"31097-9\", \"31098-7\", \"31099-5\", \"3319-1\", \"3320-9\", \"3321-7\", \"35669-1\", \"50802-8\", \"50803-6\", \"56628-1\", \"59378-0\", \"80972-3\")"
|
||||
"AKF" "Amikacin/fosfomycin" "Aminoglycosides" "" "" ""
|
||||
"AMX" 33613 "Amoxicillin" "Beta-lactams/penicillins" "J01CA04" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "c(\"ac\", \"amox\", \"amx\")" "c(\"actimoxi\", \"amoclen\", \"amolin\", \"amopen\", \"amopenixin\", \"amoxibiotic\", \"amoxicaps\", \"amoxicilina\", \"amoxicillin\", \"amoxicilline\", \"amoxicillinum\", \"amoxiden\", \"amoxil\", \"amoxivet\", \"amoxy\", \"amoxycillin\", \"anemolin\", \"aspenil\", \"biomox\", \"bristamox\", \"cemoxin\", \"clamoxyl\", \"delacillin\", \"dispermox\", \"efpenix\", \"flemoxin\", \"hiconcil\", \"histocillin\", \"hydroxyampicillin\", \"ibiamox\", \"imacillin\", \"lamoxy\", \"metafarma capsules\", \"metifarma capsules\", \"moxacin\", \"moxatag\", \"ospamox\", \"pamoxicillin\",
|
||||
\"piramox\", \"robamox\", \"sawamox pm\", \"tolodina\", \"unicillin\", \"utimox\", \"vetramox\")" 1.5 "g" 3 "g" "c(\"16365-9\", \"25274-2\", \"3344-9\", \"80133-2\")"
|
||||
"AMC" 23665637 "Amoxicillin/clavulanic acid" "Beta-lactams/penicillins" "J01CR02" "Beta-lactam antibacterials, penicillins" "Combinations of penicillins, incl. beta-lactamase inhibitors" "c(\"a/c\", \"amcl\", \"aml\", \"aug\", \"xl\")" "c(\"amocla\", \"amoclan\", \"amoclav\", \"amoxsiklav\", \"augmentan\", \"augmentin\", \"augmentin xr\", \"augmentine\", \"auspilic\", \"clamentin\", \"clamobit\", \"clavamox\", \"clavinex\", \"clavoxilin plus\", \"clavulin\", \"clavumox\", \"coamoxiclav\", \"eumetinex\", \"kmoxilin\", \"spectramox\", \"spektramox\", \"viaclav\", \"xiclav\")" 1.5 "g" 3 "g" "character(0)"
|
||||
"AXS" 465441 "Amoxicillin/sulbactam" "Beta-lactams/penicillins" "" "" ""
|
||||
"AMB" 5280965 "Amphotericin B" "Antifungals/antimycotics" "c(\"A01AB04\", \"A07AA07\", \"G01AA03\", \"J02AA01\")" "Antimycotics for systemic use" "Antibiotics" "c(\"amf\", \"amfb\", \"amph\")" "c(\"abelcet\", \"abelecet\", \"ambisome\", \"amfotericina b\", \"amphocin\", \"amphomoronal\", \"amphortericin b\", \"amphotec\", \"amphotericin\", \"amphotericin b\", \"amphotericine b\", \"amphotericinum b\", \"amphozone\", \"anfotericine b\", \"fungilin\", \"fungisome\", \"fungisone\", \"fungizone\", \"halizon\")" 40 "mg" 35 "mg" "c(\"16370-9\", \"3353-0\", \"3354-8\", \"40707-2\", \"40757-7\", \"49859-2\")"
|
||||
"AMH" "Amphotericin B-high" "Aminoglycosides" "c(\"amfo b high\", \"amhl\", \"ampho b high\", \"amphotericin high\")" "" ""
|
||||
"AMP" 6249 "Ampicillin" "Beta-lactams/penicillins" "c(\"J01CA01\", \"S01AA19\")" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "c(\"am\", \"amp\", \"ampi\")" "c(\"acillin\", \"adobacillin\", \"amblosin\", \"amcill\", \"amfipen\", \"amfipen v\", \"amipenix s\", \"ampichel\", \"ampicil\", \"ampicilina\", \"ampicillin\", \"ampicillin a\", \"ampicillin acid\", \"ampicillin anhydrate\", \"ampicillin anhydrous\", \"ampicillin base\", \"ampicillin sodium\", \"ampicillina\", \"ampicilline\", \"ampicillinum\", \"ampicin\", \"ampifarm\", \"ampikel\", \"ampimed\", \"ampipenin\", \"ampiscel\", \"ampisyn\", \"ampivax\", \"ampivet\", \"amplacilina\", \"amplin\", \"amplipenyl\", \"amplisom\", \"amplital\", \"anhydrous ampicillin\", \"austrapen\",
|
||||
\"binotal\", \"bonapicillin\", \"britacil\", \"campicillin\", \"copharcilin\", \"delcillin\", \"deripen\", \"divercillin\", \"doktacillin\", \"duphacillin\", \"grampenil\", \"guicitrina\", \"guicitrine\", \"lifeampil\", \"marcillin\", \"morepen\", \"norobrittin\", \"nuvapen\", \"olin kid\", \"omnipen\", \"orbicilina\", \"pen a oral\", \"pen ampil\", \"penbristol\", \"penbritin\", \"penbritin paediatric\", \"penbritin syrup\", \"penbrock\", \"penicline\", \"penimic\", \"pensyn\", \"pentrex\", \"pentrexl\", \"pentrexyl\", \"pentritin\", \"pfizerpen a\", \"polycillin\", \"polyflex\",
|
||||
\"ponecil\", \"princillin\", \"principen\", \"qidamp\", \"racenacillin\", \"rosampline\", \"roscillin\", \"semicillin\", \"semicillin r\", \"servicillin\", \"sumipanto\", \"synpenin\", \"texcillin\", \"tokiocillin\", \"tolomol\", \"totacillin\", \"totalciclina\", \"totapen\", \"trifacilina\", \"ukapen\", \"ultrabion\", \"ultrabron\", \"vampen\", \"viccillin\", \"viccillin s\", \"vidocillin\", \"wypicil\")" 2 "g" 6 "g" "c(\"21066-6\", \"3355-5\", \"33562-0\", \"33919-2\", \"43883-8\", \"43884-6\", \"87604-5\")"
|
||||
"SAM" 119561 "Ampicillin/sulbactam" "Beta-lactams/penicillins" "J01CR01" "Beta-lactam antibacterials, penicillins" "Combinations of penicillins, incl. beta-lactamase inhibitors" "c(\"a/s\", \"ab\", \"ams\", \"amsu\", \"apsu\", \"sam\")" "" 6 "g" ""
|
||||
"AMR" 73341 "Amprolium" "Other antibacterials" "" "c(\"amprocidum\", \"amprolio\", \"amprolium\", \"amprovine\")" "character(0)"
|
||||
"ANI" 166548 "Anidulafungin" "Antifungals/antimycotics" "J02AX06" "Antimycotics for systemic use" "Other antimycotics for systemic use" "anid" "c(\"anidulafungin\", \"anidulafungina\", \"anidulafungine\", \"anidulafunginum\", \"ecalta\", \"eraxis\")" 0.1 "g" "58420-1"
|
||||
"APL" 6602341 "Apalcillin" "Beta-lactams/penicillins" "" "c(\"apalcilina\", \"apalcillin\", \"apalcilline\", \"apalcillinum\")" "character(0)"
|
||||
"APR" 3081545 "Apramycin" "Aminoglycosides" "" "c(\"ambylan\", \"apralan\", \"apramicina\", \"apramycin\", \"apramycine\", \"apramycinum\", \"nebramycin ii\")" "character(0)"
|
||||
"ARB" 68682 "Arbekacin" "Aminoglycosides" "J01GB12" "" "c(\"arbekacin\", \"arbekacina\", \"arbekacine\", \"arbekacini sulfas\", \"arbekacinum\", \"habekacin\", \"haberacin\")" 0.2 "g" "character(0)"
|
||||
"APX" 71961 "Aspoxicillin" "Beta-lactams/penicillins" "J01CA19" "" "c(\"aspoxicilina\", \"aspoxicillan\", \"aspoxicillin\", \"aspoxicilline\", \"aspoxicillinum\")" 4 "g" "character(0)"
|
||||
"AST" 5284517 "Astromicin" "Aminoglycosides" "" "c(\"astromicin\", \"astromicin a\", \"astromicina\", \"astromicine\", \"astromicinum\", \"fortimicin a\")" "character(0)"
|
||||
"AVB" 9835049 "Avibactam" "Beta-lactams/penicillins" "" "c(\"avibactam\", \"avibactam free acid\")" "character(0)"
|
||||
"AVI" 71674 "Avilamycin" "Other antibacterials" "" "c(\"avilamycin\", \"avilamycina\", \"avilamycine\", \"avilamycinum\", \"surmax\")" "character(0)"
|
||||
"AVO" 16131159 "Avoparcin" "Glycopeptides" "" "" ""
|
||||
"AZD" 15574941 "Azidocillin" "Beta-lactams/penicillins" "J01CE04" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "" "c(\"azidocilina\", \"azidocillin\", \"azidocillina\", \"azidocilline\", \"azidocillinum\")" 1.5 "g" "character(0)"
|
||||
"AZM" 447043 "Azithromycin" "Macrolides/lincosamides" "c(\"J01FA10\", \"S01AA26\")" "Macrolides, lincosamides and streptogramins" "Macrolides" "c(\"az\", \"azi\", \"azit\", \"azm\")" "c(\"aritromicina\", \"azasite\", \"azenil\", \"azifast\", \"azigram\", \"azimakrol\", \"azithramycine\", \"azithromycin\", \"azithromycine\", \"azithromycinum\", \"azitrocin\", \"azitromax\", \"azitromicina\", \"azitromicine\", \"azitromin\", \"aziwok\", \"aztrin\", \"azyter\", \"azythromycin\", \"hemomycin\", \"misultina\", \"mixoterin\", \"setron\", \"sumamed\", \"tromix\", \"trulimax\", \"zentavion\", \"zithrax\", \"zithromac\", \"zithromax\", \"zithromax iv\", \"zithromycin\", \"zitrim\", \"zitromax\", \"zitrotek\", \"zmax sr\")" 0.3 "g" 0.5 "g" "c(\"16420-2\", \"25233-8\")"
|
||||
"AZL" 6479523 "Azlocillin" "Beta-lactams/penicillins" "J01CA09" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "c(\"az\", \"azl\", \"azlo\")" "" 12 "g" ""
|
||||
"ATM" 5742832 "Aztreonam" "Beta-lactams/penicillins" "J01DF01" "Other beta-lactam antibacterials" "Monobactams" "c(\"at\", \"atm\", \"azm\", \"azt\", \"aztr\")" "c(\"azactam\", \"azetreonam\", \"azthreonam\", \"aztreonam\", \"primbactam\")" 4 "g" "c(\"16423-6\", \"25234-6\", \"3369-6\")"
|
||||
"AZA" "Aztreonam/avibactam" "Beta-lactams/penicillins" "" "" ""
|
||||
"ANC" "Aztreonam/nacubactam" "Beta-lactams/penicillins" "" "" ""
|
||||
"BAM" 441397 "Bacampicillin" "Beta-lactams/penicillins" "J01CA06" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"bacampicilina\", \"bacampicillin\", \"bacampicilline\", \"bacampicillinum\", \"penglobe\")" 1.2 "g" "character(0)"
|
||||
"BAC" 78358334 "Bacitracin zinc" "Other antibacterials" "R02AB04" "baci" "" ""
|
||||
"BDQ" 5388906 "Bedaquiline" "Other antibacterials" "J04AK05" "" "c(\"bedaquiline\", \"sirturo\")" 86 "mg" "80637-2"
|
||||
"BEK" 439318 "Bekanamycin" "Aminoglycosides" "J01GB13" "" "c(\"aminodeoxykanamycin\", \"becanamicina\", \"bekanamycin\", \"bekanamycine\", \"bekanamycinum\", \"nebramycin v\")" 0.6 "g" "character(0)"
|
||||
"BNB" "Benzathine benzylpenicillin" "Beta-lactams/penicillins" "J01CE08" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "" "" 3.6 "g" ""
|
||||
"BNP" 64725 "Benzathine phenoxymethylpenicillin" "Beta-lactams/penicillins" "J01CE10" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "" "c(\"bicillin v\", \"biphecillin\")" 2 "g" "character(0)"
|
||||
"PEN" 5904 "Benzylpenicillin" "Beta-lactams/penicillins" "c(\"J01CE01\", \"S01AA14\")" "Combinations of antibacterials" "Combinations of antibacterials" "c(\"bepe\", \"pen\", \"peni\", \"peni g\", \"penicillin\", \"penicillin g\", \"pg\")" "c(\"abbocillin\", \"ayercillin\", \"bencilpenicilina\", \"benzopenicillin\", \"benzyl penicillin\", \"benzylpenicillin\", \"benzylpenicillin g\", \"benzylpenicilline\", \"benzylpenicillinum\", \"bicillin\", \"cillora\", \"cilloral\", \"cilopen\", \"compocillin g\", \"cosmopen\", \"dropcillin\", \"free penicillin g\", \"free penicillin ii\", \"galofak\", \"gelacillin\", \"liquacillin\", \"megacillin\", \"pencillin g\", \"penicillin\", \"penicilling\", \"pentids\", \"permapen\", \"pfizerpen\", \"pfizerpen g\", \"pharmacillin\", \"pradupen\", \"specilline g\", \"ursopen\"
|
||||
)" 3.6 "g" "3913-1"
|
||||
"BES" 10178705 "Besifloxacin" "Quinolones" "S01AE08" "" "besifloxacin" "character(0)"
|
||||
"BIA" 71339 "Biapenem" "Carbapenems" "J01DH05" "" "c(\"biapenem\", \"biapenern\", \"bipenem\", \"omegacin\")" 1.2 "g" "character(0)"
|
||||
"BCZ" 65807 "Bicyclomycin" "Other antibacterials" "c(\"\", \"bicozamycin\")" "c(\"aizumycin\", \"bacfeed\", \"bacteron\", \"bicozamicina\", \"bicozamycin\", \"bicozamycine\", \"bicozamycinum\")" "character(0)"
|
||||
"BDP" 68760 "Brodimoprim" "Trimethoprims" "J01EA02" "Sulfonamides and trimethoprim" "Trimethoprim and derivatives" "" "c(\"brodimoprim\", \"brodimoprima\", \"brodimoprime\", \"brodimoprimum\", \"bromdimoprim\", \"hyprim\", \"unitrim\")" 0.2 "g" "character(0)"
|
||||
"BUT" 47472 "Butoconazole" "Antifungals/antimycotics" "G01AF15" "" "c(\"butaconazole\", \"butoconazol\", \"butoconazole\", \"butoconazolum\", \"compositenstarke\", \"dahlin\", \"femstat\", \"gynofort\", \"polyfructosanum\")" "character(0)"
|
||||
"CDZ" 44242317 "Cadazolid" "Oxazolidinones" "" "cadazolid" "character(0)"
|
||||
"CLA" "Calcium aminosalicylate" "Antimycobacterials" "J04AA03" "Drugs for treatment of tuberculosis" "Aminosalicylic acid and derivatives" "" "" 15 "g" ""
|
||||
"CAP" 135565060 "Capreomycin" "Antimycobacterials" "J04AB30" "Drugs for treatment of tuberculosis" "Antibiotics" "c(\"\", \"capr\")" "" 1 "g" ""
|
||||
"CRB" 20824 "Carbenicillin" "Beta-lactams/penicillins" "J01CA03" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "c(\"bar\", \"carb\", \"cb\")" "c(\"anabactyl\", \"carbenicilina\", \"carbenicillin\", \"carbenicillina\", \"carbenicilline\", \"carbenicillinum\", \"geopen\", \"pyopen\")" 12 "g" "3434-8"
|
||||
"CRN" 93184 "Carindacillin" "Beta-lactams/penicillins" "J01CA05" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"carindacilina\", \"carindacillin\", \"carindacilline\", \"carindacillinum\")" 4 "g" "character(0)"
|
||||
"CAR" 6540466 "Carumonam" "Other antibacterials" "J01DF02" "" "c(\"carumonam\", \"carumonamum\")" 2 "g" "character(0)"
|
||||
"CAS" 2826718 "Caspofungin" "Antifungals/antimycotics" "J02AX04" "Antimycotics for systemic use" "Other antimycotics for systemic use" "casp" "c(\"cancidas\", \"capsofungin\", \"caspofungin\")" 50 "mg" "58419-3"
|
||||
"CAC" 91562 "Cefacetrile" "Cephalosporins (1st gen.)" "J01DB10" "Other beta-lactam antibacterials" "First-generation cephalosporins" "" "c(\"cefacetril\", \"cefacetrile\", \"cefacetrilo\", \"cefacetrilum\", \"celospor\", \"celtol\", \"cephacetrile\", \"cristacef\", \"vetrimast\")" "character(0)"
|
||||
"CEC" 51039 "Cefaclor" "Cephalosporins (2nd gen.)" "J01DC04" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "c(\"ccl\", \"cec\", \"cf\", \"cfac\", \"cfc\", \"cfcl\", \"cfr\", \"fac\")" "c(\"alenfral\", \"alfacet\", \"ceclor\", \"ceclor cd\", \"cefaclor\", \"cefaclor anhydrous\", \"cefaclor monohydrate\", \"cefacloro\", \"cefaclorum\", \"cefeaclor\", \"cephaclor\", \"dystaclor mr\", \"keflor\", \"kefral\", \"raniclor\")" 1 "g" "c(\"16564-7\", \"21149-0\")"
|
||||
"CFR" 47965 "Cefadroxil" "Cephalosporins (1st gen.)" "J01DB05" "Other beta-lactam antibacterials" "First-generation cephalosporins" "c(\"cfdx\", \"cfr\", \"fad\")" "c(\"cefadrops\", \"cefadroxil\", \"cefadroxil anhydrous\", \"cefadroxilo\", \"cefadroxilum\", \"cefradroxil\", \"cephadroxil\", \"duricef\", \"sumacef\", \"ultracef\")" 2 "g" "16565-4"
|
||||
"RID" 5773 "Cefaloridine" "Cephalosporins (1st gen.)" "J01DB02" "Other beta-lactam antibacterials" "First-generation cephalosporins" "cefa" "c(\"aliporina\", \"ampligram\", \"cefaloridin\", \"cefaloridina\", \"cefaloridine\", \"cefaloridinum\", \"cefalorizin\", \"ceflorin\", \"cepaloridin\", \"cepalorin\", \"cephalomycine\", \"cephaloridin\", \"cephaloridine\", \"cephaloridinum\", \"ceporan\", \"ceporin\", \"ceporine\", \"cilifor\", \"deflorin\", \"faredina\", \"floridin\", \"glaxoridin\", \"intrasporin\", \"keflodin\", \"keflordin\", \"kefloridin\", \"kefspor\", \"lloncefal\", \"loridine\", \"sasperin\", \"sefacin\", \"verolgin\", \"vioviantine\")" 3 "g" "character(0)"
|
||||
"MAN" 456255 "Cefamandole" "Cephalosporins (2nd gen.)" "J01DC03" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "c(\"cfam\", \"cfmn\")" "c(\"cefadole\", \"cefamandol\", \"cefamandole\", \"cefamandolum\", \"cephadole\", \"cephamandole\", \"kefamandol\", \"kefdole\", \"mancef\")" 6 "g" "3441-3"
|
||||
"CTZ" 6410758 "Cefatrizine" "Cephalosporins (1st gen.)" "J01DB07" "Other beta-lactam antibacterials" "First-generation cephalosporins" "" "c(\"bricef\", \"cefatrix\", \"cefatrizine\", \"cefatrizino\", \"cefatrizinum\", \"cepticol\", \"cetrazil\", \"latocef\", \"orosporina\", \"trizina\")" 1 "g" "character(0)"
|
||||
"CZD" 71736 "Cefazedone" "Cephalosporins (1st gen.)" "J01DB06" "Other beta-lactam antibacterials" "First-generation cephalosporins" "" "c(\"cefazedon\", \"cefazedona\", \"cefazedone\", \"cefazedone acid\", \"cefazedonum\", \"refosporen\", \"refosporene\", \"refosporin\")" 3 "g" "character(0)"
|
||||
"CZO" 33255 "Cefazolin" "Cephalosporins (1st gen.)" "J01DB04" "Other beta-lactam antibacterials" "First-generation cephalosporins" "c(\"cfz\", \"cfzl\", \"cz\", \"czol\", \"faz\", \"kz\")" "c(\"atirin\", \"cefamezin\", \"cefamezine\", \"cefazina\", \"cefazolin\", \"cefazolin acid\", \"cefazolina\", \"cefazoline\", \"cefazolinum\", \"cephamezine\", \"cephazolidin\", \"cephazolin\", \"cephazoline\", \"elzogram\", \"firmacef\", \"kefzol\", \"liviclina\", \"totacef\")" 3 "g" "c(\"16566-2\", \"25235-3\", \"3442-1\", \"3443-9\", \"80962-4\")"
|
||||
"CFB" 127527 "Cefbuperazone" "Other antibacterials" "J01DC13" "" "c(\"cefbuperazona\", \"cefbuperazone\", \"cefbuperazonum\", \"cefbuperzaone\", \"cerbuperazone\", \"tomiporan\")" 2 "g" "character(0)"
|
||||
"CCP" 6436055 "Cefcapene" "Cephalosporins (3rd gen.)" "J01DD17" "" "c(\"cefcamate\", \"cefcapene\")" 0.45 "g" "character(0)"
|
||||
"CCX" 5282438 "Cefcapene pivoxil" "Cephalosporins (3rd gen.)" "" "c(\"cefcamate pivoxil\", \"cefcapene piroxil\")" "character(0)"
|
||||
"CDR" 6915944 "Cefdinir" "Cephalosporins (3rd gen.)" "J01DD15" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"cd\", \"cdn\", \"cdr\", \"cfd\", \"din\")" "c(\"cefdinir\", \"cefdinirum\", \"cefdinyl\", \"cefdirnir\", \"ceftinex\", \"cefzon\", \"omnicef\")" 0.6 "g" "character(0)"
|
||||
"DIT" 9870843 "Cefditoren" "Cephalosporins (3rd gen.)" "J01DD16" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "cdn" "cefditoren" 0.4 "g" "character(0)"
|
||||
"DIX" 6437877 "Cefditoren pivoxil" "Cephalosporins (3rd gen.)" "" "c(\"cefditoren\", \"cefditoren pi voxil\", \"cefditoren pivoxil\", \"cefditorin\", \"cefditorin pivoxil\", \"meiact\", \"spectracef\")" "character(0)"
|
||||
"FEP" 5479537 "Cefepime" "Cephalosporins (4th gen.)" "J01DE01" "Other beta-lactam antibacterials" "Fourth-generation cephalosporins" "c(\"cfep\", \"cfpi\", \"cpe\", \"cpm\", \"fep\", \"pm\", \"xpm\")" "c(\"axepim\", \"cefepima\", \"cefepime\", \"cefepimum\", \"cepimax\", \"cepimex\", \"maxcef\", \"maxipime\")" 4 "g" "38363-8"
|
||||
"CPC" 9567559 "Cefepime/clavulanic acid" "Cephalosporins (4th gen.)" "c(\"cicl\", \"xpml\")" "" ""
|
||||
"FNC" "Cefepime/nacubactam" "Beta-lactams/penicillins" "" "" ""
|
||||
"FPT" 9567558 "Cefepime/tazobactam" "Cephalosporins (4th gen.)" "" "" ""
|
||||
"FPZ" "Cefepime/zidebactam" "Other antibacterials" "" "" ""
|
||||
"CAT" 5487888 "Cefetamet" "Cephalosporins (3rd gen.)" "J01DD10" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "" "c(\"cefetamet\", \"cefetametum\", \"cepime o\", \"deacetoxycefotaxime\")" 1 "g" "character(0)"
|
||||
"CPI" 5486182 "Cefetamet pivoxil" "Cephalosporins (3rd gen.)" "" "c(\"cefetamet pivoxyl\", \"globocef\")" "character(0)"
|
||||
"CCL" 71719688 "Cefetecol" "Cephalosporins (4th gen.)" "c(\"\", \"cefcatacol\")" "" ""
|
||||
"CZL" 193956 "Cefetrizole" "Cephalosporins (unclassified gen.)" "" "c(\"cefetrizole\", \"cefetrizolum\")" "character(0)"
|
||||
"FDC" 77843966 "Cefiderocol" "Other antibacterials" "J01DI04" "" "cefiderocol" "character(0)"
|
||||
"CFM" 5362065 "Cefixime" "Cephalosporins (3rd gen.)" "J01DD08" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"cfe\", \"cfix\", \"cfxm\", \"dcfm\", \"fix\", \"ix\")" "c(\"cefixim\", \"cefixima\", \"cefixime\", \"cefixime anhydrous\", \"cefiximum\", \"cefixoral\", \"cefspan\", \"cephoral\", \"denvar\", \"necopen\", \"suprax\", \"tricef\", \"unixime\")" 0.4 "g" "c(\"16567-0\", \"25236-1\")"
|
||||
"CMX" 9570757 "Cefmenoxime" "Cephalosporins (3rd gen.)" "J01DD05" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "" "c(\"bestron\", \"cefmax\", \"cefmenoxima\", \"cefmenoxime\", \"cefmenoximum\")" 2 "g" "character(0)"
|
||||
"CMZ" 42008 "Cefmetazole" "Cephalosporins (2nd gen.)" "J01DC09" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "" "c(\"cefmetazole\", \"cefmetazolo\", \"cefmetazolum\")" 4 "g" "character(0)"
|
||||
"CNX" 71141 "Cefminox" "Other antibacterials" "J01DC12" "" "c(\"cefminox\", \"cefminoxum\")" 4 "g" "character(0)"
|
||||
"DIZ" 5361871 "Cefodizime" "Cephalosporins (3rd gen.)" "J01DD09" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "" "c(\"cefodizima\", \"cefodizime\", \"cefodizime acid\", \"cefodizimum\", \"cefodizme\", \"diezime\", \"modivid\", \"neucef\", \"timecef\")" 2 "g" "character(0)"
|
||||
"CID" 43594 "Cefonicid" "Cephalosporins (2nd gen.)" "J01DC06" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "" "c(\"cefonicid\", \"cefonicido\", \"cefonicidum\", \"monocef\")" 1 "g" "c(\"25237-9\", \"3444-7\")"
|
||||
"CFP" 44187 "Cefoperazone" "Cephalosporins (3rd gen.)" "J01DD12" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"cfp\", \"cfpz\", \"cp\", \"cpz\", \"fop\", \"per\")" "c(\"bioperazone\", \"cefobid\", \"cefoperazine\", \"cefoperazon\", \"cefoperazone\", \"cefoperazone acid\", \"cefoperazono\", \"cefoperazonum\", \"cefozon\", \"medocef\", \"myticef\", \"pathozone\", \"peracef\")" 4 "g" "3445-4"
|
||||
"CSL" "Cefoperazone/sulbactam" "Cephalosporins (3rd gen.)" "J01DD62" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "" "" 4 "g" ""
|
||||
"CND" 43507 "Ceforanide" "Cephalosporins (2nd gen.)" "J01DC11" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "" "c(\"ceforanide\", \"ceforanido\", \"ceforanidum\", \"precef\", \"radacef\")" 4 "g" "character(0)"
|
||||
"CSE" 9830519 "Cefoselis" "Cephalosporins (4th gen.)" "" "c(\"cefoselis\", \"cefoselis sulfate\", \"winsef\")" "character(0)"
|
||||
"CTX" 5742673 "Cefotaxime" "Cephalosporins (3rd gen.)" "J01DD01" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"cfot\", \"cft\", \"cftx\", \"ct\", \"ctx\", \"fot\", \"tax\", \"xct\")" "c(\"cefotaxim\", \"cefotaxim hikma\", \"cefotaxima\", \"cefotaxime\", \"cefotaxime acid\", \"cefotaximum\", \"cephotaxime\", \"claforan\", \"omnatax\")" 4 "g" "c(\"25238-7\", \"3446-2\", \"80961-6\")"
|
||||
"CTC" 9575353 "Cefotaxime/clavulanic acid" "Cephalosporins (3rd gen.)" "c(\"cxcl\", \"xctl\")" "" ""
|
||||
"CTS" 9574753 "Cefotaxime/sulbactam" "Cephalosporins (3rd gen.)" "" "" ""
|
||||
"CTT" 53025 "Cefotetan" "Cephalosporins (2nd gen.)" "J01DC05" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "c(\"cftt\", \"cn\", \"cte\", \"ctn\", \"ctt\", \"tans\")" "c(\"apacef\", \"cefotetan\", \"cefotetan free acid\", \"cefotetanum\")" 4 "g" "c(\"25239-5\", \"3447-0\")"
|
||||
"CTF" 43708 "Cefotiam" "Cephalosporins (2nd gen.)" "J01DC07" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "" "c(\"cefotiam\", \"cefotiam?\", \"cefotiamum\", \"ceradolan\", \"ceradon\", \"haloapor\")" 1.2 "g" 4 "g" "character(0)"
|
||||
"CHE" 125846 "Cefotiam hexetil" "Cephalosporins (3rd gen.)" "" "c(\"cefotiam cilexetil\", \"pansporin t\")" "character(0)"
|
||||
"FOV" 9578573 "Cefovecin" "Cephalosporins (3rd gen.)" "" "" ""
|
||||
"FOX" 441199 "Cefoxitin" "Cephalosporins (2nd gen.)" "J01DC01" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "c(\"cfox\", \"cfx\", \"cfxt\", \"cx\", \"fox\", \"fx\")" "c(\"cefoxitin\", \"cefoxitina\", \"cefoxitine\", \"cefoxitinum\", \"cefoxotin\", \"cephoxitin\", \"mefoxin\", \"mefoxitin\", \"rephoxitin\")" 6 "g" "c(\"25240-3\", \"3448-8\")"
|
||||
"FOX1" "Cefoxitin screening" "Cephalosporins (2nd gen.)" "cfsc" "" ""
|
||||
"ZOP" 9571080 "Cefozopran" "Cephalosporins (4th gen.)" "J01DE03" "" "cefozopran" 4 "g" "character(0)"
|
||||
"CFZ" 68597 "Cefpimizole" "Cephalosporins (3rd gen.)" "" "c(\"cefpimizol\", \"cefpimizole\", \"cefpimizole sodium\", \"cefpimizolum\")" "character(0)"
|
||||
"CPM" 636405 "Cefpiramide" "Cephalosporins (3rd gen.)" "J01DD11" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "" "c(\"cefpiramide\", \"cefpiramide acid\", \"cefpiramido\", \"cefpiramidum\")" 2 "g" "character(0)"
|
||||
"CPO" 5479539 "Cefpirome" "Cephalosporins (4th gen.)" "J01DE02" "Other beta-lactam antibacterials" "Fourth-generation cephalosporins" "c(\"\", \"cfpr\")" "c(\"broact\", \"cefpiroma\", \"cefpirome\", \"cefpiromum\", \"cefrom\", \"cerfpirome\", \"keiten\")" 4 "g" "character(0)"
|
||||
"CPD" 6335986 "Cefpodoxime" "Cephalosporins (3rd gen.)" "J01DD13" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"cfpd\", \"cfpo\", \"cpd\", \"pod\", \"px\")" "c(\"cefpodoxim acid\", \"cefpodoxima\", \"cefpodoxime\", \"cefpodoxime acid\", \"cefpodoximum\", \"epoxim\")" 0.4 "g" "25241-1"
|
||||
"CPX" 6526396 "Cefpodoxime proxetil" "Cephalosporins (3rd gen.)" "" "c(\"cefodox\", \"cefoprox\", \"cefpodoxime proxetil\", \"cepodem\", \"orelox\", \"otreon\", \"podomexef\", \"simplicef\", \"vantin\")" "character(0)"
|
||||
"CDC" "Cefpodoxime/clavulanic acid" "Cephalosporins (3rd gen.)" "c(\"\", \"cecl\")" "" ""
|
||||
"CPR" 5281006 "Cefprozil" "Cephalosporins (2nd gen.)" "J01DC10" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "c(\"cpr\", \"cpz\", \"fp\")" "c(\"arzimol\", \"brisoral\", \"cefprozil\", \"cefprozil anhydrous\", \"cefprozil hydrate\", \"cefprozilo\", \"cefprozilum\", \"cefzil\", \"cronocef\", \"procef\", \"serozil\")" 1 "g" "character(0)"
|
||||
"CEQ" 5464355 "Cefquinome" "Cephalosporins (4th gen.)" "" "c(\"cefquinoma\", \"cefquinome\", \"cefquinomum\", \"cobactan\")" "character(0)"
|
||||
"CRD" 5284529 "Cefroxadine" "Cephalosporins (1st gen.)" "J01DB11" "Other beta-lactam antibacterials" "First-generation cephalosporins" "" "c(\"cefroxadine\", \"cefroxadino\", \"cefroxadinum\")" 2.1 "g" "character(0)"
|
||||
"CFS" 656575 "Cefsulodin" "Cephalosporins (3rd gen.)" "J01DD03" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"cfsl\", \"cfsu\")" "c(\"cefsulodin\", \"cefsulodine\", \"cefsulodino\", \"cefsulodinum\")" 4 "g" "c(\"131-3\", \"25242-9\")"
|
||||
"CSU" 68718 "Cefsumide" "Cephalosporins (unclassified gen.)" "" "c(\"cefsumide\", \"cefsumido\", \"cefsumidum\")" "character(0)"
|
||||
"CPT" 56841980 "Ceftaroline" "Cephalosporins (5th gen.)" "J01DI02" "c(\"\", \"cfro\")" "c(\"teflaro\", \"zinforo\")" 1.2 "g" "character(0)"
|
||||
"CPA" "Ceftaroline/avibactam" "Cephalosporins (5th gen.)" "" "" ""
|
||||
"CAZ" 5481173 "Ceftazidime" "Cephalosporins (3rd gen.)" "J01DD02" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"caz\", \"cefta\", \"cfta\", \"cftz\", \"taz\", \"tz\", \"xtz\")" "c(\"ceftazidim\", \"ceftazidima\", \"ceftazidime\", \"ceftazidimum\", \"ceptaz\", \"fortaz\", \"fortum\", \"pentacef\", \"tazicef\", \"tazidime\")" 4 "g" "c(\"21151-6\", \"3449-6\", \"80960-8\")"
|
||||
"CZA" 90643431 "Ceftazidime/avibactam" "Cephalosporins (3rd gen.)" "c(\"\", \"cfav\")" "c(\"avycaz\", \"zavicefta\")" ""
|
||||
"CCV" 9575352 "Ceftazidime/clavulanic acid" "Cephalosporins (3rd gen.)" "J01DD52" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"czcl\", \"xtzl\")" "" 6 "g" ""
|
||||
"CEM" 6537431 "Cefteram" "Cephalosporins (3rd gen.)" "J01DD18" "" "c(\"cefteram\", \"cefterame\", \"cefteramum\", \"ceftetrame\")" 0.4 "g" "character(0)"
|
||||
"CPL" 5362114 "Cefteram pivoxil" "Cephalosporins (3rd gen.)" "" "c(\"cefteram pivoxil\", \"tomiron\")" "character(0)"
|
||||
"CTL" 65755 "Ceftezole" "Cephalosporins (1st gen.)" "J01DB12" "Other beta-lactam antibacterials" "First-generation cephalosporins" "" "c(\"ceftezol\", \"ceftezole\", \"ceftezolo\", \"ceftezolum\", \"demethylcefazolin\")" 3 "g" "character(0)"
|
||||
"CTB" 5282242 "Ceftibuten" "Cephalosporins (3rd gen.)" "J01DD14" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"cb\", \"cfbu\", \"ctb\", \"tib\")" "c(\"ceftem\", \"ceftibuten\", \"ceftibuten hydrate\", \"ceftibutene\", \"ceftibuteno\", \"ceftibutenum\", \"cephem\", \"ceprifran\", \"isocef\", \"keimax\")" 0.4 "g" "character(0)"
|
||||
"TIO" 6328657 "Ceftiofur" "Cephalosporins (3rd gen.)" "" "c(\"ceftiofur\", \"ceftiofurum\", \"excede\", \"excenel\", \"naxcel\")" "character(0)"
|
||||
"CZX" 6533629 "Ceftizoxime" "Cephalosporins (3rd gen.)" "J01DD07" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"cfzx\", \"ctz\", \"cz\", \"czx\", \"tiz\", \"zox\")" "c(\"cefizox\", \"ceftisomin\", \"ceftix\", \"ceftizoxima\", \"ceftizoxime\", \"ceftizoximum\", \"epocelin\", \"eposerin\")" 4 "g" "c(\"25243-7\", \"3450-4\")"
|
||||
"CZP" 9578661 "Ceftizoxime alapivoxil" "Cephalosporins (3rd gen.)" "" "" ""
|
||||
"BPR" 135413542 "Ceftobiprole" "Cephalosporins (5th gen.)" "" "ceftobiprole" "character(0)"
|
||||
"CFM1" 135413544 "Ceftobiprole medocaril" "Cephalosporins (5th gen.)" "J01DI01" "Other beta-lactam antibacterials" "Other cephalosporins and penems" "" "" 1.5 "g" ""
|
||||
"CEI" "Ceftolozane/enzyme inhibitor" "Cephalosporins (5th gen.)" "J01DI54" "Other beta-lactam antibacterials" "Other cephalosporins and penems" "" "" 3 "g" ""
|
||||
"CZT" "Ceftolozane/tazobactam" "Cephalosporins (5th gen.)" "" "" ""
|
||||
"CRO" 5479530 "Ceftriaxone" "Cephalosporins (3rd gen.)" "J01DD04" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"axo\", \"cax\", \"cftr\", \"cro\", \"ctr\", \"frx\", \"tx\")" "c(\"biotrakson\", \"cefatriaxone\", \"cefatriaxone hydrate\", \"ceftriaxon\", \"ceftriaxona\", \"ceftriaxone\", \"ceftriaxone sodium\", \"ceftriaxonum\", \"ceftriazone\", \"cephtriaxone\", \"longacef\", \"rocefin\", \"rocephalin\", \"rocephin\", \"rocephine\", \"rophex\")" 2 "g" "c(\"25244-5\", \"3451-2\", \"80957-4\")"
|
||||
"CXM" 5479529 "Cefuroxime" "Cephalosporins (2nd gen.)" "c(\"J01DC02\", \"S01AA27\")" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "c(\"cfrx\", \"cfur\", \"cfx\", \"crm\", \"cxm\", \"fur\", \"rox\", \"xm\")" "c(\"biofuroksym\", \"cefuril\", \"cefuroxim\", \"cefuroxime\", \"cefuroximine\", \"cefuroximo\", \"cefuroximum\", \"cephuroxime\", \"kefurox\", \"sharox\", \"zinacef\", \"zinacef danmark\")" 0.5 "g" 3 "g" "c(\"25245-2\", \"3452-0\", \"80608-3\", \"80617-4\")"
|
||||
"CXA" 6321416 "Cefuroxime axetil" "Cephalosporins (2nd gen.)" "c(\"\", \"cfax\")" "c(\"altacef\", \"bioracef\", \"cefaks\", \"cefazine\", \"ceftin\", \"cefuroximaxetil\", \"cefuroxime axetil\", \"celocid\", \"cepazine\", \"cethixim\", \"cetoxil\", \"coliofossim\", \"elobact\", \"forcef\", \"furoxime\", \"kalcef\", \"maxitil\", \"medoxm\", \"nivador\", \"zinnat\")" "character(0)"
|
||||
"CFM2" "Cefuroxime/metronidazole" "Other antibacterials" "J01RA03" "Combinations of antibacterials" "Combinations of antibacterials" "" "" ""
|
||||
"ZON" 6336505 "Cefuzonam" "Other antibacterials" "" "c(\"cefuzonam\", \"cefuzonam sodium\", \"cefuzoname\", \"cefuzonamum\")" "character(0)"
|
||||
"LEX" 27447 "Cephalexin" "Cephalosporins (1st gen.)" "J01DB01" "Other beta-lactam antibacterials" "First-generation cephalosporins" "c(\"\", \"cflx\")" "c(\"alcephin\", \"alexin\", \"alsporin\", \"anhydrous cefalexin\", \"anhydrous cephalexin\", \"biocef\", \"carnosporin\", \"cefablan\", \"cefadal\", \"cefadin\", \"cefadina\", \"cefaleksin\", \"cefalessina\", \"cefalexin\", \"cefalexin anhydrous\", \"cefalexina\", \"cefalexine\", \"cefalexinum\", \"cefalin\", \"cefaloto\", \"cefaseptin\", \"ceflax\", \"ceforal\", \"cefovit\", \"celexin\", \"cepastar\", \"cepexin\", \"cephacillin\", \"cephalexin\", \"cephalexin anhydrous\", \"cephalexine\", \"cephalexinum\", \"cephanasten\", \"cephaxin\", \"cephin\", \"ceporex\", \"ceporex forte\",
|
||||
\"ceporexin\", \"ceporexine\", \"cerexin\", \"cerexins\", \"cophalexin\", \"durantel\", \"durantel ds\", \"erocetin\", \"factagard\", \"felexin\", \"ibilex\", \"ibrexin\", \"inphalex\", \"kefalospes\", \"keflet\", \"keflex\", \"kefolan\", \"keforal\", \"keftab\", \"kekrinal\", \"kidolex\", \"lafarine\", \"larixin\", \"lenocef\", \"lexibiotico\", \"lonflex\", \"lopilexin\", \"madlexin\", \"mamalexin\", \"mamlexin\", \"medoxine\", \"neokef\", \"neolexina\", \"novolexin\", \"optocef\", \"oracef\", \"oriphex\", \"oroxin\", \"ortisporina\", \"ospexin\", \"palitrex\", \"panixine disperdose\",
|
||||
\"pectril\", \"pyassan\", \"roceph\", \"roceph distab\", \"sanaxin\", \"sartosona\", \"sencephalin\", \"sepexin\", \"servispor\", \"sialexin\", \"sinthecillin\", \"sporicef\", \"sporidex\", \"syncle\", \"synecl\", \"tepaxin\", \"tokiolexin\", \"uphalexin\", \"voxxim\", \"winlex\", \"zozarine\")" 2 "g" "c(\"21175-5\", \"3453-8\")"
|
||||
"CEP" 6024 "Cephalothin" "Cephalosporins (1st gen.)" "J01DB03" "Other beta-lactam antibacterials" "First-generation cephalosporins" "c(\"cfal\", \"cflt\")" "c(\"cefalothin\", \"cefalotin\", \"cefalotina\", \"cefalotina fabra\", \"cefalotine\", \"cefalotinum\", \"cemastin\", \"cephalothinum\", \"cephalotin\", \"coaxin\", \"keflin\", \"seffin\")" 4 "g" "c(\"25246-0\", \"3454-6\")"
|
||||
"HAP" 30699 "Cephapirin" "Cephalosporins (1st gen.)" "J01DB08" "Other beta-lactam antibacterials" "First-generation cephalosporins" "" "c(\"ambrocef\", \"cefadyl\", \"cefapilin\", \"cefapirin\", \"cefapirina\", \"cefapirine\", \"cefapirinum\", \"cefaprin\", \"cefaprin sodium\", \"cefatrex\", \"cefatrexyl\", \"cephapirine\", \"metricure\")" 4 "g" "10980-1"
|
||||
"CED" 38103 "Cephradine" "Cephalosporins (1st gen.)" "J01DB09" "Other beta-lactam antibacterials" "First-generation cephalosporins" "c(\"cfra\", \"cfrd\")" "c(\"anspor\", \"cefradin\", \"cefradina\", \"cefradine\", \"cefradinum\", \"cekodin\", \"cephradin\", \"cephradine\", \"eskacef\", \"infexin\", \"megace f\", \"megacef\", \"sefril\", \"velocef\", \"velosef\")" 2 "g" 2 "g" "character(0)"
|
||||
"CTO" 71402 "Cetocycline" "Tetracyclines" "" "c(\"cetocycline\", \"cetocyline\", \"cetotetrine\")" "character(0)"
|
||||
"CHL" 5959 "Chloramphenicol" "Amphenicols" "c(\"D06AX02\", \"D10AF03\", \"G01AA05\", \"J01BA01\", \"S01AA01\", \"S02AA01\", \"S03AA08\")" "Amphenicols" "Amphenicols" "c(\"c\", \"chl\", \"chlo\", \"cl\")" "c(\"alficetyn\", \"ambofen\", \"amphenicol\", \"amphicol\", \"amseclor\", \"anacetin\", \"aquamycetin\", \"austracil\", \"austracol\", \"biocetin\", \"biophenicol\", \"catilan\", \"ch loramex\", \"chemiceticol\", \"chemicetin\", \"chemicetina\", \"chlomin\", \"chlomycol\", \"chloramex\", \"chloramfenikol\", \"chloramficin\", \"chloramfilin\", \"chloramphenicol\", \"chloramphenicole\", \"chloramphenicolum\", \"chloramsaar\", \"chlorasol\", \"chlorbiotic\", \"chloricol\", \"chlormycetin r\", \"chlornitromycin\", \"chloroamphenicol\", \"chlorocaps\", \"chlorocid\",
|
||||
\"chlorocid s\", \"chlorocide\", \"chlorocidin c\", \"chlorocidin c tetran\", \"chlorocin\", \"chlorocol\", \"chlorofair\", \"chloroject l\", \"chloromax\", \"chloromycetin\", \"chloromycetny\", \"chloromyxin\", \"chloronitrin\", \"chloroptic\", \"chloroptic s.o.p\", \"chloroptic s.o.p.\", \"chlorovules\", \"chlorsig\", \"cidocetine\", \"ciplamycetin\", \"cloramfen\", \"cloramfenicol\", \"cloramfenicolo\", \"cloramficin\", \"cloramical\", \"cloramicol\", \"cloramidina\", \"cloranfenicol\", \"cloroamfenicolo\", \"clorocyn\", \"cloromisan\", \"cloromissan\", \"clorosintex\",
|
||||
\"comycetin\", \"cylphenicol\", \"desphen\", \"detreomycin\", \"detreomycine\", \"dextromycetin\", \"doctamicina\", \"duphenicol\", \"econochlor\", \"embacetin\", \"emetren\", \"enicol\", \"enteromycetin\", \"erbaplast\", \"ertilen\", \"f armicetina\", \"farmicetina\", \"fenicol\", \"globenicol\", \"glorous\", \"halomycetin\", \"hortfenicol\", \"interomycetine\", \"intramycetin\", \"intramyctin\", \"isicetin\", \"ismicetina\", \"isophenicol\", \"isopto fenicol\", \"juvamycetin\", \"kamaver\", \"kemicetina\", \"kemicetine\", \"kloramfenikol\", \"klorita\", \"klorocid s\",
|
||||
\"laevomycetinum\", \"leukamycin\", \"leukomyan\", \"leukomycin\", \"levocin\", \"levomicetina\", \"levomitsetin\", \"levomycetin\", \"levoplast\", \"levosin\", \"levovetin\", \"loromicetina\", \"loromisan\", \"loromisin\", \"mastiphen\", \"mediamycetine\", \"medichol\", \"micloretin\", \"micochlorine\", \"micoclorina\", \"microcetina\", \"mychel\", \"mycinol\", \"myclocin\", \"mycochlorin\", \"myscel\", \"normimycin v\", \"novochlorocap\", \"novomycetin\", \"novophenicol\", \"ocuphenicol\", \"oftalent\", \"oleomycetin\", \"opclor\", \"opelor\", \"ophthochlor\", \"ophthocort\",
|
||||
\"ophtochlor\", \"optomycin\", \"otachron\", \"otophen\", \"pantovernil\", \"paraxin\", \"pentamycetin\", \"quemicetina\", \"rivomycin\", \"romphenil\", \"ronfenil\", \"ronphenil\", \"septicol\", \"sificetina\", \"sintomicetina\", \"sintomicetine r\", \"sno phenicol\", \"soluthor\", \"stanomycetin\", \"synthomycetin\", \"synthomycetine\", \"synthomycine\", \"syntomycin\", \"tevcocin\", \"tevcosin\", \"tifomycin\", \"tifomycine\", \"tiromycetin\", \"treomicetina\", \"unimycetin\", \"veticol\", \"vice ton\", \"viceton\")" 3 "g" 3 "g" "c(\"15101-9\", \"16603-3\", \"16604-1\", \"25247-8\", \"29214-4\", \"29346-4\", \"29347-2\", \"3455-3\")"
|
||||
"CTE" 54675777 "Chlortetracycline" "Tetracyclines" "c(\"A01AB21\", \"D06AA02\", \"J01AA03\", \"S01AA02\")" "Tetracyclines" "Tetracyclines" "" "c(\"acronize\", \"aueromycin\", \"aureocina\", \"aureomycin\", \"aureomykoin\", \"biomitsin\", \"biomycin\", \"biomycin a\", \"chlormax\", \"chlorotetracycline\", \"chlortetracycline\", \"chlortetracyclinum\", \"chrysomykine\", \"clortetraciclina\", \"duomycin\", \"flamycin\", \"uromycin\")" 1 "g" "87600-3"
|
||||
"CIC" 19003 "Ciclacillin" "Beta-lactams/penicillins" "" "c(\"bastcillin\", \"calthor\", \"ciclacilina\", \"ciclacillin\", \"ciclacilline\", \"ciclacillinum\", \"ciclacillum\", \"citosarin\", \"cyclacillin\", \"cyclapen\", \"noblicil\", \"orfilina\", \"peamezin\", \"syngacillin\", \"ultracillin\", \"vastcillin\", \"vipicil\", \"wyvital\")" "character(0)"
|
||||
"CIX" 47472 "Ciclopirox" "Antifungals/antimycotics" "c(\"D01AE14\", \"G01AX12\")" "Antifungals for topical use" "Other antifungals for topical use" "cipx" "c(\"butaconazole\", \"butoconazol\", \"butoconazole\", \"butoconazolum\", \"compositenstarke\", \"dahlin\", \"femstat\", \"gynofort\", \"polyfructosanum\")" "character(0)"
|
||||
"CIN" 2762 "Cinoxacin" "Quinolones" "J01MB06" "Quinolone antibacterials" "Other quinolones" "c(\"cino\", \"cnox\")" "c(\"azolinic acid\", \"cinobac\", \"cinobactin\", \"cinoxacin\", \"cinoxacine\", \"cinoxacino\", \"cinoxacinum\", \"clinoxacin\", \"noxigram\", \"uronorm\")" 1 "g" "character(0)"
|
||||
"CIP" 2764 "Ciprofloxacin" "Quinolones" "c(\"J01MA02\", \"S01AE03\", \"S02AA15\", \"S03AA07\")" "Quinolone antibacterials" "Fluoroquinolones" "c(\"ci\", \"cip\", \"cipr\", \"cp\")" "c(\"alcon cilox\", \"auripro\", \"bacquinor\", \"baflox\", \"baycip\", \"bernoflox\", \"cetraxal\", \"ciflox\", \"cifloxin\", \"ciloxan\", \"ciplus\", \"ciprecu\", \"ciprine\", \"ciprinol\", \"cipro i.v.\", \"cipro iv\", \"cipro xl\", \"cipro xr\", \"ciprobay\", \"ciprobay uro\", \"ciprocinol\", \"ciprodar\", \"ciproflox\", \"ciprofloxacin\", \"ciprofloxacina\", \"ciprofloxacine\", \"ciprofloxacino\", \"ciprofloxacinum\", \"ciprogis\", \"ciprolin\", \"ciprolon\", \"cipromycin\", \"ciproquinol\", \"ciprowin\", \"ciproxan\", \"ciproxin\", \"ciproxina\", \"ciproxine\", \"ciriax\",
|
||||
\"citopcin\", \"corsacin\", \"cyprobay\", \"fimoflox\", \"flociprin\", \"ipiflox\", \"italnik\", \"linhaliq\", \"otiprio\", \"probiox\", \"proflaxin\", \"quinolid\", \"quintor\", \"rancif\", \"roxytal\", \"septicide\", \"sophixin ofteno\", \"spitacin\", \"superocin\", \"velmonit\", \"velomonit\", \"zumaflox\")" 1 "g" 0.8 "g" "c(\"14031-9\", \"14032-7\", \"14058-2\", \"14059-0\", \"25248-6\", \"34636-1\", \"3484-3\")"
|
||||
"CLR" 84029 "Clarithromycin" "Macrolides/lincosamides" "J01FA09" "Macrolides, lincosamides and streptogramins" "Macrolides" "c(\"ch\", \"cla\", \"clar\", \"clm\", \"clr\")" "c(\"abbotic\", \"astromen\", \"biaxin\", \"biaxin filmtab\", \"biaxin hp\", \"biaxin xl\", \"biaxin xl filmtab\", \"bicrolid\", \"clacee\", \"clacid\", \"clacine\", \"clambiotic\", \"clarem\", \"claribid\", \"claricide\", \"claridar\", \"claripen\", \"clarith\", \"clarithromycin\", \"clarithromycine\", \"clarithromycinum\", \"claritromicina\", \"clathromycin\", \"crixan\", \"cyllid\", \"cyllind\", \"fromilid\", \"heliclar\", \"klabax\", \"klacid\", \"klaciped\", \"klaricid\", \"klaricid h.p\", \"klaricid h.p.\", \"klaricid pediatric\", \"klaricid xl\", \"klarid\", \"klarin\",
|
||||
\"kofron\", \"mabicrol\", \"macladin\", \"maclar\", \"veclam\", \"vikrol\", \"zeclar\")" 0.5 "g" 1 "g" "c(\"16619-9\", \"25253-6\", \"34638-7\", \"80559-8\")"
|
||||
"CLA1" 5280980 "Clavulanic acid" "Other antibacterials" "" "c(\"acide clavulanique\", \"acido clavulanico\", \"acidum clavulanicum\", \"clavulanate\", \"clavulanate acid\", \"clavulanate lithium\", \"clavulanic acid\", \"clavulansaeure\", \"clavulansaure\", \"clavulinic acid\", \"clavulox\", \"sodium clavulanate\")" "character(0)"
|
||||
"CLX" 60063 "Clinafloxacin" "Quinolones" "" "clinafloxacin" "character(0)"
|
||||
"CLI" 446598 "Clindamycin" "Macrolides/lincosamides" "c(\"D10AF01\", \"G01AA10\", \"J01FF01\")" "Macrolides, lincosamides and streptogramins" "Lincosamides" "c(\"cc\", \"cd\", \"cli\", \"clin\", \"cm\", \"da\")" "c(\"antirobe\", \"chlolincocin\", \"clindaderm\", \"clindamicina\", \"clindamycin\", \"clindamycine\", \"clindamycinum\", \"clinimycin\", \"dalacin c\", \"dalacine\", \"klimicin\", \"sobelin\")" 1.2 "g" 1.8 "g" "c(\"16621-5\", \"16622-3\", \"25249-4\", \"3486-8\")"
|
||||
"CLF" 2794 "Clofazimine" "Antimycobacterials" "J04BA01" "Drugs for treatment of lepra" "Drugs for treatment of lepra" "clof" "c(\"chlofazimine\", \"clofazimin\", \"clofazimina\", \"clofazimine\", \"clofaziminum\", \"lampren\", \"lamprene\", \"riminophenazine\")" 0.1 "g" "character(0)"
|
||||
"CLF1" 2799 "Clofoctol" "Other antibacterials" "J01XX03" "Other antibacterials" "Other antibacterials" "" "c(\"clofoctol\", \"clofoctolo\", \"clofoctolum\", \"gramplus\", \"octofene\")" "character(0)"
|
||||
"CLM" 71807 "Clometocillin" "Beta-lactams/penicillins" "J01CE07" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "" "c(\"chlomethocillin\", \"clometacillin\", \"clometocilina\", \"clometocillin\", \"clometocilline\", \"clometocillinum\", \"rixapen\")" 1 "g" "character(0)"
|
||||
"CLM1" 54680675 "Clomocycline" "Tetracyclines" "J01AA11" "Tetracyclines" "Tetracyclines" "" "c(\"chlormethylencycline\", \"clomociclina\", \"clomocyclin\", \"clomocycline\", \"clomocyclinum\", \"megaclor\")" 1 "g" "character(0)"
|
||||
"CTR" 2812 "Clotrimazole" "Antifungals/antimycotics" "c(\"A01AB18\", \"D01AC01\", \"G01AF02\")" "clot" "c(\"canesten\", \"canesten cream\", \"canesten solution\", \"canestene\", \"canestine\", \"canifug\", \"chlotrimazole\", \"cimitidine\", \"clomatin\", \"clotrimaderm\", \"clotrimaderm cream\", \"clotrimazol\", \"clotrimazole\", \"clotrimazolum\", \"cutistad\", \"desamix f\", \"diphenylmethane\", \"empecid\", \"esparol\", \"fem care\", \"femcare\", \"gyne lotrimin\", \"jidesheng\", \"kanesten\", \"klotrimazole\", \"lotrimax\", \"lotrimin\", \"lotrimin af\", \"lotrimin af cream\", \"lotrimin af lotion\", \"lotrimin af solution\", \"lotrimin cream\", \"lotrimin lotion\",
|
||||
\"lotrimin solution\", \"monobaycuten\", \"mycelax\", \"mycelex\", \"mycelex cream\", \"mycelex g\", \"mycelex otc\", \"mycelex solution\", \"mycelex troches\", \"mycelex twin pack\", \"myclo cream\", \"myclo solution\", \"myclo spray solution\", \"mycofug\", \"mycosporin\", \"mykosporin\", \"nalbix\", \"otomax\", \"pedisafe\", \"rimazole\", \"stiemazol\", \"tibatin\", \"trimysten\", \"veltrim\")" "character(0)"
|
||||
"CLO" 6098 "Cloxacillin" "Beta-lactams/penicillins" "J01CF02" "Beta-lactam antibacterials, penicillins" "Beta-lactamase resistant penicillins" "c(\"\", \"clox\")" "c(\"chloroxacillin\", \"clossacillina\", \"cloxacilina\", \"cloxacillin\", \"cloxacillin sodium\", \"cloxacilline\", \"cloxacillinna\", \"cloxacillinum\", \"cloxapen\", \"methocillin s\", \"orbenin\", \"syntarpen\", \"tegopen\")" 2 "g" 2 "g" "c(\"16628-0\", \"25250-2\")"
|
||||
"COL" 5311054 "Colistin" "Polymyxins" "c(\"A07AA10\", \"J01XB01\")" "Other antibacterials" "Polymyxins" "c(\"cl\", \"coli\", \"cs\", \"cst\", \"ct\")" "c(\"belcomycine\", \"colimycin\", \"colimycin sulphate\", \"colisticin\", \"colistimethate\", \"colistimethate sodium\", \"colistin sulfate\", \"colistin sulphate\", \"colomycin\", \"coly-mycin\", \"polymyxin e\", \"polymyxin e. sulfate\", \"promixin\", \"totazina\")" 9 "MU" 9 "MU" "c(\"16645-4\", \"29493-4\")"
|
||||
"COP" "Colistin/polysorbate" "Other antibacterials" "" "" ""
|
||||
"CYC" 6234 "Cycloserine" "Oxazolidinones" "J04AB01" "Drugs for treatment of tuberculosis" "Antibiotics" "cycl" "c(\"cicloserina\", \"closerin\", \"closina\", \"cyclorin\", \"cycloserin\", \"cycloserine\", \"cycloserinum\", \"farmiserina\", \"micoserina\", \"miroserina\", \"miroseryn\", \"novoserin\", \"oxamicina\", \"oxamycin\", \"seromycin\", \"tebemicina\", \"tisomycin\", \"wasserina\")" 0.75 "g" "c(\"16702-3\", \"25251-0\", \"3519-6\")"
|
||||
"DAL" 23724878 "Dalbavancin" "Glycopeptides" "J01XA04" "Other antibacterials" "Glycopeptide antibacterials" "dalb" "c(\"dalbavancin\", \"dalvance\")" 1.5 "g" "character(0)"
|
||||
"DAN" 71335 "Danofloxacin" "Quinolones" "" "c(\"advocin\", \"danofloxacin\", \"danofloxacine\", \"danofloxacino\", \"danofloxacinum\")" "character(0)"
|
||||
"DPS" 2955 "Dapsone" "Other antibacterials" "c(\"D10AX05\", \"J04BA02\")" "Drugs for treatment of lepra" "Drugs for treatment of lepra" "" "c(\"aczone\", \"araldite ht\", \"atrisone\", \"avlosulfon\", \"avlosulfone\", \"avlosulphone\", \"avsulfor\", \"bis sulfone\", \"bissulfone\", \"bissulphone\", \"croysulfone\", \"croysulphone\", \"dapson\", \"dapsona\", \"dapsone\", \"dapsonum\", \"di sulfone\", \"diaphenyl sulfone\", \"diaphenylsulfon\", \"diaphenylsulfone\", \"diaphenylsulphon\", \"diaphenylsulphone\", \"dimitone\", \"diphenasone\", \"diphone\", \"disulfone\", \"disulone\", \"disulphone\", \"dubronax\", \"dubronaz\", \"dumitone\", \"eporal\", \"metabolite c\", \"novophone\", \"protogen\", \"servidapson\",
|
||||
\"slphadione\", \"sulfadione\", \"sulfona\", \"sulfone ucb\", \"sulfonyldianiline\", \"sulphadione\", \"sulphonyldianiline\", \"sumicure s\", \"tarimyl\", \"udolac\", \"wln: zr dswr dz\")" 50 "mg" "9747-7"
|
||||
"DAP" 16134395 "Daptomycin" "Other antibacterials" "J01XX09" "Other antibacterials" "Other antibacterials" "c(\"dap\", \"dapt\")" "c(\"cidecin\", \"cubicin\", \"dapcin\", \"daptomicina\", \"daptomycine\", \"daptomycinum\")" 0.28 "g" "character(0)"
|
||||
"DFX" 487101 "Delafloxacin" "Quinolones" "J01MA23" "" "c(\"baxdela\", \"delafloxacin\", \"delafloxacinum\")" 0.9 "g" 0.6 "g" "character(0)"
|
||||
"DLM" 6480466 "Delamanid" "Antimycobacterials" "J04AK06" "Drugs for treatment of tuberculosis" "Other drugs for treatment of tuberculosis" "dela" "c(\"delamanid\", \"deltyba\")" 0.2 "g" "character(0)"
|
||||
"DEM" 54680690 "Demeclocycline" "Tetracyclines" "c(\"D06AA01\", \"J01AA01\")" "Tetracyclines" "Tetracyclines" "" "c(\"bioterciclin\", \"clortetrin\", \"deganol\", \"demeclociclina\", \"demeclocycline\", \"demeclocyclinum\", \"demeclor\", \"demetraclin\", \"diuciclin\", \"elkamicina\", \"ledermycin\", \"mexocine\", \"novotriclina\", \"perciclina\", \"sumaclina\")" 0.6 "g" "c(\"10982-7\", \"29494-2\")"
|
||||
"DKB" 470999 "Dibekacin" "Aminoglycosides" "J01GB09" "Aminoglycoside antibacterials" "Other aminoglycosides" "" "c(\"debecacin\", \"dibekacin\", \"dibekacin sulfate\", \"dibekacina\", \"dibekacine\", \"dibekacinum\", \"dideoxykanamycin b\", \"kappati\", \"orbicin\", \"panamicin\")" 0.14 "g" "character(0)"
|
||||
"DIC" 18381 "Dicloxacillin" "Beta-lactams/penicillins" "J01CF01" "Beta-lactam antibacterials, penicillins" "Beta-lactamase resistant penicillins" "c(\"\", \"dicl\")" "c(\"dichloroxacillin\", \"diclossacillina\", \"dicloxaciclin\", \"dicloxacilin\", \"dicloxacilina\", \"dicloxacillin\", \"dicloxacillin sodium\", \"dicloxacillina\", \"dicloxacilline\", \"dicloxacillinum\", \"dicloxacycline\", \"dycill\", \"dynapen\", \"maclicine\", \"nm|| dicloxacillin\", \"pathocil\")" 2 "g" 2 "g" "c(\"10984-3\", \"16769-2\", \"25252-8\")"
|
||||
"DIF" 56206 "Difloxacin" "Quinolones" "" "difloxacin" "character(0)"
|
||||
"DIR" 6473883 "Dirithromycin" "Macrolides/lincosamides" "J01FA13" "Macrolides, lincosamides and streptogramins" "Macrolides" "" "c(\"dirithromycin\", \"dirithromycine\", \"dirithromycinum\", \"diritromicina\", \"divitross\", \"dynabac\", \"noriclan\", \"valodin\")" 0.5 "g" "character(0)"
|
||||
"DOR" 73303 "Doripenem" "Carbapenems" "J01DH04" "Other beta-lactam antibacterials" "Carbapenems" "dori" "c(\"doribax\", \"doripenem\", \"doripenem hydrate\", \"finibax\")" 1.5 "g" "character(0)"
|
||||
"DOX" 54671203 "Doxycycline" "Tetracyclines" "c(\"A01AB22\", \"J01AA02\")" "Tetracyclines" "Tetracyclines" "c(\"dox\", \"doxy\")" "c(\"atridox\", \"azudoxat\", \"deoxymykoin\", \"dossiciclina\", \"doxcycline anhydrous\", \"doxiciclina\", \"doxitard\", \"doxivetin\", \"doxycen\", \"doxychel\", \"doxycin\", \"doxycyclin\", \"doxycycline\", \"doxycycline calcium\", \"doxycycline hyclate\", \"doxycyclinum\", \"doxylin\", \"doxysol\", \"doxytec\", \"doxytetracycline\", \"hydramycin\", \"investin\", \"jenacyclin\", \"liviatin\", \"monodox\", \"oracea\", \"periostat\", \"ronaxan\", \"spanor\", \"supracyclin\", \"vibramycin\", \"vibramycin novum\", \"vibramycine\", \"vibravenos\", \"zenavod\")" 0.1 "g" 0.1 "g" "c(\"10986-8\", \"21250-6\", \"26902-7\")"
|
||||
"ECO" 3198 "Econazole" "Antifungals/antimycotics" "c(\"D01AC03\", \"G01AF05\")" "Antifungals for topical use" "Imidazole and triazole derivatives" "econ" "c(\"econazol\", \"econazole\", \"econazolum\", \"ecostatin\", \"ecostatin cream\", \"palavale\", \"pevaryl\", \"spectazole\", \"spectazole cream\")" "character(0)"
|
||||
"ENX" 3229 "Enoxacin" "Quinolones" "J01MA04" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"enox\")" "c(\"almitil\", \"bactidan\", \"bactidron\", \"comprecin\", \"enofloxacine\", \"enoksetin\", \"enoram\", \"enoxacin\", \"enoxacina\", \"enoxacine\", \"enoxacino\", \"enoxacinum\", \"enoxen\", \"enoxin\", \"enoxor\", \"flumark\", \"penetrex\")" 0.8 "g" "c(\"16816-1\", \"3590-7\")"
|
||||
"ENR" 71188 "Enrofloxacin" "Quinolones" "" "c(\"baytril\", \"enrofloxacin\", \"enrofloxacine\", \"enrofloxacino\", \"enrofloxacinum\")" "character(0)"
|
||||
"ENV" 135565326 "Enviomycin" "Antimycobacterials" "c(\"\", \"tuberactinomycin\")" "c(\"enviomicina\", \"enviomycin\", \"enviomycina\", \"enviomycinum\")" "character(0)"
|
||||
"EPE" "Eperozolid" "Other antibacterials" "" "" ""
|
||||
"EPC" 71392 "Epicillin" "Beta-lactams/penicillins" "J01CA07" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"dexacillin\", \"dihydroampicillin\", \"epicilina\", \"epicillin\", \"epicilline\", \"epicillinum\")" 2 "g" 2 "g" "character(0)"
|
||||
"EPP" 68916 "Epiroprim" "Other antibacterials" "" "c(\"epiroprim\", \"epiroprima\", \"epiroprime\", \"epiroprimum\")" "character(0)"
|
||||
"ERV" 54726192 "Eravacycline" "Tetracyclines" "J01AA13" "Tetracyclines" "Tetracyclines" "erav" "eravacycline" "character(0)"
|
||||
"ETP" 150610 "Ertapenem" "Carbapenems" "J01DH03" "Other beta-lactam antibacterials" "Carbapenems" "c(\"erta\", \"etp\")" "c(\"ertapenem\", \"invanz\")" 1 "g" "character(0)"
|
||||
"ERY" 12560 "Erythromycin" "Macrolides/lincosamides" "c(\"D10AF02\", \"J01FA01\", \"S01AA17\")" "Macrolides, lincosamides and streptogramins" "Macrolides" "c(\"e\", \"em\", \"ery\", \"eryt\")" "c(\"abboticin\", \"abomacetin\", \"acneryne\", \"acnesol\", \"akne cordes losung\", \"aknederm ery gel\", \"aknemycin\", \"austrias\", \"benzamycin\", \"derimer\", \"deripil\", \"dotycin\", \"dumotrycin\", \"emuvin\", \"emycin\", \"endoeritrin\", \"erecin\", \"erisone\", \"eritomicina\", \"eritrocina\", \"eritromicina\", \"ermycin\", \"eryacne\", \"eryacnen\", \"eryc sprinkles\", \"erycen\", \"erycette\", \"erycin\", \"erycinum\", \"eryderm\", \"erydermer\", \"erygel\", \"eryhexal\", \"erymax\", \"erymed\", \"erysafe\", \"erytab\", \"erythrocin\", \"erythrocin stearate\",
|
||||
\"erythroderm\", \"erythrogran\", \"erythroguent\", \"erythromid\", \"erythromycin\", \"erythromycin a\", \"erythromycin base\", \"erythromycin lactate\", \"erythromycine\", \"erythromycines\", \"erythromycinum\", \"erytop\", \"erytrociclin\", \"ilocaps\", \"ilosone\", \"iloticina\", \"ilotycin\", \"ilotycin gluceptate\", \"ilotycin t.s.\", \"inderm\", \"inderm gel\", \"indermretcin\", \"latotryd\", \"lederpax\", \"mephamycin\", \"mercina\", \"oftamolets\", \"paediathrocin\", \"pantoderm\", \"pantodrin\", \"pantomicina\", \"pce dispertab\", \"pharyngocin\", \"primacine\",
|
||||
\"propiocine\", \"proterytrin\", \"retcin\", \"robimycin\", \"romycin\", \"sansac\", \"skid gel e\", \"staticin\", \"stiemicyn\", \"stiemycin\", \"theramycin z\", \"tiloryth\", \"tiprocin\", \"torlamicina\", \"udima ery gel\", \"wyamycin s\")" 2 "g" 1 "g" "c(\"12298-6\", \"16829-4\", \"25275-9\", \"3597-2\")"
|
||||
"ETH" 14052 "Ethambutol" "Antimycobacterials" "J04AK02" "Drugs for treatment of tuberculosis" "Other drugs for treatment of tuberculosis" "etha" "c(\"aethambutolum\", \"ebutol\", \"etambutol\", \"etambutolo\", \"etapiam\", \"ethambutol\", \"ethambutolum\", \"myambutol\", \"mycobutol\", \"purderal\", \"servambutol\")" 1.2 "g" 1.2 "g" "c(\"25404-5\", \"3607-9\")"
|
||||
"ETI" 456476 "Ethambutol/isoniazid" "Antimycobacterials" "J04AM03" "Drugs for treatment of tuberculosis" "Combinations of drugs for treatment of tuberculosis" "" "" ""
|
||||
"ETI1" 2761171 "Ethionamide" "Antimycobacterials" "J04AD03" "Drugs for treatment of tuberculosis" "Thiocarbamide derivatives" "ethi" "c(\"aethionamidum\", \"aetina\", \"aetiva\", \"amidazin\", \"amidazine\", \"ethatyl\", \"ethimide\", \"ethina\", \"ethinamide\", \"ethionamide\", \"ethionamidum\", \"ethioniamide\", \"ethylisothiamide\", \"ethyonomide\", \"etimid\", \"etiocidan\", \"etionamid\", \"etionamida\", \"etionamide\", \"etioniamid\", \"etionid\", \"etionizin\", \"etionizina\", \"etionizine\", \"fatoliamid\", \"iridocin\", \"iridocin bayer\", \"iridozin\", \"isothin\", \"isotiamida\", \"itiocide\", \"nicotion\", \"nisotin\", \"nizotin\", \"rigenicid\", \"sertinon\", \"teberus\", \"thianid\", \"thianide\",
|
||||
\"thioamide\", \"thiodine\", \"thiomid\", \"thioniden\", \"tianid\", \"tiomid\", \"trecator\", \"trecator sc\", \"trekator\", \"trescatyl\", \"trescazide\", \"tubenamide\", \"tubermin\", \"tuberoid\", \"tuberoson\")" 0.75 "g" "16845-0"
|
||||
"ETO" 6034 "Ethopabate" "Other antibacterials" "" "c(\"amprol plus\", \"ethopabat\", \"ethopabate\", \"ethyl pabate\")" "character(0)"
|
||||
"EXE" "Exebacase" "" "" ""
|
||||
"FAR" 65894 "Faropenem" "Other antibacterials" "J01DI03" "Other beta-lactam antibacterials" "Other cephalosporins and penems" "" "c(\"faropenem\", \"faropenem sodium\", \"fropenem\", \"fropenum sodium\")" 0.75 "g" "character(0)"
|
||||
"FDX" 10034073 "Fidaxomicin" "Other antibacterials" "A07AA12" "" "c(\"dificid\", \"dificlir\", \"difimicin\", \"fidaxomicin\", \"lipiarmycin\", \"tiacumicin b\")" 0.4 "g" "character(0)"
|
||||
"FIN" 11567473 "Finafloxacin" "Quinolones" "" "finafloxacin" "character(0)"
|
||||
"FLA" 46783781 "Flavomycin" "Other antibacterials" "" "moenomycin complex" "character(0)"
|
||||
"FLE" 3357 "Fleroxacin" "Quinolones" "J01MA08" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"fler\")" "c(\"fleroxacin\", \"fleroxacine\", \"fleroxacino\", \"fleroxacinum\", \"fleroxicin\", \"megalocin\", \"megalone\", \"megalosin\", \"quinodis\")" 0.4 "g" 0.4 "g" "character(0)"
|
||||
"FLO" 65864 "Flomoxef" "Other antibacterials" "J01DC14" "" "c(\"flomoxef\", \"flomoxefo\", \"flomoxefum\")" 2 "g" "character(0)"
|
||||
"FLR" 114811 "Florfenicol" "Other antibacterials" "" "c(\"aquafen\", \"florfenicol\", \"nuflor\", \"nuflor gold\")" "87599-7"
|
||||
"FLC" 21319 "Flucloxacillin" "Beta-lactams/penicillins" "J01CF05" "Beta-lactam antibacterials, penicillins" "Beta-lactamase resistant penicillins" "c(\"clox\", \"flux\")" "c(\"floxacillin\", \"floxapen\", \"floxapen sodium salt\", \"fluclox\", \"flucloxacilina\", \"flucloxacillin\", \"flucloxacilline\", \"flucloxacillinum\", \"fluorochloroxacillin\")" 2 "g" 2 "g" "character(0)"
|
||||
"FLU" 3365 "Fluconazole" "Antifungals/antimycotics" "c(\"D01AC15\", \"J02AC01\")" "Antimycotics for systemic use" "Triazole derivatives" "c(\"fluc\", \"fluz\", \"flz\")" "c(\"alflucoz\", \"alfumet\", \"biocanol\", \"biozole\", \"biozolene\", \"canzol\", \"cryptal\", \"diflazon\", \"diflucan\", \"dimycon\", \"elazor\", \"flucazol\", \"fluconazol\", \"fluconazole\", \"fluconazole capsules\", \"fluconazolum\", \"flucostat\", \"flukezol\", \"flunazol\", \"flunizol\", \"flusol\", \"fluzon\", \"fluzone\", \"forcan\", \"fuconal\", \"fungata\", \"loitin\", \"oxifugol\", \"pritenzol\", \"syscan\", \"trican\", \"triconal\", \"triflucan\", \"zoltec\")" 0.2 "g" 0.2 "g" "c(\"10987-6\", \"16870-8\", \"25255-1\", \"80530-9\")"
|
||||
"FLM" 3374 "Flumequine" "Quinolones" "J01MB07" "Quinolone antibacterials" "Other quinolones" "" "c(\"apurone\", \"fantacin\", \"flumequine\", \"flumequino\", \"flumequinum\", \"flumigal\", \"flumiquil\", \"flumisol\", \"flumix\", \"imequyl\")" 1.2 "g" "character(0)"
|
||||
"FLR1" 71260 "Flurithromycin" "Macrolides/lincosamides" "J01FA14" "Macrolides, lincosamides and streptogramins" "Macrolides" "" "c(\"flurithromicina\", \"flurithromycime\", \"flurithromycin\", \"flurithromycine\", \"flurithromycinum\", \"fluritromicina\", \"fluritromycinum\", \"flurizic\")" 0.75 "g" "character(0)"
|
||||
"FFL" 214356 "Fosfluconazole" "Antifungals/antimycotics" "" "c(\"fosfluconazole\", \"phosfluconazole\", \"procif\", \"prodif\")" "character(0)"
|
||||
"FOS" 446987 "Fosfomycin" "Other antibacterials" "J01XX01" "Other antibacterials" "Other antibacterials" "c(\"ff\", \"fm\", \"fo\", \"fof\", \"fos\", \"fosf\")" "c(\"fosfocina\", \"fosfomicina\", \"fosfomycin\", \"fosfomycin sodium\", \"fosfomycine\", \"fosfomycinum\", \"fosfonomycin\", \"monuril\", \"monurol\", \"phosphonemycin\", \"phosphonomycin\", \"veramina\")" 3 "g" 8 "g" "character(0)"
|
||||
"FMD" 572 "Fosmidomycin" "Other antibacterials" "" "c(\"fosmidomycin\", \"fosmidomycina\", \"fosmidomycine\", \"fosmidomycinum\")" "character(0)"
|
||||
"FRM" 8378 "Framycetin" "Aminoglycosides" "c(\"D09AA01\", \"R01AX08\", \"S01AA07\")" "c(\"\", \"fram\")" "c(\"actilin\", \"actiline\", \"antibiotique\", \"bycomycin\", \"endomixin\", \"enterfram\", \"fradiomycin\", \"fradiomycin b\", \"fradiomycinum\", \"framicetina\", \"framycetin\", \"framycetin sulfate\", \"framycetine\", \"framycetinum\", \"framygen\", \"fraquinol\", \"jernadex\", \"myacine\", \"myacyne\", \"mycerin\", \"mycifradin\", \"neobrettin\", \"neolate\", \"neomas\", \"neomcin\", \"neomicina\", \"neomin\", \"neomycin\", \"neomycin b\", \"neomycin b sulfate\", \"neomycin solution\", \"neomycin sulfate\", \"neomycin sulphate\", \"neomycinb\", \"neomycine\", \"neomycinum\",
|
||||
\"nivemycin\", \"pimavecort\", \"soframycin\", \"soframycine\", \"tuttomycin\", \"vonamycin\", \"vonamycin powder v\")" "character(0)"
|
||||
"FRZ" 5323714 "Furazolidone" "Other antibacterials" "G01AX06" "" "c(\"bifuron\", \"corizium\", \"coryzium\", \"diafuron\", \"enterotoxon\", \"furall\", \"furaxon\", \"furaxone\", \"furazol\", \"furazolidine\", \"furazolidon\", \"furazolidona\", \"furazolidone\", \"furazolidonum\", \"furazolum\", \"furazon\", \"furidon\", \"furovag\", \"furox aerosol powder\", \"furoxal\", \"furoxane\", \"furoxon\", \"furoxone\", \"furoxone liquid\", \"furoxone swine mix\", \"furozolidine\", \"giardil\", \"giarlam\", \"medaron\", \"neftin\", \"nicolen\", \"nifulidone\", \"nifuran\", \"nifurazolidone\", \"nifurazolidonum\", \"nitrofurazolidone\", \"nitrofurazolidonum\",
|
||||
\"nitrofuroxon\", \"optazol\", \"ortazol\", \"puradin\", \"roptazol\", \"sclaventerol\", \"tikofuran\", \"topazone\", \"trichofuron\", \"tricofuron\", \"tricoron\", \"trifurox\", \"viofuragyn\")" "character(0)"
|
||||
"FUS" 3000226 "Fusidic acid" "Other antibacterials" "c(\"D06AX01\", \"D09AA02\", \"J01XC01\", \"S01AA13\")" "Other antibacterials" "Steroid antibacterials" "c(\"fa\", \"fusi\")" "c(\"acide fusidique\", \"acido fusidico\", \"acidum fusidicum\", \"flucidin\", \"fucidate\", \"fucidate sodium\", \"fucidic acid\", \"fucidin\", \"fucidin acid\", \"fucithalmic\", \"fusidate\", \"fusidate acid\", \"fusidic acid\", \"fusidine\", \"fusidinic acid\", \"ramycin\")" 1.5 "g" 1.5 "g" "character(0)"
|
||||
"GAM" 59364992 "Gamithromycin" "Macrolides/lincosamides" "" "gamithromycin" "character(0)"
|
||||
"GRN" 124093 "Garenoxacin" "Quinolones" "J01MA19" "" "c(\"ganefloxacin\", \"garenfloxacin\", \"garenoxacin\")" 0.4 "g" "character(0)"
|
||||
"GAT" 5379 "Gatifloxacin" "Quinolones" "c(\"J01MA16\", \"S01AE06\")" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"gati\")" "c(\"gatiflo\", \"gatifloxacin\", \"gatifloxacine\", \"gatifloxcin\", \"gatilox\", \"gatiquin\", \"gatispan\", \"tequin\", \"tequin and zymar\", \"zymaxid\")" 0.4 "g" 0.4 "g" "character(0)"
|
||||
"GEM" 9571107 "Gemifloxacin" "Quinolones" "J01MA15" "Quinolone antibacterials" "Fluoroquinolones" "" "c(\"factiv\", \"factive\", \"gemifioxacin\", \"gemifloxacin\", \"gemifloxacine\", \"gemifloxacino\", \"gemifloxacinum\")" 0.32 "g" "character(0)"
|
||||
"GEN" 3467 "Gentamicin" "Aminoglycosides" "c(\"D06AX07\", \"J01GB03\", \"S01AA11\", \"S02AA14\", \"S03AA06\")" "Aminoglycoside antibacterials" "Other aminoglycosides" "c(\"cn\", \"gen\", \"gent\", \"gm\")" "c(\"apogen\", \"centicin\", \"cidomycin\", \"garasol\", \"genoptic liquifilm\", \"genoptic s.o.p.\", \"gentacycol\", \"gentafair\", \"gentak\", \"gentamar\", \"gentamcin sulfate\", \"gentamicin\", \"gentamicina\", \"gentamicine\", \"gentamicins\", \"gentamicinum\", \"gentamycin\", \"gentamycins\", \"gentamycinum\", \"gentavet\", \"gentocin\", \"jenamicin\", \"lyramycin\", \"oksitselanim\", \"refobacin\", \"refobacin tm\", \"septigen\", \"uromycine\")" 0.24 "g" "c(\"13561-6\", \"13562-4\", \"15106-8\", \"22746-2\", \"22747-0\", \"31091-2\", \"31092-0\", \"31093-8\", \"35668-3\", \"3663-2\", \"3664-0\", \"3665-7\", \"39082-3\", \"47109-4\", \"59379-8\", \"80971-5\", \"88111-0\")"
|
||||
"GEH" "Gentamicin-high" "Aminoglycosides" "c(\"gehi\", \"gehl\", \"genta high\", \"gentamicin high\")" "" ""
|
||||
"GEP" 25101874 "Gepotidacin" "Other antibacterials" "" "gepotidacin" "character(0)"
|
||||
"GRX" 72474 "Grepafloxacin" "Quinolones" "J01MA11" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"grep\")" "grepafloxacin" 0.4 "g" "character(0)"
|
||||
"GRI" 441140 "Griseofulvin" "Antifungals/antimycotics" "c(\"D01AA08\", \"D01BA01\")" "" "c(\"amudane\", \"curling factor\", \"delmofulvina\", \"fulcin\", \"fulcine\", \"fulvican grisactin\", \"fulvicin\", \"fulvicin bolus\", \"fulvidex\", \"fulvina\", \"fulvinil\", \"fulvistatin\", \"fungivin\", \"greosin\", \"gresfeed\", \"gricin\", \"grifulin\", \"grifulvin\", \"grifulvin v\", \"grisactin\", \"grisactin ultra\", \"grisactin v\", \"griscofulvin\", \"grise ostatin\", \"grisefuline\", \"griseo\", \"griseofulvin\", \"griseofulvin forte\", \"griseofulvina\", \"griseofulvine\", \"griseofulvinum\", \"griseomix\", \"griseostatin\", \"grisetin\", \"grisofulvin\",
|
||||
\"grisovin\", \"grisovin fp\", \"grizeofulvin\", \"grysio\", \"guservin\", \"lamoryl\", \"likuden\", \"likunden\", \"murfulvin\", \"poncyl\", \"spirofulvin\", \"sporostatin xan\", \"xuanjing\")" 0.5 "g" "12402-4"
|
||||
"HAB" 175989 "Habekacin" "Aminoglycosides" "" "c(\"arbekacin sulfate\", \"habekacin\", \"habekacin sulfate\", \"habekacin xsulfate\")" "character(0)"
|
||||
"HCH" 11979956 "Hachimycin" "Antifungals/antimycotics" "c(\"D01AA03\", \"G01AA06\", \"J02AA02\")" "Antimycotics for systemic use" "Antibiotics" "" "c(\"cabimicina\", \"hachimicina\", \"hachimycin\", \"hachimycine\", \"hachimycinum\", \"trichomycinum\", \"trichonat\")" "character(0)"
|
||||
"HET" 443387 "Hetacillin" "Beta-lactams/penicillins" "J01CA18" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"etacillina\", \"hetacilina\", \"hetacillin\", \"hetacilline\", \"hetacillinum\", \"phenazacillin\", \"versapen\")" 2 "g" "character(0)"
|
||||
"HYG" 56928061 "Hygromycin" "Aminoglycosides" "" "c(\"antihelmycin\", \"hydromycin b\", \"hygrovetine\")" "character(0)"
|
||||
"IBX" "Ibrexafungerp" "Antifungals" "" "" ""
|
||||
"ICL" 213043 "Iclaprim" "Other antibacterials" "J01EA03" "" "c(\"iclaprim\", \"mersarex\")" "character(0)"
|
||||
"IPM" 104838 "Imipenem" "Carbapenems" "J01DH51" "Other beta-lactam antibacterials" "Carbapenems" "c(\"imci\", \"imi\", \"imip\", \"imp\")" "c(\"imipemide\", \"imipenem\", \"imipenem anhydrous\", \"imipenem/cilastatin\", \"imipenemum\", \"imipenen\", \"primaxin\", \"tienamycin\")" 2 "g" "c(\"17010-0\", \"25257-7\", \"27331-8\", \"3688-9\")"
|
||||
"IPE" "Imipenem/EDTA" "Carbapenems" "" "" ""
|
||||
"IMR" "Imipenem/relebactam" "Carbapenems" "" "" ""
|
||||
"ISV" 6918485 "Isavuconazole" "Antifungals/antimycotics" "J02AC05" "c(\"\", \"isav\")" "isavuconazole" 0.2 "g" 0.2 "g" "character(0)"
|
||||
"ISE" 3037209 "Isepamicin" "Aminoglycosides" "J01GB11" "Aminoglycoside antibacterials" "Other aminoglycosides" "" "c(\"isepacin\", \"isepalline\", \"isepamicin\", \"isepamicina\", \"isepamicine\", \"isepamicinum\")" 0.4 "g" "character(0)"
|
||||
"ISO" 3760 "Isoconazole" "Antifungals/antimycotics" "c(\"D01AC05\", \"G01AF07\")" "Antimycotics for topic use" "Triazole derivatives" "" "c(\"isoconazol\", \"isoconazole\", \"isoconazolum\", \"travogen\")" "character(0)"
|
||||
"INH" 3767 "Isoniazid" "Antimycobacterials" "J04AC01" "Drugs for treatment of tuberculosis" "Hydrazides" "inh" "c(\"abdizide\", \"andrazide\", \"anidrasona\", \"antimicina\", \"antituberkulosum\", \"armacide\", \"armazid\", \"armazide\", \"atcotibine\", \"azt + isoniazid\", \"azuren\", \"bacillin\", \"cemidon\", \"chemiazid\", \"chemidon\", \"continazine\", \"cortinazine\", \"cotinazin\", \"cotinizin\", \"defonin\", \"dibutin\", \"diforin\", \"dinacrin\", \"ditubin\", \"ebidene\", \"eralon\", \"ertuban\", \"eutizon\", \"evalon\", \"fetefu\", \"fimalene\", \"hid rasonil\", \"hidranizil\", \"hidrasonil\", \"hidrulta\", \"hidrun\", \"hycozid\", \"hydrazid\", \"hydrazide\", \"hyozid\", \"i.a.i.\",
|
||||
\"idrazil\", \"inizid\", \"iscotin\", \"isidrina\", \"ismazide\", \"isobicina\", \"isocid\", \"isocidene\", \"isocotin\", \"isohydrazide\", \"isokin\", \"isolyn\", \"isonerit\", \"isonex\", \"isoniacid\", \"isoniazid\", \"isoniazid sa\", \"isoniazida\", \"isoniazide\", \"isoniazidum\", \"isonicazide\", \"isonicid\", \"isonico\", \"isonicotan\", \"isonicotil\", \"isonicotinhydrazid\", \"isonicotinohydrazide\", \"isonide\", \"isonidrin\", \"isonikazid\", \"isonilex\", \"isonin\", \"isonindon\", \"isonirit\", \"isoniton\", \"isonizida\", \"isonizide\", \"isotamine\", \"isotebe\",
|
||||
\"isotebezid\", \"isotinyl\", \"isozid\", \"isozide\", \"isozyd\", \"laniazid\", \"laniozid\", \"lanizid\", \"mayambutol\", \"mybasan\", \"neoteben\", \"neoxin\", \"neumandin\", \"niadrin\", \"nicazide\", \"nicetal\", \"nicizina\", \"niconyl\", \"nicotibina\", \"nicotibine\", \"nicotisan\", \"nicozide\", \"nidaton\", \"nidrazid\", \"nikozid\", \"niplen\", \"nitadon\", \"niteban\", \"nydrazid\", \"nyscozid\", \"pelazid\", \"percin\", \"phthisen\", \"pycazide\", \"pyreazid\", \"pyricidin\", \"pyridicin\", \"pyrizidin\", \"raumanon\", \"razide\", \"retozide\", \"rifater\", \"rimicid\",
|
||||
\"rimifon\", \"rimiphone\", \"rimitsid\", \"robiselin\", \"robisellin\", \"roxifen\", \"sanohidrazina\", \"sauterazid\", \"sauterzid\", \"stanozide\", \"tebecid\", \"tebenic\", \"tebexin\", \"tebilon\", \"teebaconin\", \"tekazin\", \"tibazide\", \"tibemid\", \"tibiazide\", \"tibinide\", \"tibison\", \"tibivis\", \"tibizide\", \"tibusan\", \"tisiodrazida\", \"tizide\", \"tubazid\", \"tubazide\", \"tubeco\", \"tubecotubercid\", \"tuberian\", \"tubicon\", \"tubilysin\", \"tubizid\", \"tubomel\", \"unicocyde\", \"unicozyde\", \"vazadrine\", \"vederon\", \"zidafimia\", \"zinadon\",
|
||||
\"zonazide\")" 0.3 "g" 0.3 "g" "c(\"25451-6\", \"26756-7\", \"3697-0\", \"40371-7\")"
|
||||
"ITR" 3793 "Itraconazole" "Antifungals/antimycotics" "J02AC02" "Antimycotics for systemic use" "Triazole derivatives" "itra" "c(\"itraconazol\", \"itraconazole\", \"itraconazolum\", \"itraconzaole\", \"itrazole\", \"oriconazole\", \"sporanox\")" 0.2 "g" 0.2 "g" "c(\"10989-2\", \"12392-7\", \"25258-5\", \"27081-9\", \"32184-4\", \"32185-1\", \"80531-7\")"
|
||||
"JOS" 5282165 "Josamycin" "Macrolides/lincosamides" "J01FA07" "Macrolides, lincosamides and streptogramins" "Macrolides" "" "c(\"josacine\", \"josamicina\", \"josamycin\", \"josamycine\", \"josamycinum\")" 2 "g" "character(0)"
|
||||
"KAN" 6032 "Kanamycin" "Aminoglycosides" "c(\"A07AA08\", \"J01GB04\", \"S01AA24\")" "Aminoglycoside antibacterials" "Other aminoglycosides" "c(\"hlk\", \"k\", \"kan\", \"kana\", \"km\")" "c(\"kanamicina\", \"kanamycin\", \"kanamycin a\", \"kanamycin base\", \"kanamycine\", \"kanamycinum\", \"kantrex\", \"kenamycin a\", \"klebcil\", \"liposomal kanamycin\")" 3 "g" 1 "g" "c(\"23889-9\", \"3698-8\", \"3699-6\", \"3700-2\", \"47395-9\")"
|
||||
"KAH" "Kanamycin-high" "Aminoglycosides" "c(\"\", \"k_h\", \"kahl\")" "" ""
|
||||
"KAC" "Kanamycin/cephalexin" "Aminoglycosides" "" "" ""
|
||||
"KET" 456201 "Ketoconazole" "Antifungals/antimycotics" "c(\"D01AC08\", \"G01AF11\", \"H02CA03\", \"J02AB02\")" "Antimycotics for systemic use" "Imidazole derivatives" "c(\"keto\", \"ktc\")" "c(\"extina\", \"fungarest\", \"fungoral\", \"ketocanazole\", \"ketoconazol\", \"ketoconazole\", \"ketoconazolum\", \"ketoderm\", \"nizoral\", \"xolegel\")" 0.2 "g" "c(\"10990-0\", \"12393-5\", \"25259-3\", \"60091-6\", \"60092-4\")"
|
||||
"KIT" "Kitasamycin" "Macrolides/lincosamides" "c(\"\", \"leucomycin\")" "" ""
|
||||
"LAS" 5360807 "Lasalocid" "Other antibacterials" "" "c(\"avatec\", \"lasalocid\", \"lasalocid a\", \"lasalocide\", \"lasalocide a\", \"lasalocido\", \"lasalocidum\")" "87598-9"
|
||||
"LTM" 47499 "Latamoxef" "Cephalosporins (3rd gen.)" "J01DD06" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"mox\", \"moxa\", \"moxalactam\")" "c(\"disodium moxalactam\", \"festamoxin\", \"lamoxactam\", \"latamoxef\", \"latamoxefum\", \"shiomarin\")" 4 "g" "character(0)"
|
||||
"LMU" 25185057 "Lefamulin" "Other antibacterials" "J01XX12" "" "lefamulin" "character(0)"
|
||||
"LEN" 65646 "Lenampicillin" "Beta-lactams/penicillins" "" "c(\"lenampicilina\", \"lenampicillin\", \"lenampicillin hcl\", \"lenampicilline\", \"lenampicillinum\")" "character(0)"
|
||||
"LVX" 149096 "Levofloxacin" "Quinolones" "c(\"J01MA12\", \"S01AE05\")" "Quinolone antibacterials" "Fluoroquinolones" "c(\"le\", \"lev\", \"levo\", \"lvx\")" "c(\"aeroquin\", \"cravit\", \"cravit hydrate\", \"cravit iv\", \"cravit ophthalmic\", \"elequine\", \"floxacin\", \"floxel\", \"iquix hydrate\", \"leroxacin\", \"lesacin\", \"levaquin\", \"levaquin hydrate\", \"levo floxacin\", \"levofiexacin\", \"levofloxacin\", \"levofloxacin hydrate\", \"levofloxacine\", \"levofloxacino\", \"levofloxacinum\", \"levokacin\", \"levoxacin\", \"mosardal\", \"nofaxin\", \"oftaquix\", \"quixin\", \"reskuin\", \"tavanic\", \"unibiotic\", \"venaxan\", \"volequin\")" 0.5 "g" 0.5 "g" "c(\"21368-6\", \"30532-6\", \"30533-4\")"
|
||||
"LND" 9850038 "Levonadifloxacin" "Quinolones" "J01MA24" "" "levonadifloxacin" "character(0)"
|
||||
"LSP" "Linco-spectin" "Other antibacterials" "c(\"\", \"lincomycin/spectinomycin\")" "" ""
|
||||
"LIN" 3000540 "Lincomycin" "Macrolides/lincosamides" "J01FF02" "Macrolides, lincosamides and streptogramins" "Lincosamides" "linc" "c(\"cillimycin\", \"jiemycin\", \"lincolcina\", \"lincolnensin\", \"lincomicina\", \"lincomycin\", \"lincomycin a\", \"lincomycine\", \"lincomycinum\")" 1.8 "g" 1.8 "g" "87597-1"
|
||||
"LNZ" 441401 "Linezolid" "Oxazolidinones" "J01XX08" "Other antibacterials" "Other antibacterials" "c(\"line\", \"lnz\", \"lz\", \"lzd\")" "c(\"linezlid\", \"linezoid\", \"linezolid\", \"linezolide\", \"linezolidum\", \"zivoxid\", \"zyvoxa\", \"zyvoxam\", \"zyvoxid\")" 1.2 "g" 1.2 "g" "c(\"34202-2\", \"80609-1\")"
|
||||
"LFE" "Linoprist-flopristin" "Other antibacterials" "" "" ""
|
||||
"LOM" 3948 "Lomefloxacin" "Quinolones" "c(\"J01MA07\", \"S01AE04\")" "Quinolone antibacterials" "Fluoroquinolones" "c(\"lmf\", \"lom\", \"lome\")" "c(\"lomefloxacin\", \"lomefloxacine\", \"lomefloxacino\", \"lomefloxacinum\", \"maxaquin\")" 0.4 "g" "character(0)"
|
||||
"LOR" 5284585 "Loracarbef" "Cephalosporins (2nd gen.)" "J01DC08" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "c(\"\", \"lora\")" "c(\"anhydrous loracarbef\", \"lorabid\", \"loracarbef\", \"loracarbefum\", \"lorbef\", \"loribid\")" 0.6 "g" "character(0)"
|
||||
"LYM" 54707177 "Lymecycline" "Tetracyclines" "J01AA04" "Tetracyclines" "Tetracyclines" "" "c(\"biovetin\", \"chlortetracyclin\", \"ciclisin\", \"ciclolysal\", \"infaciclina\", \"limeciclina\", \"lisinbiotic\", \"lymecyclin\", \"lymecycline\", \"lymecyclinum\", \"mucomycin\", \"ntetracycline\", \"tetralisal\", \"tetralysal\", \"vebicyclysal\")" 0.6 "g" 0.6 "g" "character(0)"
|
||||
"MNA" 1292 "Mandelic acid" "Other antibacterials" "c(\"B05CA06\", \"J01XX06\")" "Other antibacterials" "Other antibacterials" "" "c(\"acido mandelico\", \"almond acid\", \"amygdalic acid\", \"benzoglycolic acid\", \"hydroxyacetic acid\", \"kyselina mandlova\", \"mandelic acid\", \"paramandelic acid\", \"phenylglycolic acid\", \"uromaline\")" 12 "g" "character(0)"
|
||||
"MGX" "Manogepix" "Antifungals" "" "" ""
|
||||
"MAR" 60651 "Marbofloxacin" "Quinolones" "" "c(\"marbocyl\", \"marbofloxacin\", \"marbofloxacine\", \"marbofloxacino\", \"marbofloxacinum\", \"zeniquin\")" "character(0)"
|
||||
"MEC" 36273 "Mecillinam" "Beta-lactams/penicillins" "J01CA11" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "c(\"\", \"amdinocillin\")" "c(\"amdinocillin\", \"coactin\", \"hexacillin\", \"mecilinamo\", \"mecillinam\", \"mecillinamum\", \"micillinam\", \"penicillin hx\", \"selexidin\")" 1.2 "g" "character(0)"
|
||||
"MEL" 71306732 "Meleumycin" "Macrolides/lincosamides" "" "" ""
|
||||
"MEM" 441130 "Meropenem" "Carbapenems" "J01DH02" "Other beta-lactam antibacterials" "Carbapenems" "c(\"mem\", \"mer\", \"mero\", \"mp\", \"mrp\")" "c(\"meronem\", \"meropen\", \"meropenem\", \"meropenem anhydrous\", \"meropenem hydrate\", \"meropenem trihydrate\", \"meropenemum\", \"merrem\", \"merrem i.v.\", \"merrem iv\")" 3 "g" "41406-0"
|
||||
"MNC" "Meropenem/nacubactam" "Carbapenems" "" "" ""
|
||||
"MEV" "Meropenem/vaborbactam" "Carbapenems" "J01DH52" "Other beta-lactam antibacterials" "Carbapenems" "" "" 3 "g" ""
|
||||
"MES" 176886 "Mesulfamide" "Other antibacterials" "" "c(\"mesulfamide\", \"mesulfamido\", \"mesulfamidum\")" "character(0)"
|
||||
"MTC" 54675785 "Metacycline" "Tetracyclines" "J01AA05" "Tetracyclines" "Tetracyclines" "" "c(\"bialatan\", \"metaciclina\", \"metacycline\", \"metacyclinum\", \"methacycline\", \"methacycline base\", \"methacyclinum\", \"methylenecycline\", \"physiomycine\", \"rondomycin\")" 0.6 "g" "character(0)"
|
||||
"MTM" 6713928 "Metampicillin" "Beta-lactams/penicillins" "J01CA14" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"blomopen\", \"bonopen\", \"celinmicina\", \"elatocilline\", \"fedacilina kapseln\", \"filorex\", \"italcina kapseln\", \"magnipen\", \"metabacter ampullen\", \"metambac\", \"metampicilina\", \"metampicillin\", \"metampicillin sodium\", \"metampicillina\", \"metampicilline\", \"metampicillinum\", \"methampicillin\", \"metiskia ampullen\", \"micinovo\", \"micinovo ampullen\", \"pangocilin\", \"probiotic\", \"rastomycin k\", \"relyothenate\", \"ruticina\", \"rutizina\", \"rutizina ampullen\", \"sedomycin\", \"suvipen\", \"suvipen ampullen\", \"tampilen ampullen\",
|
||||
\"teonicon trofen\", \"viderpen\", \"viderpin\", \"vioplex\")" 1.5 "g" 1.5 "g" "character(0)"
|
||||
"MTH" 4101 "Methenamine" "Other antibacterials" "J01XX05" "Other antibacterials" "Other antibacterials" "" "c(\"aceto hmt\", \"aminoform\", \"aminoformaldehyde\", \"ammoform\", \"ammonioformaldehyde\", \"antihydral\", \"cystamin\", \"cystex\", \"cystogen\", \"duirexol\", \"ekagom h\", \"esametilentetramina\", \"formamine\", \"formin\", \"h.m.t.\", \"heksa k\", \"herax uts\", \"heterin\", \"hexa b\", \"hexaform\", \"hexaloids\", \"hexamethylamine\", \"hexamethylenamine\", \"hexamethyleneamine\", \"hexamethylentetramin\", \"hexamine\", \"hexamine silver\", \"hexamine superfine\", \"hexaminum\", \"hexasan\", \"hexilmethylenamine\", \"metenamina\", \"metenamine\", \"methamin\",
|
||||
\"methenamin\", \"methenamine\", \"methenamine silver\", \"methenaminum\", \"metramine\", \"naphthamine\", \"nocceler h\", \"preparation af\", \"resotropin\", \"sanceler h\", \"sanceler ht\", \"silver methenamine\", \"uramin\", \"uratrine\", \"urisol\", \"uritone\", \"urodeine\", \"urotropin\", \"urotropine\", \"vesaloin\", \"vesalvine\", \"xametrin\")" 3 "g" "character(0)"
|
||||
"MET" 6087 "Methicillin" "Beta-lactams/penicillins" "J01CF03" "Beta-lactam antibacterials, penicillins" "Beta-lactamase resistant penicillins" "meti" "c(\"dimocillin\", \"metacillin\", \"methcilline\", \"methicillin\", \"methicillinum\", \"methycillin\", \"meticilina\", \"meticillin\", \"meticillina\", \"meticilline\", \"meticillinum\", \"staphcillin\")" 4 "g" "c(\"29492-6\", \"3788-7\")"
|
||||
"MTP" 68590 "Metioprim" "Other antibacterials" "" "c(\"methioprim\", \"metioprim\", \"metioprima\", \"metioprime\", \"metioprimum\")" "character(0)"
|
||||
"MXT" 3047729 "Metioxate" "Quinolones" "" "c(\"metioxate\", \"metioxato\", \"metioxatum\")" "character(0)"
|
||||
"MTR" 4173 "Metronidazole" "Other antibacterials" "c(\"A01AB17\", \"D06BX01\", \"G01AF01\", \"J01XD01\", \"P01AB01\")" "Other antibacterials" "Imidazole derivatives" "c(\"metr\", \"mnz\")" "c(\"acromona\", \"anagiardil\", \"arilin\", \"atrivyl\", \"danizol\", \"deflamon\", \"efloran\", \"elyzol\", \"entizol\", \"flagemona\", \"flagesol\", \"flagil\", \"flagyl\", \"flagyl er\", \"flagyl i.v.\", \"flagyl i.v. rtu\", \"flazol\", \"flegyl\", \"florazole\", \"fossyol\", \"giatricol\", \"ginefla vir\", \"gineflavir\", \"helidac\", \"mepagyl\", \"meronidal\", \"methronidazole\", \"metric\", \"metro cream\", \"metro gel\", \"metro i.v\", \"metro i.v.\", \"metro iv\", \"metrocream\", \"metrodzhil\", \"metrogel\", \"metrogyl\", \"metrolag\", \"metrolotion\", \"metrolyl\",
|
||||
\"metromidol\", \"metronidaz\", \"metronidazol\", \"metronidazole\", \"metronidazole usp\", \"metronidazolo\", \"metronidazolum\", \"metrotop\", \"metrozine\", \"metryl\", \"mexibol\", \"mexibol 'silanes'\", \"monagyl\", \"monasin\", \"nidagel\", \"nidagyl\", \"noritate\", \"novonidazol\", \"orvagil\", \"polibiotic\", \"protostat\", \"rathimed\", \"rosased\", \"sanatrichom\", \"satric\", \"takimetol\", \"trichazol\", \"trichex\", \"tricho cordes\", \"trichobrol\", \"trichocide\", \"trichomol\", \"trichopal\", \"trichopol\", \"tricocet\", \"tricom\", \"tricowas b\", \"trikacide\",
|
||||
\"trikamon\", \"trikhopol\", \"trikojol\", \"trikozol\", \"trimeks\", \"trivazol\", \"vagilen\", \"vagimid\", \"vandazole\", \"vertisal\", \"wagitran\", \"zadstat\", \"zidoval\")" 2 "g" 1.5 "g" "10991-8"
|
||||
"MEZ" 656511 "Mezlocillin" "Beta-lactams/penicillins" "J01CA10" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "c(\"mez\", \"mezl\", \"mz\")" "c(\"mezlin\", \"mezlocilina\", \"mezlocillin\", \"mezlocillin acid\", \"mezlocillin sodium\", \"mezlocilline\", \"mezlocillinum\", \"multocillin\")" 6 "g" "3820-8"
|
||||
"MSU" "Mezlocillin/sulbactam" "Beta-lactams/penicillins" "" "" ""
|
||||
"MIF" 477468 "Micafungin" "Antifungals/antimycotics" "J02AX05" "Antimycotics for systemic use" "Other antimycotics for systemic use" "c(\"\", \"mica\")" "c(\"micafungin\", \"mycamine\")" 0.1 "g" "58418-5"
|
||||
"MCZ" 4189 "Miconazole" "Antifungals/antimycotics" "c(\"A01AB09\", \"A07AC01\", \"D01AC02\", \"G01AF04\", \"J02AB01\", \"S02AA13\")" "Antimycotics for systemic use" "Imidazole derivatives" "mico" "c(\"aflorix\", \"albistat\", \"andergin\", \"brentan\", \"conofite\", \"dactarin\", \"daktarin\", \"daktarin iv\", \"florid\", \"lotrimin af\", \"micantin\", \"miconasil nitrate\", \"miconazol\", \"miconazole\", \"miconazole base\", \"miconazolo\", \"miconazolum\", \"micozole\", \"minostate\", \"monista\", \"monistat\", \"monistat iv\", \"oravig\", \"vusion\", \"zimybase\", \"zimycan\")" 0.2 "g" 1 "g" "17278-3"
|
||||
"MCR" 3037206 "Micronomicin" "Aminoglycosides" "S01AA22" "" "c(\"gentamicin c\", \"micromycin\", \"micronomicin\", \"micronomicina\", \"micronomicine\", \"micronomicinum\", \"sagamicin\", \"santemycin\")" "character(0)"
|
||||
"MID" 5282169 "Midecamycin" "Macrolides/lincosamides" "J01FA03" "Macrolides, lincosamides and streptogramins" "Macrolides" "" "c(\"aboren\", \"espinomycin a\", \"macropen\", \"madecacine\", \"medemycin\", \"midecamicina\", \"midecamycin\", \"midecamycin a\", \"midecamycine\", \"midecamycinum\", \"midecin\", \"momicine\", \"mydecamycin\", \"myoxam\", \"normicina\", \"rubimycin\", \"turimycin p\")" 1.2 "g" 1 "g" "character(0)"
|
||||
"MIL" 37614 "Miloxacin" "Quinolones" "" "c(\"miloxacin\", \"miloxacine\", \"miloxacino\", \"miloxacinum\")" "character(0)"
|
||||
"MNO" 54675783 "Minocycline" "Tetracyclines" "c(\"A01AB23\", \"D10AF07\", \"J01AA08\")" "Tetracyclines" "Tetracyclines" "c(\"mc\", \"mh\", \"mi\", \"min\", \"mino\", \"mn\", \"mno\")" "c(\"akamin\", \"aknemin\", \"borymycin\", \"dynacin\", \"klinomycin\", \"minociclina\", \"minocin\", \"minocline\", \"minocyclin\", \"minocycline\", \"minocyclinum\", \"minocyn\", \"minoderm\", \"minomycin\", \"sebomin\", \"solodyn\", \"vectrin\")" 1 "mg" 0.2 "g" "c(\"34606-4\", \"3822-4\", \"49757-8\")"
|
||||
"MCM" 5282188 "Miocamycin" "Macrolides/lincosamides" "J01FA11" "Macrolides, lincosamides and streptogramins" "Macrolides" "" "c(\"acecamycin\", \"macroral\", \"midecamycin acetate\", \"miocamen\", \"miocamycine\", \"miokamycin\", \"myocamicin\", \"ponsinomycin\")" 1.2 "g" "character(0)"
|
||||
"MON" 23667299 "Monensin sodium" "Other antibacterials" "" "c(\"monensin sodium\", \"sodium monensin\")" "character(0)"
|
||||
"MRN" 70374 "Morinamide" "Antimycobacterials" "J04AK04" "Drugs for treatment of tuberculosis" "Other drugs for treatment of tuberculosis" "" "c(\"morfazinamide\", \"morfazinammide\", \"morfgazinamide\", \"morinamida\", \"morinamide\", \"morinamidum\", \"morphazinamid\", \"morphazinamide\", \"piazofolina\", \"piazolin\", \"piazolina\")" "character(0)"
|
||||
"MFX" 152946 "Moxifloxacin" "Quinolones" "c(\"J01MA14\", \"S01AE07\")" "Quinolone antibacterials" "Fluoroquinolones" "c(\"mox\", \"moxi\", \"mxf\")" "c(\"actira\", \"avelox\", \"avelox i.v.\", \"avelox iv\", \"avolex\", \"izilox\", \"moxeza\", \"moxifloxacin\", \"moxifloxacine\", \"vigamox\")" 0.4 "g" 0.4 "g" "c(\"43751-7\", \"45223-5\", \"80540-8\")"
|
||||
"MUP" 446596 "Mupirocin" "Other antibacterials" "c(\"D06AX09\", \"R01AX06\")" "c(\"mup\", \"mupi\")" "c(\"bactoderm\", \"bactroban\", \"bactroban nasal\", \"bactroban ointment\", \"centany\", \"mupirocin\", \"mupirocina\", \"mupirocine\", \"mupirocinum\", \"plasimine\", \"pseudomonic acid\", \"pseudomonic acid a\", \"turixin\")" "character(0)"
|
||||
"NAC" 73386748 "Nacubactam" "Beta-lactams/penicillins" "" "nacubactam" "character(0)"
|
||||
"NAD" 4410 "Nadifloxacin" "Quinolones" "D10AF05" "" "c(\"acuatim\", \"nadifloxacin\", \"nadifloxacine\", \"nadifloxacino\", \"nadifloxacinum\", \"nadixa\", \"nadoxin\")" "character(0)"
|
||||
"NAF" 8982 "Nafcillin" "Beta-lactams/penicillins" "J01CF06" "" "c(\"nafcilina\", \"nafcillin\", \"nafcillin sodium\", \"nafcilline\", \"nafcillinum\", \"nallpen\", \"naphcillin\", \"unipen\")" 3 "g" "c(\"10993-4\", \"25232-0\")"
|
||||
"ZWK" 117587595 "Nafithromycin" "Macrolides/lincosamides" "" "nafithromycin" "character(0)"
|
||||
"NAL" 4421 "Nalidixic acid" "Quinolones" "J01MB02" "Quinolone antibacterials" "Other quinolones" "c(\"na\", \"nal\", \"nali\")" "c(\"acide nalidixico\", \"acide nalidixique\", \"acido nalidissico\", \"acido nalidixico\", \"acidum nalidixicum\", \"betaxina\", \"dixiben\", \"dixinal\", \"eucisten\", \"eucistin\", \"innoxalomn\", \"innoxalon\", \"jicsron\", \"kusnarin\", \"naldixic acid\", \"nalidic acid\", \"nalidicron\", \"nalidixan\", \"nalidixane\", \"nalidixate\", \"nalidixate sodium\", \"nalidixic\", \"nalidixic acid\", \"nalidixin\", \"nalidixinic acid\", \"nalidixinsaure\", \"nalitucsan\", \"nalurin\", \"narigix\", \"naxuril\", \"neggram\", \"negram\", \"nevigramon\", \"nicelate\", \"nogram\",
|
||||
\"poleon\", \"sicmylon\", \"specifen\", \"specifin\", \"unaserus\", \"uralgin\", \"uriben\", \"uriclar\", \"urisal\", \"urodixin\", \"uroman\", \"uroneg\", \"uronidix\", \"uropan\", \"wintomylon\", \"wintron\")" 4 "g" "character(0)"
|
||||
"NAR" 65452 "Narasin" "Other antibacterials" "" "c(\"monteban\", \"narasin\", \"narasin a\", \"narasine\", \"narasino\", \"narasinum\", \"narasul\")" "87570-8"
|
||||
"NEO" 8378 "Neomycin" "Aminoglycosides" "c(\"A01AB08\", \"A07AA01\", \"B05CA09\", \"D06AX04\", \"J01GB05\", \"R02AB01\", \"S01AA03\", \"S02AA07\", \"S03AA01\")" "Aminoglycoside antibacterials" "Other aminoglycosides" "neom" "c(\"actilin\", \"actiline\", \"antibiotique\", \"bycomycin\", \"endomixin\", \"enterfram\", \"fradiomycin\", \"fradiomycin b\", \"fradiomycinum\", \"framicetina\", \"framycetin\", \"framycetin sulfate\", \"framycetine\", \"framycetinum\", \"framygen\", \"fraquinol\", \"jernadex\", \"myacine\", \"myacyne\", \"mycerin\", \"mycifradin\", \"neobrettin\", \"neolate\", \"neomas\", \"neomcin\", \"neomicina\", \"neomin\", \"neomycin\", \"neomycin b\", \"neomycin b sulfate\", \"neomycin solution\", \"neomycin sulfate\", \"neomycin sulphate\", \"neomycinb\", \"neomycine\", \"neomycinum\",
|
||||
\"nivemycin\", \"pimavecort\", \"soframycin\", \"soframycine\", \"tuttomycin\", \"vonamycin\", \"vonamycin powder v\")" 5 "g" "c(\"10995-9\", \"25262-7\")"
|
||||
"NET" 441306 "Netilmicin" "Aminoglycosides" "c(\"J01GB07\", \"S01AA23\")" "Aminoglycoside antibacterials" "Other aminoglycosides" "neti" "c(\"netillin\", \"netilmicin\", \"netilmicin sulfate\", \"netilmicina\", \"netilmicine\", \"netilmicinum\", \"netilyn\", \"netira\", \"vectacin\")" 0.35 "g" 0.35 "g" "c(\"25263-5\", \"3848-9\", \"3849-7\", \"3850-5\", \"47385-0\", \"59565-2\", \"59566-0\", \"59567-8\")"
|
||||
"NIC" 9507 "Nicarbazin" "Other antibacterials" "" "c(\"nicarb\", \"nicarbasin\", \"nicarbazin\", \"nicarbazine\", \"nicoxin\", \"nicrazin\", \"nicrazine\", \"nirazin\")" "character(0)"
|
||||
"NIF" 71946 "Nifuroquine" "Quinolones" "" "c(\"nifuroquina\", \"nifuroquine\", \"nifuroquinum\", \"quinaldofur\")" "character(0)"
|
||||
"NFR" 9571062 "Nifurtoinol" "Other antibacterials" "J01XE02" "Other antibacterials" "Nitrofuran derivatives" "" "c(\"levantin\", \"nifurtoinol\", \"nifurtoinolo\", \"nifurtoinolum\", \"urfadin\", \"urfadine\", \"urfadyn\")" 0.16 "g" "character(0)"
|
||||
"NTZ" 41684 "Nitazoxanide" "Other antibacterials" "P01AX11" "" "c(\"adrovet\", \"alinia\", \"azt + nitazoxanide\", \"colufase\", \"cryptaz\", \"dexidex\", \"heliton\", \"kidonax\", \"nitaxozanid\", \"nitaxozanide\", \"nitazox\", \"nitazoxamide\", \"nitazoxanid\", \"nitazoxanida\", \"nitazoxanide\", \"nitazoxanidum\", \"omniparax\", \"pacovanton\", \"paramix\", \"taenitaz\")" 1 "g" "character(0)"
|
||||
"NIT" 6604200 "Nitrofurantoin" "Other antibacterials" "J01XE01" "Other antibacterials" "Nitrofuran derivatives" "c(\"f\", \"f/m\", \"fd\", \"ft\", \"ni\", \"nit\", \"nitr\")" "c(\"alfuran\", \"benkfuran\", \"berkfuran\", \"berkfurin\", \"ceduran\", \"chemiofuran\", \"cistofuran\", \"cyantin\", \"cystit\", \"dantafur\", \"fua med\", \"fuamed\", \"furabid\", \"furachel\", \"furadantin\", \"furadantin retard\", \"furadantina mc\", \"furadantine\", \"furadantine mc\", \"furadantoin\", \"furadoin\", \"furadoine\", \"furadonin\", \"furadonine\", \"furadoninum\", \"furadontin\", \"furadoxyl\", \"furalan\", \"furaloid\", \"furantoin\", \"furantoina\", \"furatoin\", \"furedan\", \"furina\", \"furobactina\", \"furodantin\", \"furophen t\", \"gerofuran\",
|
||||
\"io>>uss>>a<<ixoo\", \"ituran\", \"ivadantin\", \"macpac\", \"macrobid\", \"macrodantin\", \"macrodantina\", \"macrofuran\", \"macrofurin\", \"nierofu\", \"nifurantin\", \"nifuretten\", \"nitoin\", \"nitrex\", \"nitrofuradantin\", \"nitrofurantion\", \"nitrofurantoin\", \"nitrofurantoin macro\", \"nitrofurantoina\", \"nitrofurantoine\", \"nitrofurantoinum\", \"novofuran\", \"orafuran\", \"parfuran\", \"phenurin\", \"piyeloseptyl\", \"siraliden\", \"trantoin\", \"uerineks\", \"urantoin\", \"urizept\", \"urodin\", \"urofuran\", \"urofurin\", \"urolisa\", \"urolong\",
|
||||
\"uvamin\", \"welfurin\", \"zoofurin\")" 0.2 "g" "3860-4"
|
||||
"NIZ" 5447130 "Nitrofurazone" "Other antibacterials" "" "c(\"acutol\", \"aldomycin\", \"alfucin\", \"amifur\", \"babrocid\", \"becafurazone\", \"biofuracina\", \"biofurea\", \"chemofuran\", \"chixin\", \"cocafurin\", \"coxistat\", \"dermofural\", \"dymazone\", \"dynazone\", \"eldezol\", \"fedacin\", \"flavazone\", \"fracine\", \"furacilin\", \"furacilinum\", \"furacillin\", \"furacin\", \"furacine\", \"furacinetten\", \"furacoccid\", \"furacort\", \"furacycline\", \"furaderm\", \"furagent\", \"furalcyn\", \"furaldon\", \"furalone\", \"furametral\", \"furaplast\", \"furaseptyl\", \"furaskin\", \"furatsilin\", \"furaziline\", \"furazin\",
|
||||
\"furazina\", \"furazol w\", \"furazone\", \"furazyme\", \"furesol\", \"furfurin\", \"furosem\", \"fuvacillin\", \"hemofuran\", \"ibiofural\", \"mammex\", \"mastofuran\", \"monafuracin\", \"monafuracis\", \"monofuracin\", \"nfz mix\", \"nifucin\", \"nifurid\", \"nifuzon\", \"nitrofural\", \"nitrofuralum\", \"nitrofuran\", \"nitrofurane\", \"nitrofurazan\", \"nitrofurazone\", \"nitrofurazonum\", \"nitrofurol\", \"nitrozone\", \"otofural\", \"otofuran\", \"rivafurazon\", \"sanfuran\", \"vabrocid\", \"vadrocid\", \"yatrocin\")" "character(0)"
|
||||
"NTR" 19910 "Nitroxoline" "Quinolones" "J01XX07" "Other antibacterials" "Other antibacterials" "" "c(\"galinok\", \"isinok\", \"nibiol\", \"nicene forte\", \"nitroxolin\", \"nitroxolina\", \"nitroxoline\", \"nitroxolinum\", \"notroxoline\", \"noxibiol\")" 1 "g" "character(0)"
|
||||
"NOR" 4539 "Norfloxacin" "Quinolones" "c(\"J01MA06\", \"S01AE02\")" "Quinolone antibacterials" "Fluoroquinolones" "c(\"nor\", \"norf\", \"nx\", \"nxn\")" "c(\"baccidal\", \"barazan\", \"chibroxin\", \"chibroxine\", \"chibroxol\", \"fulgram\", \"gonorcin\", \"lexinor\", \"nolicin\", \"noracin\", \"noraxin\", \"norflo\", \"norfloxacin\", \"norfloxacine\", \"norfloxacino\", \"norfloxacinum\", \"norocin\", \"noroxin\", \"noroxine\", \"norxacin\", \"sebercim\", \"uroxacin\", \"utinor\", \"zoroxin\")" 0.8 "g" "3867-9"
|
||||
"NVA" 10419027 "Norvancomycin" "Glycopeptides" "" "norvancomycin" "character(0)"
|
||||
"NOV" 54675769 "Novobiocin" "Other antibacterials" "novo" "c(\"albamix\", \"albamycin\", \"cardelmycin\", \"cathocin\", \"cathomycin\", \"crystallinic acid\", \"inamycin\", \"novobiocin\", \"novobiocina\", \"novobiocine\", \"novobiocinum\", \"robiocina\", \"sirbiocina\", \"spheromycin\", \"stilbiocina\", \"streptonivicin\")" "17378-1"
|
||||
"NYS" 6433272 "Nystatin" "Antifungals/antimycotics" "c(\"A07AA02\", \"D01AA01\", \"G01AA01\")" "nyst" "c(\"biofanal\", \"candex lotion\", \"comycin\", \"diastatin\", \"herniocid\", \"moronal\", \"myconystatin\", \"mycostatin\", \"mycostatin pastilles\", \"mykinac\", \"mykostatyna\", \"nilstat\", \"nistatin\", \"nistatina\", \"nyamyc\", \"nyotran\", \"nyotrantrade mark\", \"nystaform\", \"nystan\", \"nystatin\", \"nystatin a\", \"nystatin g\", \"nystatin lf\", \"nystatine\", \"nystatinum\", \"nystatyna\", \"nystavescent\", \"nystex\", \"nystop\", \"stamycin\", \"terrastatin\", \"zydin e\")" 1.5 "MU" "character(0)"
|
||||
"OFX" 4583 "Ofloxacin" "Quinolones" "c(\"J01MA01\", \"S01AE01\", \"S02AA16\")" "Quinolone antibacterials" "Fluoroquinolones" "c(\"of\", \"ofl\", \"oflo\", \"ofx\")" "c(\"bactocin\", \"danoflox\", \"effexin\", \"exocin\", \"exocine\", \"flobacin\", \"flodemex\", \"flotavid\", \"flovid\", \"floxal\", \"floxil\", \"floxin\", \"floxin otic\", \"floxstat\", \"fugacin\", \"inoflox\", \"kinflocin\", \"kinoxacin\", \"levofloxacin hcl\", \"liflox\", \"loxinter\", \"marfloxacin\", \"medofloxine\", \"mergexin\", \"monoflocet\", \"novecin\", \"nufafloqo\", \"occidal\", \"ocuflox\", \"oflocee\", \"oflocet\", \"oflocin\", \"oflodal\", \"oflodex\", \"oflodura\", \"ofloxacin\", \"ofloxacin otic\", \"ofloxacina\", \"ofloxacine\", \"ofloxacino\", \"ofloxacinum\",
|
||||
\"ofloxin\", \"onexacin\", \"operan\", \"orocin\", \"otonil\", \"oxaldin\", \"pharflox\", \"praxin\", \"puiritol\", \"qinolon\", \"quinolon\", \"quotavil\", \"sinflo\", \"tabrin\", \"taravid\", \"tariflox\", \"tarivid\", \"telbit\", \"tructum\", \"uro tarivid\", \"viotisone\", \"visiren\", \"zanocin\")" 0.4 "g" 0.4 "g" "c(\"25264-3\", \"3877-8\")"
|
||||
"OLE" 72493 "Oleandomycin" "Macrolides/lincosamides" "J01FA05" "Macrolides, lincosamides and streptogramins" "Macrolides" "" "c(\"amimycin\", \"landomycin\", \"matromycin\", \"oleandomycin a\", \"romicil\")" 1 "g" "character(0)"
|
||||
"OMC" 54697325 "Omadacycline" "Tetracyclines" "J01AA15" "" "c(\"amadacycline\", \"omadacycline\")" 0.3 "g" 0.1 "g" "character(0)"
|
||||
"OPT" 87880 "Optochin" "Other antibacterials" "" "c(\"numoquin\", \"optochin\", \"optoquine\")" "character(0)"
|
||||
"ORB" 60605 "Orbifloxacin" "Quinolones" "" "orbifloxacin" "character(0)"
|
||||
"ORI" 16136912 "Oritavancin" "Glycopeptides" "J01XA05" "Other antibacterials" "Glycopeptide antibacterials" "orit" "oritavancin" "character(0)"
|
||||
"ORS" "Ormetroprim/sulfamethoxazole" "Other antibacterials" "" "" ""
|
||||
"ORN" 28061 "Ornidazole" "Other antibacterials" "c(\"G01AF06\", \"J01XD03\", \"P01AB03\")" "Other antibacterials" "Imidazole derivatives" "" "c(\"madelen\", \"ornidal\", \"ornidazol\", \"ornidazole\", \"ornidazolum\", \"tiberal\")" 1.5 "g" 1 "g" "character(0)"
|
||||
"OXA" 6196 "Oxacillin" "Beta-lactams/penicillins" "J01CF04" "Beta-lactam antibacterials, penicillins" "Beta-lactamase resistant penicillins" "c(\"ox\", \"oxa\", \"oxac\", \"oxal\", \"oxs\")" "c(\"bactocill\", \"ossacillina\", \"oxacilina\", \"oxacillin\", \"oxacillin sodium\", \"oxacilline\", \"oxacillinum\", \"oxazocillin\", \"oxazocilline\", \"prostaphlin\", \"prostaphlyn\", \"sodium oxacillin\")" 2 "g" 2 "g" "c(\"25265-0\", \"3882-8\")"
|
||||
"OXO" 4628 "Oxolinic acid" "Quinolones" "J01MB05" "Quinolone antibacterials" "Other quinolones" "" "c(\"acide oxolinique\", \"acido ossolico\", \"acido oxolinico\", \"acidum oxolinicum\", \"aqualinic\", \"cistopax\", \"dioxacin\", \"emyrenil\", \"gramurin\", \"inoxyl\", \"nidantin\", \"oksaren\", \"orthurine\", \"ossian\", \"oxoboi\", \"oxolinic\", \"oxolinic acid\", \"pietil\", \"prodoxal\", \"prodoxol\", \"starner\", \"tiurasin\", \"ultibid\", \"urinox\", \"uritrate\", \"urotrate\", \"uroxol\", \"utibid\")" 1 "g" "character(0)"
|
||||
"OXY" 54675779 "Oxytetracycline" "Tetracyclines" "c(\"D06AA03\", \"G01AA07\", \"J01AA06\", \"S01AA04\")" "Tetracyclines" "Tetracyclines" "" "c(\"adamycin\", \"berkmycen\", \"biostat\", \"biostat pa\", \"dabicycline\", \"dalimycin\", \"embryostat\", \"fanterrin\", \"galsenomycin\", \"geomycin\", \"geotilin\", \"hydroxytetracyclinum\", \"imperacin\", \"lenocycline\", \"macocyn\", \"medamycin\", \"mepatar\", \"oksisyklin\", \"ossitetraciclina\", \"oxacycline\", \"oxitetraciclina\", \"oxitetracyclin\", \"oxitetracycline\", \"oxitetracyclinum\", \"oxydon\", \"oxymycin\", \"oxymykoin\", \"oxypam\", \"oxysteclin\", \"oxyterracin\", \"oxyterracine\", \"oxyterracyne\", \"oxytetracid\", \"oxytetracyclin\", \"oxytetracycline\",
|
||||
\"oxytetracycline base\", \"oxytetracyclinum\", \"proteroxyna\", \"riomitsin\", \"ryomycin\", \"solkaciclina\", \"stecsolin\", \"stevacin\", \"tarocyn\", \"tarosin\", \"teravit\", \"terrafungine\", \"terramitsin\", \"terramycin\", \"terramycin im\", \"tetran\", \"unimycin\", \"ursocyclin\", \"ursocycline\", \"vendarcin\")" 1 "g" 1 "g" "c(\"17396-3\", \"25266-8\", \"87595-5\")"
|
||||
"OZN" "Ozenoxacin" "" "" ""
|
||||
"PAS" 4649 "P-aminosalicylic acid" "Antimycobacterials" "" "c(\"aminopar\", \"aminosalicylic\", \"aminosalicylic acid\", \"aminosalyl\", \"aminox\", \"apacil\", \"deapasil\", \"entepas\", \"ferrosan\", \"gabbropas\", \"helipidyl\", \"hellipidyl\", \"neopasalate\", \"osacyl\", \"pamacyl\", \"pamisyl\", \"paramycin\", \"parasal\", \"parasalicil\", \"parasalindon\", \"pasalon\", \"pasara\", \"pascorbic\", \"pasdium\", \"paser granules\", \"paskalium\", \"pasmed\", \"pasnodia\", \"pasolac\", \"propasa\", \"rezipas\", \"teebacin\", \"wln: zr cq dvq\")" "character(0)"
|
||||
"PAN" 72015 "Panipenem" "Carbapenems" "" "c(\"panipenem\", \"panipenemum\", \"penipanem\")" "character(0)"
|
||||
"PAR" 165580 "Paromomycin" "Other antibacterials" "A07AA06" "" "c(\"aminosidin\", \"aminosidine\", \"aminosidine i\", \"aminosidine sulfate\", \"amminosidin\", \"crestomycin\", \"estomycin\", \"gabbromicina\", \"gabbromycin\", \"gabromycin\", \"humatin\", \"humycin\", \"hydroxymycin\", \"hydroxymycin sulfate\", \"monomycin\", \"monomycin a\", \"neomycin e\", \"paramomycin\", \"paramomycin sulfate\", \"paromomicina\", \"paromomycin\", \"paromomycin i\", \"paromomycine\", \"paromomycinum\", \"paucimycin\", \"paucimycinum\", \"quintomycin c\")" 3 "g" "character(0)"
|
||||
"PAZ" 65957 "Pazufloxacin" "Quinolones" "J01MA18" "Quinolone antibacterials" "Fluoroquinolones" "" "c(\"pazufloxacin\", \"pazufloxacine\", \"pazufloxacino\", \"pazufloxacinum\")" 1 "g" "character(0)"
|
||||
"PEF" 51081 "Pefloxacin" "Quinolones" "J01MA03" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"pefl\")" "c(\"abactal\", \"labocton\", \"pefloxacin\", \"pefloxacine\", \"pefloxacino\", \"pefloxacinum\", \"perfloxacin\", \"silver pefloxacin\")" 0.8 "g" 0.8 "g" "3906-5"
|
||||
"PNM" 10250769 "Penamecillin" "Beta-lactams/penicillins" "J01CE06" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "" "c(\"hydroxymethyl\", \"penamecilina\", \"penamecillin\", \"penamecillina\", \"penamecilline\", \"penamecillinum\")" 1.05 "g" "character(0)"
|
||||
"PNO" "Penicillin/novobiocin" "Beta-lactams/penicillins" "" "" ""
|
||||
"PSU" "Penicillin/sulbactam" "Beta-lactams/penicillins" "" "" ""
|
||||
"PNM1" 54686187 "Penimepicycline" "Tetracyclines" "J01AA10" "Tetracyclines" "Tetracyclines" "" "c(\"duamine\", \"hydrocycline\", \"penetracyne\", \"penimepiciclina\", \"penimepicycline\", \"penimepicyclinum\")" "character(0)"
|
||||
"PIM" 65453 "Pentisomicin" "Aminoglycosides" "" "c(\"pentisomicin\", \"pentisomicina\", \"pentisomicine\", \"pentisomicinum\")" "character(0)"
|
||||
"PTZ" 55250256 "Pentizidone" "Other antibacterials" "" "" ""
|
||||
"PEX" 16132253 "Pexiganan" "Other antibacterials" "" "pexiganan" "character(0)"
|
||||
"PHE" 272833 "Phenethicillin" "Beta-lactams/penicillins" "J01CE05" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "c(\"\", \"fene\")" "c(\"feneticilina\", \"feneticillina\", \"feneticilline\", \"k phenethicillin\", \"phenethicilin\", \"phenethicillinum\", \"pheneticillin\", \"pheneticilline\", \"pheneticillinum\", \"phenoxy pc\", \"potassium penicillin\")" 1 "g" "41471-4"
|
||||
"PHN" 6869 "Phenoxymethylpenicillin" "Beta-lactams/penicillins" "J01CE02" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "c(\"fepe\", \"peni v\", \"penicillin v\", \"pnv\", \"pv\")" "c(\"acipen v\", \"apocillin\", \"apopen\", \"beromycin\", \"calcipen\", \"compocillin v\", \"crystapen v\", \"distaquaine v\", \"eskacillian v\", \"eskacillin v\", \"fenacilin\", \"fenospen\", \"meropenin\", \"oracillin\", \"oratren\", \"penicillin v\", \"phenocillin\", \"phenomycilline\", \"phenopenicillin\", \"robicillin\", \"rocilin\", \"stabicillin\", \"vebecillin\", \"veetids\", \"vegacillin\")" 2 "g" "character(0)"
|
||||
"PMR" 5284447 "Pimaricin" "Antifungals/antimycotics" "c(\"\", \"natamycin\")" "c(\"delvocid\", \"mycophyt\", \"myprozine\", \"natacyn\", \"natamicina\", \"natamycin\", \"natamycine\", \"natamycinum\", \"pimafucin\", \"pimaracin\", \"pimarizin\", \"synogil\", \"tennecetin\")" "character(0)"
|
||||
"PPA" 4831 "Pipemidic acid" "Quinolones" "J01MB04" "Quinolone antibacterials" "Other quinolones" "c(\"pipz\", \"pizu\")" "c(\"acide pipemidique\", \"acido pipemidico\", \"acidum pipemidicum\", \"deblaston\", \"dolcol\", \"pipedac\", \"pipemid\", \"pipemidic\", \"pipemidic acid\", \"pipemidicacid\", \"pipram\", \"uromidin\")" 0.8 "g" "character(0)"
|
||||
"PIP" 43672 "Piperacillin" "Beta-lactams/penicillins" "J01CA12" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "c(\"pi\", \"pip\", \"pipc\", \"pipe\", \"pp\")" "c(\"isipen\", \"pentcillin\", \"peperacillin\", \"peracin\", \"piperacilina\", \"piperacillin\", \"piperacillin na\", \"piperacillin sodium\", \"piperacilline\", \"piperacillinum\", \"pipercillin\", \"pipracil\", \"pipril\")" 14 "g" "c(\"25268-4\", \"3972-7\")"
|
||||
"PIS" "Piperacillin/sulbactam" "Beta-lactams/penicillins" "" "" ""
|
||||
"TZP" 461573 "Piperacillin/tazobactam" "Beta-lactams/penicillins" "J01CR05" "Beta-lactam antibacterials, penicillins" "Combinations of penicillins, incl. beta-lactamase inhibitors" "c(\"p/t\", \"piptaz\", \"piptazo\", \"pit\", \"pita\", \"pt\", \"ptc\", \"ptz\", \"tzp\")" "c(\"\", \"tazocel\", \"tazocillin\", \"tazocin\", \"zosyn\")" 14 "g" "character(0)"
|
||||
"PRC" 71978 "Piridicillin" "Beta-lactams/penicillins" "" "piridicillin" "character(0)"
|
||||
"PRL" 157385 "Pirlimycin" "Macrolides/lincosamides" "" "c(\"pirlimycin\", \"pirlimycina\", \"pirlimycine\", \"pirlimycinum\", \"pirsue\")" "character(0)"
|
||||
"PIR" 4855 "Piromidic acid" "Quinolones" "J01MB03" "Quinolone antibacterials" "Other quinolones" "" "c(\"acide piromidique\", \"acido piromidico\", \"acidum piromidicum\", \"actrun c\", \"bactramyl\", \"enterol\", \"gastrurol\", \"panacid\", \"pirodal\", \"piromidic acid\", \"pyrido\", \"reelon\", \"septural\", \"urisept\", \"uropir\", \"zaomeal\")" 2 "g" "character(0)"
|
||||
"PVM" 33478 "Pivampicillin" "Beta-lactams/penicillins" "J01CA02" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"berocillin\", \"pivaloylampicillin\", \"pivampicilina\", \"pivampicillin\", \"pivampicilline\", \"pivampicillinum\", \"pondocillin\")" 1.05 "g" "character(0)"
|
||||
"PME" 115163 "Pivmecillinam" "Beta-lactams/penicillins" "J01CA08" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"amdinocillin pivoxil\", \"coactabs\", \"hydroxymethyl\", \"pivmecilinamo\", \"pivmecillinam\", \"pivmecillinam hcl\", \"pivmecillinamum\")" 0.6 "g" "character(0)"
|
||||
"PLZ" 42613186 "Plazomicin" "Aminoglycosides" "J01GB14" "" "plazomicin" "92024-9"
|
||||
"PLB" 49800004 "Polymyxin B" "Polymyxins" "c(\"A07AA05\", \"J01XB02\", \"S01AA18\", \"S02AA11\", \"S03AA03\")" "Other antibacterials" "Polymyxins" "c(\"pb\", \"pol\", \"polb\", \"poly\", \"poly b\", \"polymixin\", \"polymixin b\")" "c(\"polimixina b\", \"polumyxin b\", \"polymixin b\", \"polymyxine b\")" 3 "MU" 0.15 "g" "c(\"17473-0\", \"25269-2\")"
|
||||
"POP" "Polymyxin B/polysorbate 80" "Polymyxins" "" "" ""
|
||||
"POS" 468595 "Posaconazole" "Antifungals/antimycotics" "J02AC04" "Antimycotics for systemic use" "Triazole derivatives" "posa" "c(\"noxafil\", \"posaconazole\", \"posaconazole sp\", \"posconazole\")" 0.3 "g" 0.3 "g" "c(\"53731-6\", \"80545-7\")"
|
||||
"PRA" 9802884 "Pradofloxacin" "Quinolones" "" "pradofloxacin" "character(0)"
|
||||
"PRX" 71455 "Premafloxacin" "Quinolones" "" "premafloxacin" "character(0)"
|
||||
"PMD" 456199 "Pretomanid" "Antimycobacterials" "J04AK08" "Drugs for treatment of tuberculosis" "Other drugs for treatment of tuberculosis" "" "" ""
|
||||
"PRM" 6446787 "Primycin" "Macrolides/lincosamides" "" "" ""
|
||||
"PRI" 11979535 "Pristinamycin" "Macrolides/lincosamides" "J01FG01" "Macrolides, lincosamides and streptogramins" "Streptogramins" "c(\"\", \"pris\")" "c(\"eskalin v\", \"mikamycin\", \"mikamycine\", \"mikamycinum\", \"ostreogrycinum\", \"pristinamycine\", \"pristinamycinum\", \"stafac\", \"stafytracine\", \"staphylomycin\", \"starfac\", \"streptogramin\", \"vernamycin\", \"virgimycin\", \"virgimycine\", \"virginiamycina\", \"virginiamycine\", \"virginiamycinum\")" 2 "g" "character(0)"
|
||||
"PRB" 5903 "Procaine benzylpenicillin" "Beta-lactams/penicillins" "J01CE09" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "" "c(\"depocillin\", \"duphapen\", \"hostacillin\", \"hydracillin\", \"jenacillin o\", \"nopcaine\", \"penicillin procaine\", \"retardillin\", \"vetspen\", \"vitablend\")" 0.6 "g" "character(0)"
|
||||
"PRP" 92879 "Propicillin" "Beta-lactams/penicillins" "J01CE03" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "" "c(\"propicilina\", \"propicillin\", \"propicilline\", \"propicillinum\")" 0.9 "g" "character(0)"
|
||||
"PKA" 9872451 "Propikacin" "Aminoglycosides" "" "c(\"propikacin\", \"propikacina\", \"propikacine\", \"propikacinum\")" "character(0)"
|
||||
"PTH" 666418 "Prothionamide" "Antimycobacterials" "J04AD01" "Drugs for treatment of tuberculosis" "Thiocarbamide derivatives" "prot" "c(\"ektebin\", \"peteha\", \"prothionamide\", \"prothionamidum\", \"protion\", \"protionamid\", \"protionamida\", \"protionamide\", \"protionamidum\", \"protionizina\", \"tebeform\", \"trevintix\", \"tuberex\")" 0.75 "g" "character(0)"
|
||||
"PRU" 65947 "Prulifloxacin" "Quinolones" "J01MA17" "Quinolone antibacterials" "Fluoroquinolones" "" "c(\"prulifloxacin\", \"pruvel\", \"pufloxacin dioxolil\", \"quisnon\")" 0.6 "g" "character(0)"
|
||||
"PZA" 1046 "Pyrazinamide" "Antimycobacterials" "J04AK01" "Drugs for treatment of tuberculosis" "Other drugs for treatment of tuberculosis" "pyra" "c(\"aldinamid\", \"aldinamide\", \"braccopiral\", \"corsazinmid\", \"dipimide\", \"eprazin\", \"farmizina\", \"isopas\", \"lynamide\", \"novamid\", \"p ezetamid\", \"pezetamid\", \"pharozinamide\", \"piraldina\", \"pirazimida\", \"pirazinamid\", \"pirazinamida\", \"pirazinamide\", \"prazina\", \"pyrafat\", \"pyramide\", \"pyrazide\", \"pyrazinamdie\", \"pyrazinamid\", \"pyrazinamide\", \"pyrazinamidum\", \"pyrazine carboxamide\", \"pyrazineamide\", \"pyrizinamide\", \"rifafour\", \"rozide\", \"tebrazid\", \"tebrazio\", \"tisamid\", \"unipyranamide\", \"zinamide\", \"zinastat\"
|
||||
)" 1.5 "g" "c(\"11001-5\", \"25270-0\")"
|
||||
"QDA" 11979418 "Quinupristin/dalfopristin" "Macrolides/lincosamides" "J01FG02" "Macrolides, lincosamides and streptogramins" "Streptogramins" "c(\"q/d\", \"qda\", \"qida\", \"quda\", \"rp\", \"syn\")" "" 1.5 "g" ""
|
||||
"RAC" 56052 "Ractopamine" "Other antibacterials" "" "c(\"ractopamina\", \"ractopamine\", \"ractopaminum\")" "character(0)"
|
||||
"RAM" 16132338 "Ramoplanin" "Glycopeptides" "" "ramoplanin" "character(0)"
|
||||
"RZM" 10993211 "Razupenem" "Carbapenems" "" "razupenem" "character(0)"
|
||||
"RTP" 6918462 "Retapamulin" "Other antibacterials" "D06AX13" "Antibiotics for topical use" "Other antibiotics for topical use" "c(\"\", \"ret\")" "c(\"altabax\", \"altargo\", \"retapamulin\")" "character(0)"
|
||||
"RZF" "Rezafungin" "Antifungals" "" "" ""
|
||||
"RBC" 44631912 "Ribociclib" "Antifungals/antimycotics" "L01EF02" "Antimycotics for systemic use" "Triazole derivatives" "ribo" "c(\"kisqali\", \"ribociclib\")" "character(0)"
|
||||
"RST" 33042 "Ribostamycin" "Aminoglycosides" "J01GB10" "Aminoglycoside antibacterials" "Other aminoglycosides" "" "c(\"dekamycin iv\", \"hetangmycin\", \"ribastamin\", \"ribostamicina\", \"ribostamycin\", \"ribostamycine\", \"ribostamycinum\", \"vistamycin\", \"xylostatin\")" 1 "g" "character(0)"
|
||||
"RID1" 16659285 "Ridinilazole" "Other antibacterials" "" "ridinilazole" "character(0)"
|
||||
"RIB" 135398743 "Rifabutin" "Antimycobacterials" "J04AB04" "Drugs for treatment of tuberculosis" "Antibiotics" "rifb" "c(\"alfacid\", \"ansamicin\", \"ansamycin\", \"ansatipin\", \"ansatipine\", \"mycobutin\", \"rifabutin\", \"rifabutina\", \"rifabutine\", \"rifabutinum\")" 0.15 "g" "24032-5"
|
||||
"RIF" 135398735 "Rifampicin" "Antimycobacterials" "J04AB02" "Drugs for treatment of tuberculosis" "Antibiotics" "rifa" "c(\"abrifam\", \"archidyn\", \"arficin\", \"arzide\", \"azt + rifampin\", \"benemicin\", \"benemycin\", \"dipicin\", \"doloresum\", \"eremfat\", \"famcin\", \"fenampicin\", \"rifadin\", \"rifadin i.v\", \"rifadin i.v.\", \"rifadine\", \"rifagen\", \"rifaldazin\", \"rifaldazine\", \"rifaldin\", \"rifamate\", \"rifamicin amp\", \"rifamor\", \"rifampicin\", \"rifampicin sv\", \"rifampicina\", \"rifampicine\", \"rifampicinum\", \"rifampin\", \"rifamsolin\", \"rifamycin amp\", \"rifaprodin\", \"rifcin\", \"rifobac\", \"rifoldin\", \"rifoldine\", \"riforal\", \"rimactan\", \"rimactane\",
|
||||
\"rimactizid\", \"rimazid\", \"rimycin\", \"sinerdol\", \"tubocin\")" 0.6 "g" 0.6 "g" "character(0)"
|
||||
"RFI" "Rifampicin/isoniazid" "Antimycobacterials" "J04AM02" "Drugs for treatment of tuberculosis" "Combinations of drugs for treatment of tuberculosis" "" "c(\"rifinah\", \"rimactazid\")" "character(0)"
|
||||
"RPEI" "Rifampicin/pyrazinamide/ethambutol/isoniazid" "Antimycobacterials" "J04AM06" "Drugs for treatment of tuberculosis" "Combinations of drugs for treatment of tuberculosis" "" "" ""
|
||||
"RPI" "Rifampicin/pyrazinamide/isoniazid" "Antimycobacterials" "J04AM05" "Drugs for treatment of tuberculosis" "Combinations of drugs for treatment of tuberculosis" "" "" ""
|
||||
"RFM" 6324616 "Rifamycin" "Antimycobacterials" "c(\"A07AA13\", \"D06AX15\", \"J04AB03\", \"S01AA16\", \"S02AA12\")" "Drugs for treatment of tuberculosis" "Antibiotics" "" "c(\"aemcolo\", \"rifacin\", \"rifamicina\", \"rifamicine sv\", \"rifamycin\", \"rifamycine\", \"rifamycinum\", \"rifocin\", \"rifocyn\", \"rifomycin\", \"rifomycin sv\", \"tuborin\")" 0.6 "g" "character(0)"
|
||||
"RFP" 135403821 "Rifapentine" "Antimycobacterials" "J04AB05" "Drugs for treatment of tuberculosis" "Antibiotics" "c(\"rifp\", \"rpt\")" "c(\"cyclopentyl rifampin\", \"priftin\", \"rifapentin\", \"rifapentina\", \"rifapentine\", \"rifapentinum\")" 0.11 "g" "character(0)"
|
||||
"RFX" 6436173 "Rifaximin" "Other antibacterials" "c(\"A07AA11\", \"D06AX11\")" "Intestinal antiinfectives" "Antibiotics" "" "c(\"fatroximin\", \"flonorm\", \"lormyx\", \"lumenax\", \"normix\", \"redactiv\", \"rifacol\", \"rifamixin\", \"rifaxidin\", \"rifaximin\", \"rifaximina\", \"rifaximine\", \"rifaximinum\", \"rifaxin\", \"ritacol\", \"spiraxin\", \"xifaxan\", \"xifaxsan\")" 0.6 "g" "character(0)"
|
||||
"RIT" 65633 "Ritipenem" "Carbapenems" "" "ritipenem" "character(0)"
|
||||
"RIA" 163692 "Ritipenem acoxil" "Carbapenems" "" "ritipenem acoxil" "character(0)"
|
||||
"ROK" 5282211 "Rokitamycin" "Macrolides/lincosamides" "J01FA12" "Macrolides, lincosamides and streptogramins" "Macrolides" "" "c(\"propionylleucomycin\", \"ricamycin\", \"rokicid\", \"rokital\", \"rokitamicina\", \"rokitamycin\", \"rokitamycine\", \"rokitamycinum\")" 0.8 "g" "character(0)"
|
||||
"RLT" 54682938 "Rolitetracycline" "Tetracyclines" "J01AA09" "Tetracyclines" "Tetracyclines" "" "c(\"bristacin\", \"kinteto\", \"reverin\", \"rolitetraciclina\", \"rolitetracycline\", \"rolitetracyclinum\", \"solvocillin\", \"superciclin\", \"synotodecin\", \"synterin\", \"syntetrex\", \"syntetrin\", \"velacicline\", \"velacycline\")" 0.35 "g" "character(0)"
|
||||
"ROS" 287180 "Rosoxacin" "Quinolones" "J01MB01" "Quinolone antibacterials" "Other quinolones" "" "c(\"acrosoxacin\", \"eracine\", \"eradacil\", \"eradacin\", \"rosoxacin\", \"rosoxacine\", \"rosoxacino\", \"rosoxacinum\", \"roxadyl\", \"winuron\")" 0.3 "g" "character(0)"
|
||||
"RXT" "Roxithromycin" "Macrolides/lincosamides" "J01FA06" "Macrolides, lincosamides and streptogramins" "Macrolides" "roxi" "" 0.3 "g" ""
|
||||
"RFL" 58258 "Rufloxacin" "Quinolones" "J01MA10" "Quinolone antibacterials" "Fluoroquinolones" "" "c(\"rufloxacin\", \"rufloxacin hcl\", \"rufloxacine\", \"rufloxacino\", \"rufloxacinum\")" 0.2 "g" "character(0)"
|
||||
"SAL" 3085092 "Salinomycin" "Other antibacterials" "" "c(\"coxistac\", \"procoxacin\", \"salinomicina\", \"salinomycin\", \"salinomycine\", \"salinomycinum\")" "87593-0"
|
||||
"SAR" 56208 "Sarafloxacin" "Quinolones" "" "c(\"difloxacine\", \"difloxacino\", \"difloxacinum\", \"saraflox\", \"sarafloxacin\", \"sarafloxacine\", \"sarafloxacino\", \"sarafloxacinum\")" "character(0)"
|
||||
"SRX" 9933415 "Sarmoxicillin" "Beta-lactams/penicillins" "" "sarmoxicillin" "character(0)"
|
||||
"SEC" 71815 "Secnidazole" "Other antibacterials" "P01AB07" "" "c(\"flagentyl\", \"secnidal\", \"secnidazol\", \"secnidazole\", \"secnidazolum\", \"secnil\", \"sindose\", \"solosec\")" 2 "g" "character(0)"
|
||||
"SMF" "Simvastatin/fenofibrate" "Antimycobacterials" "C10BA04" "Drugs for treatment of tuberculosis" "Other drugs for treatment of tuberculosis" "simv" "" ""
|
||||
"SIS" 36119 "Sisomicin" "Aminoglycosides" "J01GB08" "Aminoglycoside antibacterials" "Other aminoglycosides" "siso" "c(\"rickamicin\", \"salvamina\", \"siseptin sulfate\", \"sisomicin\", \"sisomicin sulfate\", \"sisomicina\", \"sisomicine\", \"sisomicinum\", \"sisomin\", \"sisomycin\", \"sissomicin\", \"sizomycin\")" 0.24 "g" "character(0)"
|
||||
"SIT" 461399 "Sitafloxacin" "Quinolones" "J01MA21" "" "c(\"gracevit\", \"sitafloxacinisomer\")" 0.1 "g" "character(0)"
|
||||
"SDA" 2724368 "Sodium aminosalicylate" "Antimycobacterials" "J04AA02" "Drugs for treatment of tuberculosis" "Aminosalicylic acid and derivatives" "" "c(\"bactylan\", \"decapasil\", \"lepasen\", \"monopas\", \"nippas\", \"p.a.s. sodium\", \"pamisyl sodium\", \"parasal sodium\", \"pas sodium\", \"pasade\", \"pasnal\", \"passodico\", \"salvis\", \"sanipirol\", \"sodiopas\", \"sodium p.a.s\", \"sodium pas\", \"teebacin\", \"tubersan\")" 14 "g" 14 "g" "character(0)"
|
||||
"SOL" 25242512 "Solithromycin" "Macrolides/lincosamides" "J01FA16" "" "" ""
|
||||
"SPX" 60464 "Sparfloxacin" "Quinolones" "J01MA09" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"spa\", \"spar\")" "c(\"esparfloxacino\", \"sparfloxacin\", \"sparfloxacine\", \"sparfloxacinum\")" 0.2 "g" "character(0)"
|
||||
"SPT" 15541 "Spectinomycin" "Other antibacterials" "J01XX04" "Other antibacterials" "Other antibacterials" "c(\"sc\", \"spe\", \"spec\", \"spt\")" "c(\"actinospectacina\", \"adspec\", \"espectinomicina\", \"prospec\", \"specitinomycin\", \"spectam\", \"spectinomicina\", \"spectinomycin\", \"spectinomycin di hcl\", \"spectinomycine\", \"spectinomycinum\", \"stanilo\", \"togamycin\", \"trobicin\")" 3 "g" "character(0)"
|
||||
"SPI" 6419898 "Spiramycin" "Macrolides/lincosamides" "J01FA02" "Macrolides, lincosamides and streptogramins" "Macrolides" "c(\"\", \"spir\")" "c(\"espiramicin\", \"provamycin\", \"rovamycin\", \"rovamycine\", \"sequamycin\", \"spiramycine\", \"spiramycinum\")" 3 "g" "character(0)"
|
||||
"SPM" "Spiramycin/metronidazole" "Other antibacterials" "J01RA04" "Combinations of antibacterials" "Combinations of antibacterials" "" "" ""
|
||||
"STR" "Streptoduocin" "Aminoglycosides" "J01GA02" "Aminoglycoside antibacterials" "Streptomycins" "" "" 1 "g" ""
|
||||
"STR1" 19649 "Streptomycin" "Aminoglycosides" "c(\"A07AA04\", \"J01GA01\")" "Aminoglycoside antibacterials" "Streptomycins" "c(\"s\", \"stm\", \"str\", \"stre\")" "c(\"agrept\", \"agrimycin\", \"chemform\", \"estreptomicina\", \"neodiestreptopab\", \"strepcen\", \"streptomicina\", \"streptomycin\", \"streptomycin a\", \"streptomycin spx\", \"streptomycin sulfate\", \"streptomycine\", \"streptomyzin\", \"vetstrep\")" 1 "g" "4039-4"
|
||||
"STH" "Streptomycin-high" "Aminoglycosides" "c(\"sthi\", \"sthl\", \"strepto high\", \"streptomycin high\")" "" ""
|
||||
"STI" "Streptomycin/isoniazid" "Antimycobacterials" "J04AM01" "Drugs for treatment of tuberculosis" "Combinations of drugs for treatment of tuberculosis" "" "" ""
|
||||
"SUL" 130313 "Sulbactam" "Beta-lactams/penicillins" "J01CG01" "Beta-lactam antibacterials, penicillins" "Beta-lactamase inhibitors" "" "c(\"betamaze\", \"sulbactam\", \"sulbactam acid\", \"sulbactam free acid\", \"sulbactamum\")" 1 "g" "character(0)"
|
||||
"SBC" 20055036 "Sulbenicillin" "Beta-lactams/penicillins" "J01CA16" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"kedacillina\", \"sulbenicilina\", \"sulbenicilline\", \"sulbenicillinum\")" 15 "g" "character(0)"
|
||||
"SUC" 5318 "Sulconazole" "Antifungals/antimycotics" "D01AC09" "" "c(\"sulconazol\", \"sulconazole\", \"sulconazolum\")" "character(0)"
|
||||
"SUP" 6634 "Sulfachlorpyridazine" "Other antibacterials" "" "c(\"cluricol\", \"cosulid\", \"cosumix\", \"durasulf\", \"nefrosul\", \"nsulfanilamide\", \"prinzone vet\", \"prinzone vet.\", \"solfaclorpiridazina\", \"sonilyn\", \"sulfachlorpyridazine\", \"sulfacloropiridazina\", \"vetisulid\")" "character(0)"
|
||||
"SDI" 5215 "Sulfadiazine" "Trimethoprims" "J01EC02" "Sulfonamides and trimethoprim" "Intermediate-acting sulfonamides" "" "c(\"adiazin\", \"adiazine\", \"cocodiazine\", \"codiazine\", \"cremodiazine\", \"cremotres\", \"debenal\", \"deltazina\", \"diazin\", \"diazolone\", \"diazovit\", \"diazyl\", \"eskadiazine\", \"honey diazine\", \"liquadiazine\", \"microsulfon\", \"neazine\", \"neotrizine\", \"nsulfanilamide\", \"palatrize\", \"piridisir\", \"pirimal\", \"pyrimal\", \"quadetts\", \"quadramoid\", \"sanodiazine\", \"sildaflo\", \"silvadene\", \"solfadiazina\", \"spofadrizine\", \"sterazine\", \"sulfacombin\", \"sulfadiazene\", \"sulfadiazin\", \"sulfadiazina\", \"sulfadiazine\", \"sulfadiazinum\",
|
||||
\"sulfapirimidin\", \"sulfapyrimidin\", \"sulfapyrimidine\", \"sulfatryl\", \"sulfazine\", \"sulfolex\", \"sulfonamides duplex\", \"sulfonsol\", \"sulfose\", \"sulphadiazine\", \"sulphadiazine e\", \"terfonyl\", \"theradiazine\", \"thermazene\", \"trifonamide\", \"triple sulfa\", \"triple sulfas\", \"trisem\", \"truozine\", \"zinc sulfadiazine\")" 0.6 "g" "c(\"27216-1\", \"59742-7\", \"6907-0\")"
|
||||
"SLT" 122284 "Sulfadiazine/tetroxoprim" "Trimethoprims" "J01EE06" "Sulfonamides and trimethoprim" "Combinations of sulfonamides and trimethoprim, incl. derivatives" "" "" ""
|
||||
"SLT1" 64932 "Sulfadiazine/trimethoprim" "Trimethoprims" "J01EE02" "Sulfonamides and trimethoprim" "Combinations of sulfonamides and trimethoprim, incl. derivatives" "" "c(\"antastmon\", \"cotrimazine\", \"diaziprim forte\", \"ditrim\", \"ditrivet\", \"sultrisan\", \"triglobe\", \"trimin\", \"tucoprim\", \"uniprim\")" "character(0)"
|
||||
"SUD" 5323 "Sulfadimethoxine" "Trimethoprims" "J01ED01" "Sulfonamides and trimethoprim" "Long-acting sulfonamides" "" "c(\"agribon\", \"arnosulfan\", \"bactrovet\", \"deposul\", \"diasulfa\", \"diasulfyl\", \"dimetazina\", \"dinosol\", \"dorisul\", \"lasibon\", \"madribon\", \"madrigid\", \"madriqid\", \"madroxin\", \"madroxine\", \"maxulvet\", \"mecozine\", \"memcozine\", \"metoxidon\", \"neostrepal\", \"neostreptal\", \"nsulfanilamide\", \"omnibon\", \"persulfen\", \"primor\", \"radonin\", \"redifal\", \"rofenaid\", \"roscosulf\", \"scandisil\", \"solfadimetossina\", \"sudine\", \"suldixine\", \"sulfabon\", \"sulfadimethoxin\", \"sulfadimethoxine\", \"sulfadimethoxinum\", \"sulfadimetossina\",
|
||||
\"sulfadimetoxin\", \"sulfadimetoxina\", \"sulfadimetoxine\", \"sulfastop\", \"sulfdimethoxine\", \"sulfoplan\", \"sulphadimethoxine\", \"sulxin\", \"sumbio\", \"symbio\", \"theracanzan\", \"ultrasulfon\")" 0.5 "g" "character(0)"
|
||||
"SDM" 5327 "Sulfadimidine" "Trimethoprims" "J01EB03" "Sulfonamides and trimethoprim" "Short-acting sulfonamides" "" "c(\"azolmetazin\", \"benzene sulfonamide\", \"calfspan\", \"calfspan tablets\", \"cremomethazine\", \"diazil\", \"diazilsulfadine\", \"dimezathine\", \"intradine\", \"kelametazine\", \"mermeth\", \"metazin\", \"neasina\", \"neazina\", \"nsulfanilamide\", \"panazin\", \"pirmazin\", \"primazin\", \"sa iii\", \"solfadimidina\", \"spanbolet\", \"sulfadimerazine\", \"sulfadimesin\", \"sulfadimesine\", \"sulfadimethyldiazine\", \"sulfadimezin\", \"sulfadimezine\", \"sulfadimezinum\", \"sulfadimidin\", \"sulfadimidina\", \"sulfadimidine\", \"sulfadimidinum\", \"sulfadine\",
|
||||
\"sulfametazina\", \"sulfametazyny\", \"sulfamethazine\", \"sulfamethiazine\", \"sulfamezathine\", \"sulfamidine\", \"sulfasure sr bolus\", \"sulfodimesin\", \"sulfodimezine\", \"sulka k boluses\", \"sulka s boluses\", \"sulmet\", \"sulphadimidine\", \"sulphamethasine\", \"sulphamethazine\", \"sulphamezathine\", \"sulphamidine\", \"sulphodimezine\", \"superseptil\", \"superseptyl\", \"vertolan\")" 4 "g" "character(0)"
|
||||
"SLT2" "Sulfadimidine/trimethoprim" "Trimethoprims" "J01EE05" "Sulfonamides and trimethoprim" "Combinations of sulfonamides and trimethoprim, incl. derivatives" "" "" ""
|
||||
"SLF" 5344 "Sulfafurazole" "Trimethoprims" "c(\"J01EB05\", \"S01AB02\")" "Sulfonamides and trimethoprim" "Short-acting sulfonamides" "c(\"\", \"sfsz\")" "c(\"accuzole\", \"alphazole\", \"amidoxal\", \"astrazolo\", \"azo gantrisin\", \"azosulfizin\", \"bactesulf\", \"barazae\", \"chemouag\", \"cosoxazole\", \"dorsulfan\", \"dorsulfan warthausen\", \"entusil\", \"entusul\", \"eryzole\", \"gantrisin\", \"gantrisine\", \"gantrisona\", \"gantrizin\", \"gantrosan\", \"isoxamin\", \"neazolin\", \"neoxazoi\", \"neoxazol\", \"novazolo\", \"novosaxazole\", \"nsulfanilamide\", \"nsulphanilamide\", \"pancid\", \"pediazole\", \"renosulfan\", \"resoxol\", \"roxosul\", \"roxosul tablets\", \"roxoxol\", \"saxosozine\", \"sodizole\", \"solfafurazolo\",
|
||||
\"soxamide\", \"soxazole\", \"soxisol\", \"soxitabs\", \"soxomide\", \"stansin\", \"sulbio\", \"sulfafuraz ole\", \"sulfafurazol\", \"sulfafurazole\", \"sulfafurazolum\", \"sulfagan\", \"sulfagen\", \"sulfaisoxazole\", \"sulfalar\", \"sulfapolar\", \"sulfasol\", \"sulfasoxazole\", \"sulfasoxizole\", \"sulfazin\", \"sulfisin\", \"sulfisonazole\", \"sulfisoxasole\", \"sulfisoxazol\", \"sulfisoxazole\", \"sulfisoxazolum\", \"sulfizin\", \"sulfizol\", \"sulfizole\", \"sulfofurazole\", \"sulfoxol\", \"suloxsol\", \"sulphafuraz\", \"sulphafurazol\", \"sulphafurazole\", \"sulphafurazolum\",
|
||||
\"sulphaisoxazole\", \"sulphisoxazol\", \"sulphisoxazole\", \"sulphofurazole\", \"sulsoxin\", \"thiasin\", \"unisulf\", \"urisoxin\", \"uritrisin\", \"urogan\", \"vagilia\")" 4 "g" 4 "g" "character(0)"
|
||||
"SLF1" 5343 "Sulfaisodimidine" "Trimethoprims" "J01EB01" "Sulfonamides and trimethoprim" "Short-acting sulfonamides" "" "c(\"aristamid\", \"aristamide\", \"aristogyn\", \"domain\", \"domian\", \"elcosin\", \"elcosine\", \"elkosil\", \"elkosin\", \"elkosine\", \"erycon\", \"isosulf\", \"mefenal\", \"nsulfanilamide\", \"solfisomidina\", \"sulfadimetine\", \"sulfaisodimerazine\", \"sulfaisodimidine\", \"sulfaisodimidinum\", \"sulfaisomidine\", \"sulfamethin\", \"sulfasomidine\", \"sulfisomidina\", \"sulfisomidine\", \"sulfisomidine sodium\", \"sulfisomidinum\", \"sulphasomidine\")" 4 "g" 4 "g" "character(0)"
|
||||
"SLF2" 9047 "Sulfalene" "Trimethoprims" "J01ED02" "Sulfonamides and trimethoprim" "Long-acting sulfonamides" "" "c(\"dalysep\", \"kelfizin\", \"kelfizina\", \"kelfizine\", \"kelfizine w\", \"longum\", \"nsulfanilamide\", \"policydal\", \"polycidal\", \"solfametopirazina\", \"sulfalen\", \"sulfalene\", \"sulfaleno\", \"sulfalenum\", \"sulfamethopyrazine\", \"sulfamethoxypyrazine\", \"sulfametopyrazine\", \"sulfametoxypyridazin\", \"sulphalene\", \"sulphametopyrazine\", \"vetkelfizina\")" 0.1 "g" "character(0)"
|
||||
"SZO" 187764 "Sulfamazone" "Trimethoprims" "J01ED09" "Sulfonamides and trimethoprim" "Long-acting sulfonamides" "" "c(\"sulfamazon\", \"sulfamazona\", \"sulfamazone\", \"sulfamazonum\")" 1.5 "g" "character(0)"
|
||||
"SLF3" 5325 "Sulfamerazine" "Trimethoprims" "c(\"D06BA06\", \"J01ED07\")" "Sulfonamides and trimethoprim" "Long-acting sulfonamides" "" "c(\"cremomerazine\", \"kelamerazine\", \"mebacid\", \"mesulfa\", \"methylpyrimal\", \"methylsulfazin\", \"methylsulfazine\", \"metilsulfadiazin\", \"metilsulfazin\", \"nsulfanilamide\", \"percoccide\", \"pyralcid\", \"pyrimal m\", \"romezin\", \"septacil\", \"septosyl\", \"solfamerazina\", \"solumedin\", \"sulfameradine\", \"sulfamerazin\", \"sulfamerazina\", \"sulfamerazine\", \"sulfamerazinum\", \"sulfamethyldiazine\", \"sulphamerazine\", \"sumedine\", \"susfamerazine\")" 3 "g" "character(0)"
|
||||
"SLT3" "Sulfamerazine/trimethoprim" "Trimethoprims" "J01EE07" "Sulfonamides and trimethoprim" "Combinations of sulfonamides and trimethoprim, incl. derivatives" "" "" ""
|
||||
"SUM" 5327 "Sulfamethazine" "Other antibacterials" "" "c(\"azolmetazin\", \"benzene sulfonamide\", \"calfspan\", \"calfspan tablets\", \"cremomethazine\", \"diazil\", \"diazilsulfadine\", \"dimezathine\", \"intradine\", \"kelametazine\", \"mermeth\", \"metazin\", \"neasina\", \"neazina\", \"nsulfanilamide\", \"panazin\", \"pirmazin\", \"primazin\", \"sa iii\", \"solfadimidina\", \"spanbolet\", \"sulfadimerazine\", \"sulfadimesin\", \"sulfadimesine\", \"sulfadimethyldiazine\", \"sulfadimezin\", \"sulfadimezine\", \"sulfadimezinum\", \"sulfadimidin\", \"sulfadimidina\", \"sulfadimidine\", \"sulfadimidinum\", \"sulfadine\",
|
||||
\"sulfametazina\", \"sulfametazyny\", \"sulfamethazine\", \"sulfamethiazine\", \"sulfamezathine\", \"sulfamidine\", \"sulfasure sr bolus\", \"sulfodimesin\", \"sulfodimezine\", \"sulka k boluses\", \"sulka s boluses\", \"sulmet\", \"sulphadimidine\", \"sulphamethasine\", \"sulphamethazine\", \"sulphamezathine\", \"sulphamidine\", \"sulphodimezine\", \"superseptil\", \"superseptyl\", \"vertolan\")" "87592-2"
|
||||
"SLF4" 5328 "Sulfamethizole" "Trimethoprims" "c(\"B05CA04\", \"D06BA04\", \"J01EB02\", \"S01AB01\")" "Sulfonamides and trimethoprim" "Short-acting sulfonamides" "c(\"\", \"sfmz\")" "c(\"ayerlucil\", \"lucosil\", \"methazol\", \"microsul\", \"nsulfanilamide\", \"proklar\", \"renasul\", \"salimol\", \"solfametizolo\", \"sulamethizole\", \"sulfa gram\", \"sulfamethizol\", \"sulfamethizole\", \"sulfamethizolum\", \"sulfametizol\", \"sulfapyelon\", \"sulfstat\", \"sulfurine\", \"sulphamethizole\", \"tetracid\", \"thidicur\", \"thiosulfil\", \"thiosulfil forte\", \"ultrasul\", \"urocydal\", \"urodiaton\", \"urolucosil\", \"urosulfin\")" 4 "g" "c(\"60175-7\", \"60176-5\", \"60177-3\")"
|
||||
"SMX" 5329 "Sulfamethoxazole" "Trimethoprims" "J01EC01" "Sulfonamides and trimethoprim" "Intermediate-acting sulfonamides" "c(\"sfmx\", \"sulf\")" "c(\"azo gantanol\", \"eusaprim\", \"gamazole\", \"gantanol\", \"gantanol ds\", \"metoxal\", \"nsulfanilamide\", \"nsulphanilamide\", \"radonil\", \"septran\", \"septrin\", \"simsinomin\", \"sinomin\", \"solfametossazolo\", \"sulfamethalazole\", \"sulfamethoxazol\", \"sulfamethoxazole\", \"sulfamethoxazolum\", \"sulfamethoxizole\", \"sulfamethylisoxazole\", \"sulfametoxazol\", \"sulfisomezole\", \"sulphamethalazole\", \"sulphamethoxazol\", \"sulphamethoxazole\", \"sulphisomezole\", \"urobak\")" 2 "g" "c(\"10342-4\", \"25271-8\", \"39772-9\", \"59971-2\", \"59972-0\", \"60333-2\", \"72674-5\", \"80549-9\", \"80974-9\")"
|
||||
"SLF5" 5330 "Sulfamethoxypyridazine" "Trimethoprims" "J01ED05" "Sulfonamides and trimethoprim" "Long-acting sulfonamides" "" "c(\"altezol\", \"davosin\", \"depovernil\", \"kineks\", \"lederkyn\", \"lentac\", \"lisulfen\", \"longin\", \"medicel\", \"midicel\", \"midikel\", \"myasul\", \"nsulfanilamide\", \"opinsul\", \"paramid\", \"paramid supra\", \"petrisul\", \"piridolo\", \"quinoseptyl\", \"retamid\", \"retasulfin\", \"retasulphine\", \"slosul\", \"spofadazine\", \"sulfalex\", \"sulfapyridazine\", \"sulfdurazin\", \"sulfozona\", \"sultirene\", \"vinces\")" 0.5 "g" "character(0)"
|
||||
"SLF6" 19596 "Sulfametomidine" "Trimethoprims" "J01ED03" "Sulfonamides and trimethoprim" "Long-acting sulfonamides" "" "c(\"duroprocin\", \"methofadin\", \"methofazine\", \"nsulfanilamide\", \"solfametomidina\", \"sulfamethomidine\", \"sulfametomidin\", \"sulfametomidina\", \"sulfametomidine\", \"sulfametomidinum\")" "character(0)"
|
||||
"SLF7" 5326 "Sulfametoxydiazine" "Trimethoprims" "J01ED04" "Sulfonamides and trimethoprim" "Long-acting sulfonamides" "" "c(\"bayrena\", \"berlicid\", \"dairena\", \"durenat\", \"juvoxin\", \"kinecid\", \"kirocid\", \"longasulf\", \"methoxypyrimal\", \"nsulfanilamide\", \"solfametossidiazina\", \"sulfameter\", \"sulfamethorine\", \"sulfamethoxine\", \"sulfamethoxydiazin\", \"sulfamethoxydiazine\", \"sulfamethoxydin\", \"sulfamethoxydine\", \"sulfametin\", \"sulfametinum\", \"sulfametorin\", \"sulfametorine\", \"sulfametorinum\", \"sulfametoxidiazina\", \"sulfametoxidine\", \"sulfametoxydiazine\", \"sulfametoxydiazinum\", \"sulphameter\", \"sulphamethoxydiazine\", \"supramid\",
|
||||
\"ultrax\")" 0.5 "g" "character(0)"
|
||||
"SLT4" "Sulfametrole/trimethoprim" "Trimethoprims" "J01EE03" "Sulfonamides and trimethoprim" "Combinations of sulfonamides and trimethoprim, incl. derivatives" "c(\"\", \"trsm\")" "" ""
|
||||
"SLF8" 12894 "Sulfamoxole" "Trimethoprims" "J01EC03" "Sulfonamides and trimethoprim" "Intermediate-acting sulfonamides" "" "c(\"justamil\", \"nsulfanilamide\", \"oxasulfa\", \"solfamossolo\", \"sulfadimethyloxazole\", \"sulfamoxol\", \"sulfamoxole\", \"sulfamoxolum\", \"sulfano\", \"sulfavigor\", \"sulfmidil\", \"sulfono\", \"sulfune\", \"sulfuno\", \"sulphamoxole\", \"tardamid\", \"tardamide\")" 1 "g" 1 "g" "character(0)"
|
||||
"SLT5" "Sulfamoxole/trimethoprim" "Trimethoprims" "J01EE04" "Sulfonamides and trimethoprim" "Combinations of sulfonamides and trimethoprim, incl. derivatives" "" "" ""
|
||||
"SLF9" 5333 "Sulfanilamide" "Trimethoprims" "c(\"D06BA05\", \"J01EB06\")" "Sulfonamides and trimethoprim" "Short-acting sulfonamides" "" "c(\"albexan\", \"albosal\", \"ambeside\", \"antistrept\", \"astreptine\", \"astrocid\", \"bacteramid\", \"bactesid\", \"collomide\", \"colsulanyde\", \"copticide\", \"deseptyl\", \"desseptyl\", \"dipron\", \"ergaseptine\", \"erysipan\", \"estreptocida\", \"exoseptoplix\", \"gerison\", \"gombardol\", \"infepan\", \"lysococcine\", \"neococcyl\", \"orgaseptine\", \"prontalbin\", \"prontosil album\", \"prontosil i\", \"prontosil white\", \"prontylin\", \"pronzin album\", \"proseptal\", \"proseptine\", \"proseptol\", \"pysococcine\", \"rubiazol a\", \"sanamid\", \"septamide album\",
|
||||
\"septanilam\", \"septinal\", \"septolix\", \"septoplex\", \"septoplix\", \"solfanilamide\", \"stopton album\", \"stramid\", \"strepamide\", \"strepsan\", \"streptagol\", \"streptamid\", \"streptamin\", \"streptasol\", \"streptocid\", \"streptocid album\", \"streptocide\", \"streptocide white\", \"streptocidum\", \"streptoclase\", \"streptocom\", \"streptol\", \"strepton\", \"streptopan\", \"streptosil\", \"streptozol\", \"streptozone\", \"streptrocide\", \"sulfamidyl\", \"sulfamine\", \"sulfana\", \"sulfanalone\", \"sulfanidyl\", \"sulfanil\", \"sulfanilamida\", \"sulfanilamide\",
|
||||
\"sulfanilamidum\", \"sulfanilimidic acid\", \"sulfanimide\", \"sulfocidin\", \"sulfocidine\", \"sulfonamide\", \"sulfonamide p\", \"sulfonylamide\", \"sulphanilamide\", \"sulphanilamide gr\", \"sulphonamide\", \"therapol\", \"tolder\", \"white streptocide\", \"wln: zswr dz\")" "character(0)"
|
||||
"SLF10" 68933 "Sulfaperin" "Trimethoprims" "J01ED06" "Sulfonamides and trimethoprim" "Long-acting sulfonamides" "" "c(\"anastaf\", \"archisulfa\", \"avissul\", \"chemiopen\", \"demosulfan\", \"durisan saft\", \"ipersulfidin sirup\", \"isosulfamerazine\", \"methylsulfadiazin\", \"novosul\", \"nsulfanilamide\", \"orosulfan\", \"pallidin\", \"retardon\", \"risulfasens\", \"sulfaperin\", \"sulfaperina\", \"sulfaperine\", \"sulfaperinum\", \"sulfatreis\", \"sulfopirimidine\", \"sulpenta\", \"ultrasulfon sirup\")" 0.5 "g" "character(0)"
|
||||
"SLF11" 5335 "Sulfaphenazole" "Trimethoprims" "J01ED08" "Sulfonamides and trimethoprim" "Long-acting sulfonamides" "" "c(\"depocid\", \"depotsulfonamide\", \"eftolon\", \"firmazolo\", \"inamil\", \"isarol\", \"isarol v\", \"merian\", \"microtan pirazolo\", \"nsulfanilamide\", \"orisul\", \"orisulf\", \"paidazolo\", \"phenylsulfapyrazole\", \"plisulfan\", \"raziosulfa\", \"solfafenazolo\", \"sulfabid\", \"sulfafenazol\", \"sulfafenazolo\", \"sulfaphenazol\", \"sulfaphenazole\", \"sulfaphenazolum\", \"sulfaphenazon\", \"sulfaphenylpipazol\", \"sulfaphenylpyrazol\", \"sulfaphenylpyrazole\", \"sulfonylpyrazol\", \"sulphaphenazole\", \"sulphenazole\")" 1 "g" "character(0)"
|
||||
"SLF12" 5336 "Sulfapyridine" "Trimethoprims" "J01EB04" "Sulfonamides and trimethoprim" "Short-acting sulfonamides" "" "c(\"adiplon\", \"coccoclase\", \"dagenan\", \"eubasin\", \"eubasinum\", \"haptocil\", \"piridazol\", \"plurazol\", \"pyriamid\", \"pyridazol\", \"relbapiridina\", \"septipulmon\", \"solfapiridina\", \"streptosilpyridine\", \"sulfapiridina\", \"sulfapyridin\", \"sulfapyridine\", \"sulfapyridinum\", \"sulfidin\", \"sulfidine\", \"sulphapyridin\", \"sulphapyridine\", \"thioseptal\", \"trianon\")" 1 "g" "c(\"14075-6\", \"55580-5\")"
|
||||
"SNA" 60582 "Sulfasuccinamide" "Other antibacterials" "" "c(\"ambesid\", \"derganil\", \"sulfasuccinamid\", \"sulfasuccinamida\", \"sulfasuccinamide\", \"sulfasuccinamidum\")" "character(0)"
|
||||
"SUT" 5340 "Sulfathiazole" "Trimethoprims" "c(\"D06BA02\", \"J01EB07\")" "Sulfonamides and trimethoprim" "Short-acting sulfonamides" "" "c(\"azoquimiol\", \"azoseptale\", \"cerazol\", \"cerazole\", \"chemosept\", \"cibazol\", \"duatok\", \"dulana\", \"eleudron\", \"enterobiocine\", \"estafilol\", \"formosulfathiazole\", \"neostrepsan\", \"norsulfasol\", \"norsulfazol\", \"norsulfazole\", \"norsulfazolum\", \"nsulfanilamide\", \"planomide\", \"poliseptil\", \"sanotiazol\", \"septozol\", \"solfatiazolo\", \"streptosilthiazole\", \"sulfamul\", \"sulfathiazol\", \"sulfathiazole\", \"sulfathiazolum\", \"sulfatiazol\", \"sulfavitina\", \"sulfocerol\", \"sulphathiazole\", \"sulzol\", \"thiacoccine\", \"thiasulfol\",
|
||||
\"thiazamide\", \"thiozamide\", \"wintrazole\")" "87591-4"
|
||||
"SLF13" 3000579 "Sulfathiourea" "Trimethoprims" "J01EB08" "Sulfonamides and trimethoprim" "Short-acting sulfonamides" "" "c(\"badional\", \"baldinol\", \"fontamide\", \"salvoseptyl\", \"solfatiourea\", \"solufontamide\", \"sulfanilthiourea\", \"sulfathiocarbamid\", \"sulfathiocarbamide\", \"sulfathiocarbamidum\", \"sulfathiourea\", \"sulfathiouree\", \"sulfatiourea\", \"sulphathiourea\")" 6 "g" "character(0)"
|
||||
"SOX" 5344 "Sulfisoxazole" "Other antibacterials" "" "c(\"accuzole\", \"alphazole\", \"amidoxal\", \"astrazolo\", \"azo gantrisin\", \"azosulfizin\", \"bactesulf\", \"barazae\", \"chemouag\", \"cosoxazole\", \"dorsulfan\", \"dorsulfan warthausen\", \"entusil\", \"entusul\", \"eryzole\", \"gantrisin\", \"gantrisine\", \"gantrisona\", \"gantrizin\", \"gantrosan\", \"isoxamin\", \"neazolin\", \"neoxazoi\", \"neoxazol\", \"novazolo\", \"novosaxazole\", \"nsulfanilamide\", \"nsulphanilamide\", \"pancid\", \"pediazole\", \"renosulfan\", \"resoxol\", \"roxosul\", \"roxosul tablets\", \"roxoxol\", \"saxosozine\", \"sodizole\", \"solfafurazolo\",
|
||||
\"soxamide\", \"soxazole\", \"soxisol\", \"soxitabs\", \"soxomide\", \"stansin\", \"sulbio\", \"sulfafuraz ole\", \"sulfafurazol\", \"sulfafurazole\", \"sulfafurazolum\", \"sulfagan\", \"sulfagen\", \"sulfaisoxazole\", \"sulfalar\", \"sulfapolar\", \"sulfasol\", \"sulfasoxazole\", \"sulfasoxizole\", \"sulfazin\", \"sulfisin\", \"sulfisonazole\", \"sulfisoxasole\", \"sulfisoxazol\", \"sulfisoxazole\", \"sulfisoxazolum\", \"sulfizin\", \"sulfizol\", \"sulfizole\", \"sulfofurazole\", \"sulfoxol\", \"suloxsol\", \"sulphafuraz\", \"sulphafurazol\", \"sulphafurazole\", \"sulphafurazolum\",
|
||||
\"sulphaisoxazole\", \"sulphisoxazol\", \"sulphisoxazole\", \"sulphofurazole\", \"sulsoxin\", \"thiasin\", \"unisulf\", \"urisoxin\", \"uritrisin\", \"urogan\", \"vagilia\")" "9701-4"
|
||||
"SSS" 86225 "Sulfonamide" "Other antibacterials" "c(\"\", \"sfna\")" "" ""
|
||||
"SLP" 9950244 "Sulopenem" "Other antibacterials" "" "sulopenem" "character(0)"
|
||||
"SLT6" 444022 "Sultamicillin" "Beta-lactams/penicillins" "J01CR04" "Beta-lactam antibacterials, penicillins" "Combinations of penicillins, incl. beta-lactamase inhibitors" "" "c(\"sultamicilina\", \"sultamicillin\", \"sultamicillinum\")" 1.5 "g" "character(0)"
|
||||
"SUR" 46700778 "Surotomycin" "Other antibacterials" "" "surotomycin" "character(0)"
|
||||
"TAL" 71447 "Talampicillin" "Beta-lactams/penicillins" "J01CA15" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"talampicilina\", \"talampicillin\", \"talampicilline\", \"talampicillinum\")" 2 "g" "character(0)"
|
||||
"TLP" 163307 "Talmetoprim" "Other antibacterials" "" "talmetoprim" "character(0)"
|
||||
"TAZ" 123630 "Tazobactam" "Beta-lactams/penicillins" "J01CG02" "Beta-lactam antibacterials, penicillins" "Beta-lactamase inhibitors" "tazo" "c(\"tazobactam\", \"tazobactam acid\", \"tazobactamum\", \"tazobactum\")" "character(0)"
|
||||
"TBP" 9800194 "Tebipenem" "Carbapenems" "" "" ""
|
||||
"TZD" 11234049 "Tedizolid" "Oxazolidinones" "J01XX11" "Other antibacterials" "Other antibacterials" "tedi" "c(\"tedizolid\", \"torezolid\")" 0.2 "g" 0.2 "g" "character(0)"
|
||||
"TEC" 16131923 "Teicoplanin" "Glycopeptides" "J01XA02" "Other antibacterials" "Glycopeptide antibacterials" "c(\"tec\", \"tei\", \"teic\", \"tp\", \"tpl\", \"tpn\")" "c(\"targocid\", \"tecoplanina\", \"tecoplanine\", \"tecoplaninum\", \"teichomycin\", \"teicoplanina\", \"teicoplanine\", \"teicoplaninum\")" 0.4 "g" "c(\"25534-9\", \"25535-6\", \"34378-0\", \"34379-8\", \"4043-6\", \"80968-1\")"
|
||||
"TCM" "Teicoplanin-macromethod" "Glycopeptides" "" "" ""
|
||||
"TLV" 3081362 "Telavancin" "Glycopeptides" "J01XA03" "Other antibacterials" "Glycopeptide antibacterials" "tela" "c(\"telavancin\", \"vibativ\")" "character(0)"
|
||||
"TLT" 3002190 "Telithromycin" "Macrolides/lincosamides" "J01FA15" "Macrolides, lincosamides and streptogramins" "Macrolides" "c(\"\", \"teli\")" "levviax" 0.8 "g" "character(0)"
|
||||
"TMX" 60021 "Temafloxacin" "Quinolones" "J01MA05" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"tema\")" "c(\"omniflox\", \"temafloxacin\", \"temafloxacina\", \"temafloxacine\", \"temafloxacinum\")" 0.8 "g" "character(0)"
|
||||
"TEM" 171758 "Temocillin" "Beta-lactams/penicillins" "J01CA17" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "c(\"\", \"temo\")" "c(\"temocilina\", \"temocillin\", \"temocillina\", \"temocilline\", \"temocillinum\")" 4 "g" "character(0)"
|
||||
"TRB" 1549008 "Terbinafine" "Antifungals/antimycotics" "c(\"D01AE15\", \"D01BA02\")" "Antifungals for systemic use" "Antifungals for systemic use" "c(\"\", \"terb\")" "c(\"corbinal\", \"lamasil\", \"lamisil\", \"lamisil at\", \"lamisil tablet\", \"terbinafina\", \"terbinafine\", \"terbinafinum\", \"terbinex\")" 0.25 "g" "character(0)"
|
||||
"TRC" 441383 "Terconazole" "Antifungals/antimycotics" "G01AG02" "" "c(\"fungistat\", \"panlomyc\", \"terazol\", \"terconazol\", \"terconazole\", \"terconazolum\", \"tercospor\", \"triaconazole\", \"zazole\")" "character(0)"
|
||||
"TRZ" 65720 "Terizidone" "Antimycobacterials" "J04AK03" "Drugs for treatment of tuberculosis" "Other drugs for treatment of tuberculosis" "" "c(\"terivalidin\", \"terizidon\", \"terizidona\", \"terizidone\", \"terizidonum\")" "character(0)"
|
||||
"TCY" 54675776 "Tetracycline" "Tetracyclines" "c(\"A01AB13\", \"D06AA04\", \"J01AA07\", \"S01AA09\", \"S02AA08\", \"S03AA02\")" "Tetracyclines" "Tetracyclines" "c(\"tc\", \"te\", \"tet\", \"tetr\")" "c(\"abramycin\", \"abricycline\", \"achromycin\", \"achromycin v\", \"actisite\", \"agromicina\", \"ambramicina\", \"ambramycin\", \"amycin\", \"biocycline\", \"bristaciclin\", \"bristaciclina\", \"bristacycline\", \"cefracycline\", \"centet\", \"ciclibion\", \"copharlan\", \"criseociclina\", \"cyclomycin\", \"cyclopar\", \"cytome\", \"democracin\", \"deschlorobiomycin\", \"dumocyclin\", \"enterocycline\", \"hostacyclin\", \"lexacycline\", \"limecycline\", \"liquamycin\", \"medocycline\", \"mericycline\", \"micycline\", \"neocycline\", \"oletetrin\", \"omegamycin\",
|
||||
\"orlycycline\", \"panmycin\", \"piracaps\", \"polycycline\", \"polyotic\", \"purocyclina\", \"resteclin\", \"robitet\", \"roviciclina\", \"sigmamycin\", \"solvocin\", \"sumycin\", \"sumycin syrup\", \"tetrabon\", \"tetrachel\", \"tetraciclina\", \"tetracycl\", \"tetracyclin\", \"tetracycline\", \"tetracycline base\", \"tetracycline i\", \"tetracycline ii\", \"tetracyclinum\", \"tetracyn\", \"tetradecin\", \"tetrafil\", \"tetramed\", \"tetrasure\", \"tetraverine\", \"tetrazyklin\", \"tetrex\", \"topicycline\", \"tsiklomistsin\", \"tsiklomitsin\", \"veracin\", \"vetacyclinum\"
|
||||
)" 1 "g" 1 "g" "c(\"25272-6\", \"4045-1\", \"87590-6\")"
|
||||
"TET" 65450 "Tetroxoprim" "Other antibacterials" "" "c(\"tetroxoprim\", \"tetroxoprima\", \"tetroxoprime\", \"tetroxoprimum\")" "character(0)"
|
||||
"THA" 9568512 "Thiacetazone" "Oxazolidinones" "" "c(\"aktivan\", \"ambathizon\", \"amithiozone\", \"amithizone\", \"amitiozon\", \"benthiozone\", \"benzothiozane\", \"benzothiozon\", \"berculon a\", \"berkazon\", \"citazone\", \"conteben\", \"diasan\", \"diazan\", \"domakol\", \"ilbion\", \"livazone\", \"mirizone neustab\", \"mivizon\", \"myvizone\", \"neotibil\", \"neustab\", \"novakol\", \"nuclon argentinian\", \"panrone\", \"parazone\", \"seroden\", \"siocarbazone\", \"tebalon\", \"tebecure\", \"tebemar\", \"tebesone i\", \"tebethion\", \"tebethione\", \"tebezon\", \"thiacetazone\", \"thiacetone\", \"thiacetozone\",
|
||||
\"thibon\", \"thibone\", \"thioacetazon\", \"thioacetazone\", \"thioacetazonum\", \"thioazetazone\", \"thiocarbazil\", \"thiomicid\", \"thionicid\", \"thioparamizon\", \"thioparamizone\", \"thiosemicarbarzone\", \"thiosemicarbazone\", \"thiotebesin\", \"thiotebezin\", \"thiotebicina\", \"thizone\", \"tiacetazon\", \"tibicur\", \"tibion\", \"tibione\", \"tibizan\", \"tibone\", \"tioacetazon\", \"tioacetazona\", \"tioatsetazon\", \"tiobicina\", \"tiocarone\", \"tiosecolo\", \"tubercazon\", \"tubigal\")" "character(0)"
|
||||
"THI" 27200 "Thiamphenicol" "Amphenicols" "J01BA02" "Amphenicols" "Amphenicols" "" "c(\"descocin\", \"dexawin\", \"dextrosulfenidol\", \"dextrosulphenidol\", \"efnicol\", \"hyrazin\", \"igralin\", \"macphenicol\", \"masatirin\", \"neomyson\", \"racefenicol\", \"racefenicolo\", \"racefenicolum\", \"raceophenidol\", \"racephenicol\", \"rincrol\", \"thiamcol\", \"thiamphenicol\", \"thiamphenicolum\", \"thiocymetin\", \"thiomycetin\", \"thiophenicol\", \"tiamfenicol\", \"tiamfenicolo\", \"urfamicina\", \"urfamycine\", \"vicemycetin\")" 1.5 "g" 1.5 "g" "character(0)"
|
||||
"THI1" "Thioacetazone/isoniazid" "Antimycobacterials" "J04AM04" "Drugs for treatment of tuberculosis" "Combinations of drugs for treatment of tuberculosis" "" "" ""
|
||||
"TIA" 656958 "Tiamulin" "Other antibacterials" "" "c(\"denagard\", \"tiamulin\", \"tiamulin pamoate\", \"tiamulina\", \"tiamuline\", \"tiamulinum\")" "87589-8"
|
||||
"TIC" 36921 "Ticarcillin" "Beta-lactams/penicillins" "J01CA13" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "c(\"tc\", \"ti\", \"tic\", \"tica\")" "c(\"ticarcilina\", \"ticarcillin\", \"ticarcilline\", \"ticarcillinum\", \"ticillin\")" 15 "g" "c(\"25254-4\", \"4054-3\", \"4055-0\")"
|
||||
"TCC" 6437075 "Ticarcillin/clavulanic acid" "Beta-lactams/penicillins" "J01CR03" "Beta-lactam antibacterials, penicillins" "Combinations of penicillins, incl. beta-lactamase inhibitors" "c(\"t/c\", \"tcc\", \"ticl\", \"tim\", \"tlc\")" "timentin" 15 "g" "character(0)"
|
||||
"TGC" 54686904 "Tigecycline" "Tetracyclines" "J01AA12" "Tetracyclines" "Tetracyclines" "c(\"tgc\", \"tig\", \"tige\")" "c(\"haizheng li xing\", \"tigeciclina\", \"tigecyclin\", \"tigecycline\", \"tigecycline hydrate\", \"tigecyclinum\", \"tigilcycline\", \"tygacil\")" 0.1 "g" "character(0)"
|
||||
"TBQ" 65592 "Tilbroquinol" "Quinolones" "P01AA05" "" "c(\"tilbroquinol\", \"tilbroquinolum\")" "character(0)"
|
||||
"TIP" 24860548 "Tildipirosin" "Macrolides/lincosamides" "" "c(\"tildipirosin\", \"zuprevo\")" "character(0)"
|
||||
"TIL" 5282521 "Tilmicosin" "Macrolides/lincosamides" "" "c(\"micotil\", \"pulmotil\", \"tilmicosin\", \"tilmicosina\", \"tilmicosine\", \"tilmicosinum\")" "87588-0"
|
||||
"TIN" 5479 "Tinidazole" "Other antibacterials" "c(\"J01XD02\", \"P01AB02\")" "Other antibacterials" "Imidazole derivatives" "c(\"\", \"tini\")" "c(\"amtiba\", \"bioshik\", \"ethyl sulfone\", \"fasigin\", \"fasigyn\", \"fasigyntrade mark\", \"fasygin\", \"glongyn\", \"haisigyn\", \"pletil\", \"simplotan\", \"simplotantrade mark\", \"sorquetan\", \"tindamax\", \"tindamaxtrade mark\", \"tinidazol\", \"tinidazole\", \"tinidazolum\", \"tricolam\", \"trimonase\")" 2 "g" 1.5 "g" "character(0)"
|
||||
"TCR" 3001386 "Tiocarlide" "Antimycobacterials" "J04AD02" "Drugs for treatment of tuberculosis" "Thiocarbamide derivatives" "" "c(\"amixyl\", \"datanil\", \"disocarban\", \"disoxyl\", \"thiocarlide\", \"tiocarlid\", \"tiocarlida\", \"tiocarlide\", \"tiocarlidum\")" 7 "g" "character(0)"
|
||||
"TDC" 10247721 "Tiodonium chloride" "Other antibacterials" "" "c(\"cloruro de tiodonio\", \"tiodonii chloridum\", \"tiodonium chloride\")" "character(0)"
|
||||
"TXC" 65788 "Tioxacin" "Quinolones" "" "c(\"tioxacin\", \"tioxacine\", \"tioxacino\", \"tioxacinum\", \"tioxic acid\")" "character(0)"
|
||||
"TIZ" 394397 "Tizoxanide" "Other antibacterials" "" "ntzdes" "character(0)"
|
||||
"TOB" 36294 "Tobramycin" "Aminoglycosides" "c(\"J01GB01\", \"S01AA12\")" "Aminoglycoside antibacterials" "Other aminoglycosides" "c(\"nn\", \"tm\", \"to\", \"tob\", \"tobr\")" "c(\"bethkis\", \"brulamycin\", \"deoxykanamycin b\", \"distobram\", \"gernebcin\", \"gotabiotic\", \"kitabis pak\", \"nebcin\", \"nebicin\", \"nebramycin\", \"nebramycin vi\", \"obramycin\", \"sybryx\", \"tenebrimycin\", \"tenemycin\", \"tobacin\", \"tobi podhaler\", \"tobracin\", \"tobradex\", \"tobradistin\", \"tobralex\", \"tobramaxin\", \"tobramicin\", \"tobramicina\", \"tobramitsetin\", \"tobramycetin\", \"tobramycin\", \"tobramycin base\", \"tobramycin sulfate\", \"tobramycine\", \"tobramycinum\", \"tobrased\", \"tobrasone\", \"tobrex\")" 0.24 "g" "c(\"13584-8\", \"17808-7\", \"22750-4\", \"22751-2\", \"22752-0\", \"31094-6\", \"31095-3\", \"31096-1\", \"35239-3\", \"35670-9\", \"4057-6\", \"4058-4\", \"4059-2\", \"50927-3\", \"52962-8\", \"59380-6\", \"80966-5\")"
|
||||
"TOH" "Tobramycin-high" "Aminoglycosides" "c(\"tobra high\", \"tobramycin high\", \"tohl\")" "" ""
|
||||
"TFX" 5517 "Tosufloxacin" "Quinolones" "J01MA22" "" "tosufloxacin" 0.45 "g" "character(0)"
|
||||
"TMP" 5578 "Trimethoprim" "Trimethoprims" "J01EA01" "Sulfonamides and trimethoprim" "Trimethoprim and derivatives" "c(\"t\", \"tmp\", \"tr\", \"tri\", \"trim\", \"w\")" "c(\"abaprim\", \"alprim\", \"anitrim\", \"antrima\", \"antrimox\", \"bacdan\", \"bacidal\", \"bacide\", \"bacterial\", \"bacticel\", \"bactifor\", \"bactin\", \"bactoprim\", \"bactramin\", \"bactrim\", \"bencole\", \"bethaprim\", \"biosulten\", \"briscotrim\", \"chemotrin\", \"colizole\", \"colizole ds\", \"conprim\", \"cotrimel\", \"cotrimoxizole\", \"deprim\", \"dosulfin\", \"duocide\", \"esbesul\", \"espectrin\", \"euctrim\", \"exbesul\", \"fermagex\", \"fortrim\", \"idotrim\", \"ikaprim\", \"instalac\", \"kombinax\", \"lagatrim\", \"lagatrim forte\", \"lastrim\", \"lescot\",
|
||||
\"methoprim\", \"metoprim\", \"monoprim\", \"monotrim\", \"monotrimin\", \"novotrimel\", \"omstat\", \"oraprim\", \"pancidim\", \"polytrim\", \"priloprim\", \"primosept\", \"primsol\", \"proloprim\", \"protrin\", \"purbal\", \"resprim\", \"resprim forte\", \"roubac\", \"roubal\", \"salvatrim\", \"septrin ds\", \"septrin forte\", \"septrin s\", \"setprin\", \"sinotrim\", \"stopan\", \"streptoplus\", \"sugaprim\", \"sulfamar\", \"sulfamethoprim\", \"sulfoxaprim\", \"sulthrim\", \"sultrex\", \"syraprim\", \"tiempe\", \"tmp smx\", \"toprim\", \"trimanyl\", \"trimethioprim\", \"trimethopim\",
|
||||
\"trimethoprim\", \"trimethoprime\", \"trimethoprimum\", \"trimethopriom\", \"trimetoprim\", \"trimetoprima\", \"trimexazole\", \"trimexol\", \"trimezol\", \"trimogal\", \"trimono\", \"trimopan\", \"trimpex\", \"triprim\", \"trisul\", \"trisulcom\", \"trisulfam\", \"trisural\", \"uretrim\", \"urobactrim\", \"utetrin\", \"velaten\", \"wellcoprim\", \"wellcoprin\", \"xeroprim\", \"zamboprim\")" 0.4 "g" 0.4 "g" "c(\"11005-6\", \"17747-7\", \"25273-4\", \"32342-8\", \"4079-0\", \"4080-8\", \"4081-6\", \"55584-7\", \"80552-3\", \"80973-1\")"
|
||||
"SXT" 358641 "Trimethoprim/sulfamethoxazole" "Trimethoprims" "J01EE01" "Sulfonamides and trimethoprim" "Combinations of sulfonamides and trimethoprim, incl. derivatives" "c(\"cot\", \"cotrim\", \"sxt\", \"t/s\", \"trsu\", \"trsx\", \"ts\")" "c(\"bactrim\", \"bactrimel\", \"belcomycine\", \"colimycin\", \"colimycin sulphate\", \"colisticin\", \"colistimethate\", \"colistimethate sodium\", \"colistin sulfate\", \"colistin sulphate\", \"colomycin\", \"coly-mycin\", \"cotrimazole\", \"cotrimoxazole\", \"polymyxin e\", \"polymyxin e. sulfate\", \"promixin\", \"septra\", \"totazina\")" "character(0)"
|
||||
"TRL" 202225 "Troleandomycin" "Macrolides/lincosamides" "J01FA08" "Macrolides, lincosamides and streptogramins" "Macrolides" "" "c(\"acetyloleandomycin\", \"aovine\", \"cyclamycin\", \"evramicina\", \"matromicina\", \"matromycin t\", \"oleandocetine\", \"t.a.o.\", \"treolmicina\", \"tribiocillina\", \"triocetin\", \"triolan\", \"troleandomicina\", \"troleandomycin\", \"troleandomycine\", \"troleandomycinum\", \"viamicina\", \"wytrion\")" 1 "g" "character(0)"
|
||||
"TRO" 55886 "Trospectomycin" "Other antibacterials" "" "c(\"trospectinomycin\", \"trospectomicina\", \"trospectomycin\", \"trospectomycine\", \"trospectomycinum\")" "character(0)"
|
||||
"TVA" 62959 "Trovafloxacin" "Quinolones" "J01MA13" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"trov\")" "c(\"trovafloxacin\", \"trovan\")" 0.2 "g" 0.2 "g" "character(0)"
|
||||
"TUL" 9832301 "Tulathromycin" "Macrolides/lincosamides" "" "c(\"draxxin\", \"tulathrmycin a\", \"tulathromycin\", \"tulathromycin a\")" "character(0)"
|
||||
"TYL" 5280440 "Tylosin" "Macrolides/lincosamides" "" "c(\"fradizine\", \"tilosina\", \"tylocine\", \"tylosin\", \"tylosin a\", \"tylosine\", \"tylosinum\")" "87587-2"
|
||||
"TYL1" 6441094 "Tylvalosin" "Macrolides/lincosamides" "c(\"\", \"tvn\")" "" ""
|
||||
"PRU1" 124225 "Ulifloxacin (Prulifloxacin)" "Other antibacterials" "" "ulifloxacin" "character(0)"
|
||||
"VAN" 14969 "Vancomycin" "Glycopeptides" "c(\"A07AA09\", \"J01XA01\", \"S01AA28\")" "Other antibacterials" "Glycopeptide antibacterials" "c(\"va\", \"van\", \"vanc\")" "c(\"vancocin\", \"vancocin hcl\", \"vancoled\", \"vancomicina\", \"vancomycin\", \"vancomycin hcl\", \"vancomycine\", \"vancomycinum\", \"vancor\", \"viomycin derivative\")" 2 "g" 2 "g" "c(\"13586-3\", \"13587-1\", \"20578-1\", \"31012-8\", \"39092-2\", \"39796-8\", \"39797-6\", \"4089-9\", \"4090-7\", \"4091-5\", \"4092-3\", \"50938-0\", \"59381-4\")"
|
||||
"VAM" "Vancomycin-macromethod" "Glycopeptides" "" "" ""
|
||||
"VIO" 135398671 "Viomycin" "Antimycobacterials" "" "c(\"celiomycin\", \"florimycin\", \"floromycin\", \"viomicina\", \"viomycin\", \"viomycine\", \"viomycinum\")" "character(0)"
|
||||
"VIR" 11979535 "Virginiamycine" "Other antibacterials" "" "c(\"eskalin v\", \"mikamycin\", \"mikamycine\", \"mikamycinum\", \"ostreogrycinum\", \"pristinamycine\", \"pristinamycinum\", \"stafac\", \"stafytracine\", \"staphylomycin\", \"starfac\", \"streptogramin\", \"vernamycin\", \"virgimycin\", \"virgimycine\", \"virginiamycina\", \"virginiamycine\", \"virginiamycinum\")" "character(0)"
|
||||
"VOR" 71616 "Voriconazole" "Antifungals/antimycotics" "J02AC03" "Antimycotics for systemic use" "Triazole derivatives" "c(\"vori\", \"vrc\")" "c(\"pfizer\", \"vfend i.v.\", \"voriconazol\", \"voriconazole\", \"voriconazolum\", \"vorikonazole\")" 0.4 "g" 0.4 "g" "c(\"38370-3\", \"53902-3\", \"73676-9\", \"80553-1\", \"80651-3\")"
|
||||
"XBR" 72144 "Xibornol" "Other antibacterials" "J01XX02" "Other antibacterials" "Other antibacterials" "" "c(\"bactacine\", \"bracen\", \"nanbacine\", \"xibornol\", \"xibornolo\", \"xibornolum\")" "character(0)"
|
||||
"ZID" 77846445 "Zidebactam" "Other antibacterials" "" "zidebactam" "character(0)"
|
||||
"ZFD" "Zoliflodacin" "" "" ""
|
||||
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|
||||
"atc" "cid" "name" "atc_group" "synonyms" "oral_ddd" "oral_units" "iv_ddd" "iv_units"
|
||||
"J05AF06" 441300 "Abacavir" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"Abacavir\", \"Abacavir sulfate\", \"Ziagen\")" 0.6 "g"
|
||||
"J05AB01" 135398513 "Aciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "c(\"Acicloftal\", \"Aciclovier\", \"Aciclovir\", \"Aciclovirum\", \"Activir\", \"AcycloFoam\", \"Acycloguanosine\", \"Acyclovir\", \"Acyclovir Lauriad\", \"ACYCLOVIR SODIUM\", \"Avirax\", \"Cargosil\", \"Cyclovir\", \"Genvir\", \"Gerpevir\", \"Hascovir\", \"Herpevir\", \"Maynar\", \"Poviral\", \"Sitavig\", \"Sitavir\", \"Vipral\", \"Virolex\", \"Viropump\", \"Virorax\", \"Zovirax\", \"Zovirax topical\", \"Zyclir\")" 4 "g" 4 "g"
|
||||
"J05AF08" 60871 "Adefovir dipivoxil" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"Adefovir di ester\", \"Adefovir dipivoxil\", \"Adefovir Dipivoxil\", \"Adefovir dipivoxyl\", \"Adefovir pivoxil\", \"Adefovirdipivoxl\", \"Bisadenine\", \"BISADENINE\", \"BisPMEA\", \"Hepsera\", \"Preveon\", \"YouHeDing\")" 10 "mg"
|
||||
"J05AE05" 65016 "Amprenavir" "Protease inhibitors" "c(\"Agenerase\", \"Amprenavir\", \"Amprenavirum\", \"Prozei\", \"Vertex\")" 1.2 "g"
|
||||
"J05AP06" 16076883 "Asunaprevir" "Antivirals for treatment of HCV infections" "c(\"Asunaprevir\", \"Sunvepra\")"
|
||||
"J05AE08" 148192 "Atazanavir" "Protease inhibitors" "c(\"Atazanavir\", \"Atazanavir Base\", \"Latazanavir\", \"Reyataz\", \"Zrivada\")" 0.3 "g"
|
||||
"J05AR15" 86583336 "Atazanavir and cobicistat" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR23" "Atazanavir and ritonavir" "Antivirals for treatment of HIV infections, combinations" "" 0.3 "g"
|
||||
"J05AP03" 10324367 "Boceprevir" "Antivirals for treatment of HCV infections" "c(\"Bocepravir\", \"Boceprevir\", \"Victrelis\")" 2.4 "g"
|
||||
"J05AB15" 446727 "Brivudine" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "c(\"Bridic\", \"Brivox\", \"Brivudin\", \"Brivudina\", \"Brivudine\", \"Brivudinum\", \"BrVdUrd\", \"Helpin\", \"Zerpex\", \"Zostex\")" 0.125 "g"
|
||||
"J05AB12" 60613 "Cidofovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "c(\"Cidofovir\", \"Cidofovir anhydrous\", \"Cidofovir gel\", \"Cidofovirum\", \"Forvade\", \"Vistide\")" 25 "mg"
|
||||
"J05AF12" 73115 "Clevudine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"Clevudine\", \"Levovir\", \"Revovir\")" 30 "mg"
|
||||
"J05AP07" 25154714 "Daclatasvir" "Antivirals for treatment of HCV infections" "c(\"Daclatasvir\", \"Daklinza\")" 60 "mg"
|
||||
"J05AE10" 213039 "Darunavir" "Protease inhibitors" "c(\"Darunavir\", \"Darunavirum\", \"Prezista\", \"Prezista Naive\")" 1.2 "g"
|
||||
"J05AR14" "Darunavir and cobicistat" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AP09" 56640146 "Dasabuvir" "Antivirals for treatment of HCV infections" "Dasabuvir" 0.5 "g"
|
||||
"J05AP52" "Dasabuvir, ombitasvir, paritaprevir and ritonavir" "Antivirals for treatment of HCV infections" ""
|
||||
"J05AG02" 5625 "Delavirdine" "Non-nucleoside reverse transcriptase inhibitors" "c(\"BHAP der\", \"Delavirdin\", \"Delavirdina\", \"Delavirdine\", \"Delavirdinum\", \"PIPERAZINE\", \"Rescriptor\")" 1.2 "g"
|
||||
"J05AF02" 135398739 "Didanosine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"Didanosina\", \"Didanosine\", \"Didanosinum\", \"Dideoxyinosine\", \"DIDEOXYINOSINE\", \"Hypoxanthine ddN\", \"Videx\", \"Videx EC\")" 0.4 "g"
|
||||
"J05AX12" 54726191 "Dolutegravir" "Other antivirals" "c(\"Dolutegravir\", \"Dolutegravir Sodium\", \"Soltegravir\", \"Tivicay\")" 50 "mg"
|
||||
"J05AR21" 131801472 "Dolutegravir and rilpivirine" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AG06" 58460047 "Doravirine" "Non-nucleoside reverse transcriptase inhibitors" "c(\"Doravirine\", \"Pifeltro\")"
|
||||
"J05AG03" 64139 "Efavirenz" "Non-nucleoside reverse transcriptase inhibitors" "c(\"Efavirenz\", \"Efavirenzum\", \"Eravirenz\", \"Stocrin\", \"Strocin\", \"Sustiva\")" 0.6 "g"
|
||||
"J05AP54" 91669168 "Elbasvir and grazoprevir" "Antivirals for treatment of HCV infections" ""
|
||||
"J05AX11" 5277135 "Elvitegravir" "Other antivirals" "c(\"Elvitegravir\", \"Vitekta\")"
|
||||
"J05AF09" 60877 "Emtricitabine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"Coviracil\", \"Emtricitabin\", \"Emtricitabina\", \"Emtricitabine\", \"Emtricitabinum\", \"Emtritabine\", \"Emtriva\", \"Racivir\")" 0.2 "g"
|
||||
"J05AR17" 90469070 "Emtricitabine and tenofovir alafenamide" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR20" "Emtricitabine, tenofovir alafenamide and bictegravir" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR19" "Emtricitabine, tenofovir alafenamide and rilpivirine" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR22" "Emtricitabine, tenofovir alafenamide, darunavir and cobicistat" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR18" "Emtricitabine, tenofovir alafenamide, elvitegravir and cobicistat" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR06" "Emtricitabine, tenofovir disoproxil and efavirenz" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR08" "Emtricitabine, tenofovir disoproxil and rilpivirine" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR09" "Emtricitabine, tenofovir disoproxil, elvitegravir and cobicistat" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AX07" 16130199 "Enfuvirtide" "Other antivirals" "c(\"Enfurvitide\", \"Enfuvirtide\", \"Fuzeon\", \"Pentafuside\")" 0.18 "g"
|
||||
"J05AX17" 10089466 "Enisamium iodide" "Other antivirals" "Enisamium iodide" 1.5 "g"
|
||||
"J05AF10" 135398508 "Entecavir" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"Baraclude\", \"Entecavir\", \"Entecavir anhydrous\", \"Entecavirum\")" 0.5 "mg"
|
||||
"J05AG04" 193962 "Etravirine" "Non-nucleoside reverse transcriptase inhibitors" "c(\"DAPY deriv\", \"Etravine\", \"Etravirine\", \"Intelence\")" 0.4 "g"
|
||||
"J05AP04" 42601552 "Faldaprevir" "Antivirals for treatment of HCV infections" "Faldaprevir"
|
||||
"J05AB09" 3324 "Famciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "c(\"Famciclovir\", \"Famciclovirum\", \"Famvir\", \"Oravir\")" 0.75 "g"
|
||||
"J05AE07" 131536 "Fosamprenavir" "Protease inhibitors" "c(\"Amprenavir phosphate\", \"Fosamprenavir\", \"Lexiva\", \"Telzir\")" 1.4 "g"
|
||||
"J05AD01" 3415 "Foscarnet" "Phosphonic acid derivatives" "c(\"Forscarnet\", \"Forscarnet sodium\", \"Foscarmet\", \"Foscarnet\", \"Phosphonoformate\", \"Phosphonoformic acid\")" 6.5 "g"
|
||||
"J05AD02" 546 "Fosfonet" "Phosphonic acid derivatives" "c(\"Fosfonet\", \"Fosfonet sodium\", \"Fosfonet Sodium\", \"Fosfonoacetate\", \"Fosfonoacetic acid\", \"Phosphonacetate\", \"Phosphonacetic acid\")"
|
||||
"J05AB06" 135398740 "Ganciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "c(\"Citovirax\", \"Cymevan\", \"Cymeven\", \"Cymevene\", \"Cytovene\", \"Cytovene IV\", \"Ganciclovir\", \"Ganciclovirum\", \"Gancyclovir\", \"Hydroxyacyclovir\", \"Virgan\", \"Vitrasert\", \"Zirgan\")" 3 "g" 0.5 "g"
|
||||
"J05AP57" "Glecaprevir and pibrentasvir" "Antivirals for treatment of HCV infections" ""
|
||||
"J05AX23" "Ibalizumab" "Other antivirals" ""
|
||||
"J05AB02" 5905 "Idoxuridine" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "c(\"Antizona\", \"Dendrid\", \"Emanil\", \"Heratil\", \"Herpesil\", \"Herpid\", \"Herpidu\", \"Herplex\", \"HERPLEX\", \"Herplex liquifilm\", \"Idexur\", \"Idossuridina\", \"Idoxene\", \"Idoxuridin\", \"Idoxuridina\", \"Idoxuridine\", \"Idoxuridinum\", \"Idu Oculos\", \"Iducher\", \"Idulea\", \"Iduoculos\", \"Iduridin\", \"Iduviran\", \"Iododeoxyridine\", \"Iododeoxyuridine\", \"Iodoxuridine\", \"Joddeoxiuridin\", \"Kerecid\", \"Kerecide\", \"Ophthalmadine\", \"Spectanefran\", \"Stoxil\", \"Synmiol\", \"Virudox\")"
|
||||
"J05AE02" 5362440 "Indinavir" "Protease inhibitors" "c(\"Compound J\", \"Crixivan\", \"Indinavir\", \"Indinavir anhydrous\", \"Propolis+Indinavir\")" 2.4 "g"
|
||||
"J05AX05" 135449284 "Inosine pranobex" "Other antivirals" "c(\"Aviral\", \"Delimmun\", \"Immunovir\", \"Imunovir\", \"Inosine pranobex\", \"Inosiplex\", \"Isoprinosin\", \"Isoprinosina\", \"Isoprinosine\", \"Isoviral\", \"Methisoprinol\", \"Methysoprinol\", \"Metisoprinol\", \"Viruxan\")" 3 "g"
|
||||
"J05AF05" 60825 "Lamivudine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"Epivir\", \"Hepitec\", \"Heptivir\", \"Heptodin\", \"Heptovir\", \"Lamivir\", \"Lamivudin\", \"Lamivudina\", \"Lamivudine\", \"Lamivudinum\", \"Zeffix\")" 0.3 "g"
|
||||
"J05AR02" "Lamivudine and abacavir" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR16" 73386700 "Lamivudine and raltegravir" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR12" "Lamivudine and tenofovir disoproxil" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR13" "Lamivudine, abacavir and dolutegravir" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR24" "Lamivudine, tenofovir disoproxil and doravirine" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR11" "Lamivudine, tenofovir disoproxil and efavirenz" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AX18" 45138674 "Letermovir" "Other antivirals" "c(\"Letermovir\", \"Prevymis\")" 0.48 "g" 0.48 "g"
|
||||
"J05AR10" 11979606 "Lopinavir and ritonavir" "Antivirals for treatment of HIV infections, combinations" "c(\"Aluvia\", \"Kaletra\")" 0.8 "g"
|
||||
"J05AX02" 24839946 "Lysozyme" "Other antivirals" "c(\"Lysozyme chloride\", \"Lysozyme Chloride\", \"Lysozyme G\")"
|
||||
"J05AX09" 3002977 "Maraviroc" "Other antivirals" "c(\"Celsentri\", \"Maraviroc\", \"Selzentry\")" 0.6 "g"
|
||||
"J05AX10" 471161 "Maribavir" "Other antivirals" "c(\"Benzimidavir\", \"Camvia\", \"Maribavir\")"
|
||||
"J05AA01" 667492 "Metisazone" "Thiosemicarbazones" "c(\"Kemoviran\", \"Marboran\", \"Marborane\", \"Methisazon\", \"Methisazone\", \"Methsazone\", \"Metisazon\", \"Metisazona\", \"Metisazone\", \"Metisazonum\", \"Viruzona\")"
|
||||
"J05AX01" 71655 "Moroxydine" "Other antivirals" "c(\"Bimolin\", \"Flumidine\", \"Influmine\", \"Moroxidina\", \"Moroxydine\", \"Moroxydinum\", \"Vironil\", \"Virugon\", \"Virumin\", \"Wirumin\")" 0.3 "g"
|
||||
"J05AE04" 64143 "Nelfinavir" "Protease inhibitors" "c(\"Nelfinavir\", \"Viracept\")" 2.25 "g"
|
||||
"J05AG01" 4463 "Nevirapine" "Non-nucleoside reverse transcriptase inhibitors" "c(\"Nevirapine\", \"Nevirapine anhydrous\", \"Viramune\", \"Viramune IR\", \"Viramune XR\")" 0.4 "g"
|
||||
"J05AP53" "Ombitasvir, paritaprevir and ritonavir" "Antivirals for treatment of HCV infections" ""
|
||||
"J05AH02" 65028 "Oseltamivir" "Neuraminidase inhibitors" "c(\"Agucort\", \"Oseltamivir\", \"Tamiflu\", \"Tamvir\")" 0.15 "g"
|
||||
"J05AB13" 135398748 "Penciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "c(\"Adenovir\", \"Denavir\", \"Penciceovir\", \"Penciclovir\", \"Penciclovirum\", \"Pencyclovir\", \"Vectavir\")"
|
||||
"J05AX21" 9942657 "Pentanedioic acid imidazolyl ethanamide" "Other antivirals" "Ingamine" 90 "mg"
|
||||
"J05AH03" 154234 "Peramivir" "Neuraminidase inhibitors" "c(\"PeramiFlu\", \"Peramivir\", \"Rapiacta\", \"RAPIVAB\")"
|
||||
"J05AX06" 1684 "Pleconaril" "Other antivirals" "c(\"Picovir\", \"Pleconaril\", \"Pleconarilis\")"
|
||||
"J05AX08" 54671008 "Raltegravir" "Other antivirals" "c(\"Isentress\", \"Raltegravir\")" 0.8 "g"
|
||||
"J05AP01" 37542 "Ribavirin" "Antivirals for treatment of HCV infections" "c(\"Copegus\", \"Cotronak\", \"Drug: Ribavirin\", \"Ravanex\", \"Rebetol\", \"Rebetron\", \"Rebretron\", \"Ribacine\", \"Ribamide\", \"Ribamidil\", \"Ribamidyl\", \"Ribasphere\", \"Ribavirin\", \"Ribavirin Capsules\", \"Ribavirina\", \"Ribavirine\", \"Ribavirinum\", \"Ribovirin\", \"Tribavirin\", \"Varazid\", \"Vilona\", \"Viramid\", \"Viramide\", \"Virazid\", \"Virazide\", \"Virazole\")" 1 "g"
|
||||
"J05AG05" 6451164 "Rilpivirine" "Non-nucleoside reverse transcriptase inhibitors" "c(\"Edurant\", \"Rilpivirine\")" 25 "mg"
|
||||
"J05AC02" 5071 "Rimantadine" "Cyclic amines" "c(\"Remantadine\", \"Riamantadine\", \"Rimant\", \"RIMANTADIN\", \"Rimantadin A\", \"Rimantadina\", \"Rimantadine\", \"Rimantadinum\")" 0.2 "g"
|
||||
"J05AE03" 392622 "Ritonavir" "Protease inhibitors" "c(\"Norvir\", \"Norvir Sec\", \"Norvir Softgel\", \"Ritonavir\", \"Ritonavire\", \"Ritonavirum\")" 1.2 "g"
|
||||
"J05AE01" 441243 "Saquinavir" "Protease inhibitors" "c(\"Fortovase\", \"Invirase\", \"Saquinavir\")" 1.8 "g"
|
||||
"J05AP05" 24873435 "Simeprevir" "Antivirals for treatment of HCV infections" "c(\"Olysio\", \"Simeprevir sodium\")" 0.15 "g"
|
||||
"J05AP08" 45375808 "Sofosbuvir" "Antivirals for treatment of HCV infections" "c(\"Hepcinat\", \"Hepcvir\", \"Sofosbuvir\", \"Sovaldi\", \"SOVALDI\", \"SoviHep\")" 0.4 "g"
|
||||
"J05AP51" 72734365 "Sofosbuvir and ledipasvir" "Antivirals for treatment of HCV infections" ""
|
||||
"J05AP55" 91885554 "Sofosbuvir and velpatasvir" "Antivirals for treatment of HCV infections" "Epclusa Tablet"
|
||||
"J05AP56" "Sofosbuvir, velpatasvir and voxilaprevir" "Antivirals for treatment of HCV infections" ""
|
||||
"J05AF04" 18283 "Stavudine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"Estavudina\", \"Sanilvudine\", \"Stavudin\", \"Stavudine\", \"Stavudinum\", \"Zerit Xr\", \"Zerut XR\")" 80 "mg"
|
||||
"J05AR07" 15979285 "Stavudine, lamivudine and nevirapine" "Antivirals for treatment of HIV infections, combinations" "STAVUDIINE"
|
||||
"J05AP02" 3010818 "Telaprevir" "Antivirals for treatment of HCV infections" "c(\"Incivek\", \"Incivo\", \"Telaprevir\", \"Telavic\")" 2.25 "g"
|
||||
"J05AF11" 159269 "Telbivudine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"Epavudine\", \"Sebivo\", \"Telbivudin\", \"Telbivudine\", \"Tyzeka\")" 0.6 "g"
|
||||
"J05AF13" 9574768 "Tenofovir alafenamide" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Vemlidy" 25 "mg"
|
||||
"J05AF07" 5481350 "Tenofovir disoproxil" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"BisPMPA\", \"PMPA prodrug\", \"Tenofovir\", \"Viread\")" 0.245 "g"
|
||||
"J05AR03" "Tenofovir disoproxil and emtricitabine" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AX19" 5475 "Tilorone" "Other antivirals" "c(\"Amiksin\", \"Amixin\", \"Amixin IC\", \"Amyxin\", \"Tiloron\", \"Tilorona\", \"Tilorone\", \"Tiloronum\")" 0.125 "g"
|
||||
"J05AE09" 54682461 "Tipranavir" "Protease inhibitors" "c(\"Aptivus\", \"Tipranavir\")" 1 "g"
|
||||
"J05AC03" 64377 "Tromantadine" "Cyclic amines" "c(\"Tromantadina\", \"Tromantadine\", \"Tromantadinum\", \"Viruserol\")"
|
||||
"J05AX13" 131411 "Umifenovir" "Other antivirals" "c(\"Arbidol\", \"Arbidol base\", \"Umifenovir\")" 0.8 "g"
|
||||
"J05AB11" 135398742 "Valaciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "c(\"Talavir\", \"Valaciclovir\", \"Valaciclovirum\", \"ValACV\", \"Valcivir\", \"Valcyclovir\", \"Valtrex\", \"Virval\", \"Zelitrex\")" 3 "g"
|
||||
"J05AB14" 135413535 "Valganciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "c(\"Cymeval\", \"Valganciclovir\")" 0.9 "g"
|
||||
"J05AB03" 21704 "Vidarabine" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "c(\"Adenine arabinoside\", \"Araadenosine\", \"Arabinoside adenine\", \"Arabinosyl adenine\", \"Arabinosyladenine\", \"Spongoadenosine\", \"Vidarabin\", \"Vidarabina\", \"Vidarabine\", \"Vidarabine anhydrous\", \"Vidarabinum\", \"Vira A\", \"Vira ATM\")"
|
||||
"J05AF03" 24066 "Zalcitabine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"Dideoxycytidine\", \"Interferon AD + ddC\", \"Zalcitabine\", \"Zalcitibine\")" 2.25 "mg"
|
||||
"J05AH01" 60855 "Zanamivir" "Neuraminidase inhibitors" "c(\"MODIFIED SIALIC ACID\", \"Relenza\", \"Zanamavir\", \"Zanamir\", \"Zanamivi\", \"Zanamivir\", \"Zanamivir hydrate\")"
|
||||
"J05AF01" 35370 "Zidovudine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "c(\"Azidothymidine\", \"AZT Antiviral\", \"Beta interferon\", \"Compound S\", \"Propolis+AZT\", \"Retrovir\", \"Zidovudina\", \"Zidovudine\", \"ZIDOVUDINE\", \"Zidovudine EP III\", \"Zidovudinum\")" 0.6 "g" 0.6 "g"
|
||||
"J05AR01" "Zidovudine and lamivudine" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR04" "Zidovudine, lamivudine and abacavir" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
"J05AR05" "Zidovudine, lamivudine and nevirapine" "Antivirals for treatment of HIV infections, combinations" ""
|
||||
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@@ -1 +0,0 @@
|
||||
7b6649442069d3d121f61ca3ff01843a
|
||||
@@ -1,6 +0,0 @@
|
||||
|
||||
license_text <- readLines("docs/LICENSE-text.html")
|
||||
license_text <- paste(license_text, collapse = "|||")
|
||||
license_text <- gsub("licen(s|c)e", "Survey", license_text, ignore.case = TRUE)
|
||||
license_text <- gsub("<pre>.*</pre>", '<p>If no form is showing below, please <a href="https://forms.office.com/Pages/ResponsePage.aspx?id=-SJRM_TUZ02i_M1twg3ecDlnO1BBtdxGi-GnYu7DKfdUNTFLQ0xVSUlRVVlXTlVTNjZFMjdRUVpCSy4u" target="_blank">click here to open it</a>.</p><iframe width="100%" height= "500px" src= "https://forms.office.com/Pages/ResponsePage.aspx?id=-SJRM_TUZ02i_M1twg3ecDlnO1BBtdxGi-GnYu7DKfdUNTFLQ0xVSUlRVVlXTlVTNjZFMjdRUVpCSy4u&embed=true" frameborder= "0" marginwidth= "0" marginheight= "0" style= "border: none; max-width:100%; max-height:100vh" allowfullscreen webkitallowfullscreen mozallowfullscreen msallowfullscreen> </iframe>', license_text)
|
||||
writeLines(unlist(strsplit(license_text, "|||", fixed = TRUE)), "docs/survey.html")
|
||||
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Reference in New Issue
Block a user