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| Author | SHA1 | Date | |
|---|---|---|---|
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@@ -1,27 +0,0 @@
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^.*\.Rproj$
|
||||
^\.gitlab-ci\.R$
|
||||
^\.gitlab-ci\.yml$
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^\.Renviron$
|
||||
^\.Rprofile$
|
||||
^\.Rproj\.user$
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||||
^\.travis\.yml$
|
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^\.zenodo\.json$
|
||||
^_noinclude$
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||||
^_pkgdown\.yml$
|
||||
^appveyor\.yml$
|
||||
^codecov\.yml$
|
||||
^cran-comments\.md$
|
||||
^CRAN-RELEASE$
|
||||
^doc$
|
||||
^docs$
|
||||
^git_.*\.sh$
|
||||
^index\.md$
|
||||
^installed_deps$
|
||||
^Meta$
|
||||
^pkgdown$
|
||||
^public$
|
||||
^data-raw$
|
||||
R/aa_test.R$
|
||||
^\.lintr$
|
||||
^vignettes/benchmark.*
|
||||
^vignettes/SPSS.*
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-24
@@ -1,24 +0,0 @@
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Meta
|
||||
doc
|
||||
.Renviron
|
||||
.Rproj.user
|
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.Rhistory
|
||||
.RData
|
||||
.Ruserdata
|
||||
AMR.Rproj
|
||||
tests/testthat/Rplots.pdf
|
||||
inst/doc
|
||||
/src/*.o
|
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/src/*.o-*
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||||
/src/*.d
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||||
/src/*.so
|
||||
_noinclude
|
||||
*.dll
|
||||
vignettes/*.R
|
||||
.DS_Store
|
||||
.Rprofile
|
||||
^CRAN-RELEASE$
|
||||
packrat/lib*/
|
||||
packrat/src/
|
||||
data-raw/taxon.tab
|
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data-raw/DSMZ_bactnames.xlsx
|
||||
@@ -1,53 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
install_if_needed <- function(pkg, repos, quiet) {
|
||||
package_path <- find.package(pkg, quiet = quiet)
|
||||
if (length(package_path) == 0) {
|
||||
message("NOTE: pkg ", pkg, " missing, installing...")
|
||||
install.packages(pkg, repos = repos, quiet = quiet)
|
||||
}
|
||||
}
|
||||
|
||||
gl_update_pkg_all <- function(repos = "https://cran.rstudio.com",
|
||||
quiet = TRUE,
|
||||
install_pkgdown = FALSE,
|
||||
install_lintr = FALSE) {
|
||||
# update existing
|
||||
update.packages(ask = FALSE, repos = repos, quiet = quiet)
|
||||
|
||||
install_if_needed(pkg = "devtools", repos = repos, quiet = quiet)
|
||||
if (install_pkgdown == TRUE) {
|
||||
install_if_needed(pkg = "pkgdown", repos = repos, quiet = quiet)
|
||||
}
|
||||
if (install_lintr == TRUE) {
|
||||
install_if_needed(pkg = "lintr", repos = repos, quiet = quiet)
|
||||
}
|
||||
|
||||
devtools::install_dev_deps(repos = repos, quiet = quiet, upgrade = TRUE)
|
||||
|
||||
cat("INSTALLED:\n")
|
||||
instld <- as.data.frame(installed.packages())
|
||||
rownames(instld) <- NULL
|
||||
print(instld[, c("Package", "Version")])
|
||||
|
||||
return(invisible(TRUE))
|
||||
}
|
||||
-147
@@ -1,147 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
# to do a full CRAN check with R-Hub:
|
||||
# chck <- rhub::check(devtools::build(), platform = c('debian-clang-devel', 'debian-gcc-devel', 'fedora-clang-devel', 'fedora-gcc-devel', 'windows-x86_64-devel', 'debian-gcc-patched', 'solaris-x86-patched', 'debian-gcc-release', 'windows-x86_64-release', 'macos-elcapitan-release', 'windows-x86_64-oldrel'))
|
||||
|
||||
stages:
|
||||
- build
|
||||
- test
|
||||
- deploy
|
||||
- lint
|
||||
|
||||
image: rocker/r-base
|
||||
|
||||
before_script:
|
||||
- apt-get update -qq --allow-releaseinfo-change
|
||||
# install dependencies for packages
|
||||
- apt-get install -y wget locales libxml2-dev libssl-dev libcurl4-openssl-dev zlib1g-dev > /dev/null
|
||||
# recent pandoc
|
||||
- wget --quiet https://github.com/jgm/pandoc/releases/download/2.7.3/pandoc-2.7.3-1-amd64.deb
|
||||
- dpkg -i pandoc*.deb
|
||||
- rm pandoc*.deb
|
||||
# set R system language
|
||||
- echo "LC_ALL=en_US.UTF-8" >> /etc/environment
|
||||
- echo "en_US.UTF-8 UTF-8" >> /etc/locale.gen
|
||||
- echo "LANG=en_US.UTF-8" > /etc/locale.conf
|
||||
- locale-gen
|
||||
# cache R packages
|
||||
- mkdir -p installed_deps
|
||||
- echo 'R_LIBS="installed_deps"' > .Renviron
|
||||
- echo 'R_LIBS_USER="installed_deps"' >> .Renviron
|
||||
- echo 'R_LIBS_SITE="installed_deps"' >> .Renviron
|
||||
# set language
|
||||
- echo 'LANGUAGE="en_US.utf8"' >> .Renviron
|
||||
- echo 'LANG="en_US.utf8"' >> .Renviron
|
||||
- echo 'LANGUAGE="en_US.utf8"' > ~/.Renviron
|
||||
|
||||
R-release:
|
||||
stage: build
|
||||
allow_failure: false
|
||||
script:
|
||||
- Rscript -e 'sessionInfo()'
|
||||
# install missing and outdated packages
|
||||
- Rscript -e 'source(".gitlab-ci.R"); gl_update_pkg_all(repos = "https://cran.rstudio.com", quiet = TRUE, install_pkgdown = TRUE, install_lintr = TRUE)'
|
||||
# remove vignettes folder and get VignetteBuilder field out of DESCRIPTION file
|
||||
- rm -rf vignettes
|
||||
- Rscript -e 'd <- read.dcf("DESCRIPTION"); d[, colnames(d) == "VignetteBuilder"] <- NA; write.dcf(d, "DESCRIPTION")'
|
||||
# build package
|
||||
- R CMD build . --no-build-vignettes --no-manual
|
||||
- PKG_FILE_NAME=$(ls -1t *.tar.gz | head -n 1)
|
||||
- R CMD check "${PKG_FILE_NAME}" --no-build-vignettes --no-manual --as-cran
|
||||
artifacts:
|
||||
when: always
|
||||
paths:
|
||||
- '*.Rcheck/*'
|
||||
expire_in: '1 month'
|
||||
cache:
|
||||
key: r350
|
||||
paths:
|
||||
- installed_deps/
|
||||
|
||||
R-devel:
|
||||
stage: build
|
||||
image: rocker/r-devel
|
||||
allow_failure: false
|
||||
script:
|
||||
- Rscriptdevel -e 'sessionInfo()'
|
||||
# install missing and outdated packages
|
||||
- Rscriptdevel -e 'source(".gitlab-ci.R"); gl_update_pkg_all(repos = "https://cran.rstudio.com", quiet = TRUE)'
|
||||
# remove vignettes folder and get VignetteBuilder field out of DESCRIPTION file
|
||||
- rm -rf vignettes
|
||||
- Rscriptdevel -e 'd <- read.dcf("DESCRIPTION"); d[, colnames(d) == "VignetteBuilder"] <- NA; write.dcf(d, "DESCRIPTION")'
|
||||
# build package
|
||||
- Rdevel CMD build . --no-build-vignettes --no-manual
|
||||
- PKG_FILE_NAME=$(ls -1t *.tar.gz | head -n 1)
|
||||
- Rdevel CMD check "${PKG_FILE_NAME}" --no-build-vignettes --no-manual --as-cran
|
||||
artifacts:
|
||||
when: always
|
||||
paths:
|
||||
- '*.Rcheck/*'
|
||||
expire_in: '1 month'
|
||||
cache:
|
||||
key: r360
|
||||
paths:
|
||||
- installed_deps/
|
||||
|
||||
coverage:
|
||||
stage: test
|
||||
allow_failure: true
|
||||
when: on_success
|
||||
cache:
|
||||
key: r350
|
||||
paths:
|
||||
- installed_deps/
|
||||
policy: pull # no uploading after run
|
||||
only:
|
||||
- premaster
|
||||
- master
|
||||
script:
|
||||
- apt-get install --yes git
|
||||
# codecov token is set in https://gitlab.com/msberends/AMR/settings/ci_cd
|
||||
- Rscript -e "cc <- covr::package_coverage(); covr::codecov(coverage = cc, token = '$codecov'); cat('Code coverage:', covr::percent_coverage(cc))"
|
||||
coverage: '/Code coverage: \d+\.\d+/'
|
||||
|
||||
pages:
|
||||
stage: deploy
|
||||
when: always
|
||||
only:
|
||||
- master
|
||||
script:
|
||||
- mv docs public
|
||||
artifacts:
|
||||
paths:
|
||||
- public
|
||||
|
||||
lintr:
|
||||
stage: lint
|
||||
when: on_success
|
||||
cache:
|
||||
key: r350
|
||||
paths:
|
||||
- installed_deps/
|
||||
policy: pull # no uploading after run
|
||||
only:
|
||||
- premaster
|
||||
- master
|
||||
script:
|
||||
# check all syntax with lintr
|
||||
- Rscript -e 'lintr::lint_package()'
|
||||
@@ -1,2 +0,0 @@
|
||||
linters: with_defaults(line_length_linter = NULL, trailing_whitespace_linter = NULL, object_name_linter = NULL, cyclocomp_linter = NULL, object_usage_linter = NULL, object_length_linter(length = 50L))
|
||||
exclusions: list("R/mo_history.R", "tests/testthat/test-mo_history.R")
|
||||
@@ -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)
|
||||
-64
@@ -1,64 +0,0 @@
|
||||
Package: AMR
|
||||
Version: 0.8.0
|
||||
Date: 2019-10-15
|
||||
Title: Antimicrobial Resistance Analysis
|
||||
Authors@R: c(
|
||||
person(role = c("aut", "cre"),
|
||||
family = "Berends", given = c("Matthijs", "S."), email = "m.s.berends@umcg.nl", comment = c(ORCID = "0000-0001-7620-1800")),
|
||||
person(role = c("aut", "ctb"),
|
||||
family = "Luz", given = c("Christian", "F."), email = "c.f.luz@umcg.nl", comment = c(ORCID = "0000-0001-5809-5995")),
|
||||
person(role = c("aut", "ths"),
|
||||
family = "Friedrich", given = c("Alex", "W."), email = "alex.friedrich@umcg.nl", comment = c(ORCID = "0000-0003-4881-038X")),
|
||||
person(role = c("aut", "ths"),
|
||||
family = "Sinha", given = c("Bhanu", "N.", "M."), email = "b.sinha@umcg.nl", comment = c(ORCID = "0000-0003-1634-0010")),
|
||||
person(role = c("aut", "ths"),
|
||||
family = "Albers", given = c("Casper", "J."), email = "c.j.albers@rug.nl", comment = c(ORCID = "0000-0002-9213-6743")),
|
||||
person(role = c("aut", "ths"),
|
||||
family = "Glasner", given = "Corinna", email = "c.glasner@umcg.nl", comment = c(ORCID = "0000-0003-1241-1328")),
|
||||
person(role = "ctb",
|
||||
family = "Fonville", given = c("Judith", "M."), email = "j.fonville@pamm.nl"),
|
||||
person(role = "ctb",
|
||||
family = "Hassing", given = c("Erwin", "E.", "A."), email = "e.hassing@certe.nl"),
|
||||
person(role = "ctb",
|
||||
family = "Hazenberg", given = c("Eric", "H.", "L.", "C.", "M."), email = "e.hazenberg@jbz.nl"),
|
||||
person(role = "ctb",
|
||||
family = "Lenglet", given = "Annick", email = "annick.lenglet@amsterdam.msf.org"),
|
||||
person(role = "ctb",
|
||||
family = "Meijer", given = c("Bart", "C."), email = "b.meijerg@certe.nl"),
|
||||
person(role = "ctb",
|
||||
family = "Souverein", given = "Dennis", email = "d.souvereing@streeklabhaarlem.nl"))
|
||||
Description: Functions to simplify the analysis and prediction of Antimicrobial
|
||||
Resistance (AMR) and to work with microbial and antimicrobial properties by
|
||||
using evidence-based methods, like those defined by Leclercq et al. (2013)
|
||||
<doi:10.1111/j.1469-0691.2011.03703.x> and the Clinical and Laboratory
|
||||
Standards Institute (2014) <isbn: 1-56238-899-1>.
|
||||
Depends:
|
||||
R (>= 3.1.0)
|
||||
Imports:
|
||||
backports,
|
||||
clean (>= 1.1.0),
|
||||
crayon (>= 1.3.0),
|
||||
data.table (>= 1.9.0),
|
||||
dplyr (>= 0.7.0),
|
||||
ggplot2,
|
||||
knitr (>= 1.0.0),
|
||||
microbenchmark,
|
||||
pillar,
|
||||
rlang (>= 0.3.1),
|
||||
tidyr (>= 0.7.0)
|
||||
Suggests:
|
||||
covr (>= 3.0.1),
|
||||
curl,
|
||||
readxl,
|
||||
rmarkdown,
|
||||
rstudioapi,
|
||||
rvest (>= 0.3.2),
|
||||
testthat (>= 1.0.2),
|
||||
xml2 (>= 1.0.0)
|
||||
VignetteBuilder: knitr
|
||||
URL: https://msberends.gitlab.io/AMR, https://gitlab.com/msberends/AMR
|
||||
BugReports: https://gitlab.com/msberends/AMR/issues
|
||||
License: GPL-2 | file LICENSE
|
||||
Encoding: UTF-8
|
||||
LazyData: true
|
||||
RoxygenNote: 6.1.1
|
||||
@@ -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
|
||||
@@ -1,319 +0,0 @@
|
||||
# Generated by roxygen2: do not edit by hand
|
||||
|
||||
S3method("[",ab)
|
||||
S3method("[",mo)
|
||||
S3method("[<-",ab)
|
||||
S3method("[<-",mo)
|
||||
S3method("[[",ab)
|
||||
S3method("[[",mo)
|
||||
S3method("[[<-",ab)
|
||||
S3method("[[<-",mo)
|
||||
S3method(as.data.frame,ab)
|
||||
S3method(as.data.frame,mo)
|
||||
S3method(as.double,mic)
|
||||
S3method(as.integer,mic)
|
||||
S3method(as.numeric,mic)
|
||||
S3method(as.rsi,data.frame)
|
||||
S3method(as.rsi,default)
|
||||
S3method(as.rsi,disk)
|
||||
S3method(as.rsi,mic)
|
||||
S3method(barplot,mic)
|
||||
S3method(barplot,rsi)
|
||||
S3method(c,ab)
|
||||
S3method(c,mo)
|
||||
S3method(droplevels,mic)
|
||||
S3method(droplevels,rsi)
|
||||
S3method(format,bug_drug_combinations)
|
||||
S3method(freq,mo)
|
||||
S3method(freq,rsi)
|
||||
S3method(kurtosis,data.frame)
|
||||
S3method(kurtosis,default)
|
||||
S3method(kurtosis,matrix)
|
||||
S3method(pillar_shaft,ab)
|
||||
S3method(pillar_shaft,disk)
|
||||
S3method(pillar_shaft,mic)
|
||||
S3method(pillar_shaft,mo)
|
||||
S3method(pillar_shaft,rsi)
|
||||
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,disk)
|
||||
S3method(print,mic)
|
||||
S3method(print,mo)
|
||||
S3method(print,mo_renamed)
|
||||
S3method(print,mo_uncertainties)
|
||||
S3method(print,rsi)
|
||||
S3method(skewness,data.frame)
|
||||
S3method(skewness,default)
|
||||
S3method(skewness,matrix)
|
||||
S3method(summary,mic)
|
||||
S3method(summary,mo)
|
||||
S3method(summary,rsi)
|
||||
S3method(type_sum,ab)
|
||||
S3method(type_sum,disk)
|
||||
S3method(type_sum,mic)
|
||||
S3method(type_sum,mo)
|
||||
S3method(type_sum,rsi)
|
||||
export("%like%")
|
||||
export("%like_case%")
|
||||
export(ab_atc)
|
||||
export(ab_atc_group1)
|
||||
export(ab_atc_group2)
|
||||
export(ab_cid)
|
||||
export(ab_ddd)
|
||||
export(ab_group)
|
||||
export(ab_info)
|
||||
export(ab_name)
|
||||
export(ab_property)
|
||||
export(ab_synonyms)
|
||||
export(ab_tradenames)
|
||||
export(age)
|
||||
export(age_groups)
|
||||
export(anti_join_microorganisms)
|
||||
export(as.ab)
|
||||
export(as.atc)
|
||||
export(as.disk)
|
||||
export(as.mic)
|
||||
export(as.mo)
|
||||
export(as.rsi)
|
||||
export(atc_online_ddd)
|
||||
export(atc_online_groups)
|
||||
export(atc_online_property)
|
||||
export(availability)
|
||||
export(brmo)
|
||||
export(bug_drug_combinations)
|
||||
export(catalogue_of_life_version)
|
||||
export(clear_mo_history)
|
||||
export(count_I)
|
||||
export(count_IR)
|
||||
export(count_R)
|
||||
export(count_S)
|
||||
export(count_SI)
|
||||
export(count_all)
|
||||
export(count_df)
|
||||
export(eucast_exceptional_phenotypes)
|
||||
export(eucast_rules)
|
||||
export(facet_rsi)
|
||||
export(filter_1st_cephalosporins)
|
||||
export(filter_2nd_cephalosporins)
|
||||
export(filter_3rd_cephalosporins)
|
||||
export(filter_4th_cephalosporins)
|
||||
export(filter_5th_cephalosporins)
|
||||
export(filter_ab_class)
|
||||
export(filter_aminoglycosides)
|
||||
export(filter_carbapenems)
|
||||
export(filter_cephalosporins)
|
||||
export(filter_first_isolate)
|
||||
export(filter_first_weighted_isolate)
|
||||
export(filter_fluoroquinolones)
|
||||
export(filter_glycopeptides)
|
||||
export(filter_macrolides)
|
||||
export(filter_tetracyclines)
|
||||
export(first_isolate)
|
||||
export(freq)
|
||||
export(full_join_microorganisms)
|
||||
export(g.test)
|
||||
export(geom_rsi)
|
||||
export(get_locale)
|
||||
export(get_mo_source)
|
||||
export(ggplot_rsi)
|
||||
export(ggplot_rsi_predict)
|
||||
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(key_antibiotics)
|
||||
export(key_antibiotics_equal)
|
||||
export(kurtosis)
|
||||
export(labels_rsi_count)
|
||||
export(left_join_microorganisms)
|
||||
export(like)
|
||||
export(mdr_tb)
|
||||
export(mdro)
|
||||
export(mo_authors)
|
||||
export(mo_class)
|
||||
export(mo_failures)
|
||||
export(mo_family)
|
||||
export(mo_fullname)
|
||||
export(mo_genus)
|
||||
export(mo_gramstain)
|
||||
export(mo_info)
|
||||
export(mo_kingdom)
|
||||
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_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(p.symbol)
|
||||
export(p_symbol)
|
||||
export(portion_I)
|
||||
export(portion_IR)
|
||||
export(portion_R)
|
||||
export(portion_S)
|
||||
export(portion_SI)
|
||||
export(portion_df)
|
||||
export(read.4D)
|
||||
export(resistance_predict)
|
||||
export(right_join_microorganisms)
|
||||
export(rsi_df)
|
||||
export(rsi_predict)
|
||||
export(scale_rsi_colours)
|
||||
export(scale_type.ab)
|
||||
export(scale_type.mo)
|
||||
export(scale_y_percent)
|
||||
export(semi_join_microorganisms)
|
||||
export(set_mo_source)
|
||||
export(skewness)
|
||||
export(theme_rsi)
|
||||
exportMethods("[.ab")
|
||||
exportMethods("[.mo")
|
||||
exportMethods("[<-.ab")
|
||||
exportMethods("[<-.mo")
|
||||
exportMethods("[[.ab")
|
||||
exportMethods("[[.mo")
|
||||
exportMethods("[[<-.ab")
|
||||
exportMethods("[[<-.mo")
|
||||
exportMethods(as.data.frame.ab)
|
||||
exportMethods(as.data.frame.mo)
|
||||
exportMethods(as.double.mic)
|
||||
exportMethods(as.integer.mic)
|
||||
exportMethods(as.numeric.mic)
|
||||
exportMethods(barplot.mic)
|
||||
exportMethods(barplot.rsi)
|
||||
exportMethods(c.ab)
|
||||
exportMethods(c.mo)
|
||||
exportMethods(droplevels.mic)
|
||||
exportMethods(droplevels.rsi)
|
||||
exportMethods(format.bug_drug_combinations)
|
||||
exportMethods(freq.mo)
|
||||
exportMethods(freq.rsi)
|
||||
exportMethods(kurtosis)
|
||||
exportMethods(kurtosis.data.frame)
|
||||
exportMethods(kurtosis.default)
|
||||
exportMethods(kurtosis.matrix)
|
||||
exportMethods(plot.mic)
|
||||
exportMethods(plot.rsi)
|
||||
exportMethods(print.ab)
|
||||
exportMethods(print.bug_drug_combinations)
|
||||
exportMethods(print.catalogue_of_life_version)
|
||||
exportMethods(print.disk)
|
||||
exportMethods(print.mic)
|
||||
exportMethods(print.mo)
|
||||
exportMethods(print.mo_renamed)
|
||||
exportMethods(print.mo_uncertainties)
|
||||
exportMethods(print.rsi)
|
||||
exportMethods(scale_type.ab)
|
||||
exportMethods(scale_type.mo)
|
||||
exportMethods(skewness)
|
||||
exportMethods(skewness.data.frame)
|
||||
exportMethods(skewness.default)
|
||||
exportMethods(skewness.matrix)
|
||||
exportMethods(summary.mic)
|
||||
exportMethods(summary.mo)
|
||||
exportMethods(summary.rsi)
|
||||
importFrom(clean,freq)
|
||||
importFrom(clean,freq.default)
|
||||
importFrom(clean,top_freq)
|
||||
importFrom(crayon,bgGreen)
|
||||
importFrom(crayon,bgRed)
|
||||
importFrom(crayon,bgYellow)
|
||||
importFrom(crayon,black)
|
||||
importFrom(crayon,blue)
|
||||
importFrom(crayon,bold)
|
||||
importFrom(crayon,green)
|
||||
importFrom(crayon,italic)
|
||||
importFrom(crayon,magenta)
|
||||
importFrom(crayon,make_style)
|
||||
importFrom(crayon,red)
|
||||
importFrom(crayon,silver)
|
||||
importFrom(crayon,strip_style)
|
||||
importFrom(crayon,underline)
|
||||
importFrom(crayon,white)
|
||||
importFrom(crayon,yellow)
|
||||
importFrom(data.table,as.data.table)
|
||||
importFrom(data.table,data.table)
|
||||
importFrom(data.table,setkey)
|
||||
importFrom(dplyr,"%>%")
|
||||
importFrom(dplyr,all_vars)
|
||||
importFrom(dplyr,any_vars)
|
||||
importFrom(dplyr,arrange)
|
||||
importFrom(dplyr,arrange_at)
|
||||
importFrom(dplyr,between)
|
||||
importFrom(dplyr,bind_rows)
|
||||
importFrom(dplyr,case_when)
|
||||
importFrom(dplyr,desc)
|
||||
importFrom(dplyr,distinct)
|
||||
importFrom(dplyr,everything)
|
||||
importFrom(dplyr,filter)
|
||||
importFrom(dplyr,filter_all)
|
||||
importFrom(dplyr,filter_at)
|
||||
importFrom(dplyr,funs)
|
||||
importFrom(dplyr,group_by)
|
||||
importFrom(dplyr,group_by_at)
|
||||
importFrom(dplyr,group_vars)
|
||||
importFrom(dplyr,if_else)
|
||||
importFrom(dplyr,lag)
|
||||
importFrom(dplyr,left_join)
|
||||
importFrom(dplyr,mutate)
|
||||
importFrom(dplyr,mutate_all)
|
||||
importFrom(dplyr,mutate_at)
|
||||
importFrom(dplyr,n)
|
||||
importFrom(dplyr,n_distinct)
|
||||
importFrom(dplyr,n_groups)
|
||||
importFrom(dplyr,progress_estimated)
|
||||
importFrom(dplyr,pull)
|
||||
importFrom(dplyr,rename)
|
||||
importFrom(dplyr,row_number)
|
||||
importFrom(dplyr,select)
|
||||
importFrom(dplyr,select_if)
|
||||
importFrom(dplyr,slice)
|
||||
importFrom(dplyr,summarise)
|
||||
importFrom(dplyr,summarise_if)
|
||||
importFrom(dplyr,tibble)
|
||||
importFrom(dplyr,transmute)
|
||||
importFrom(dplyr,ungroup)
|
||||
importFrom(dplyr,vars)
|
||||
importFrom(graphics,arrows)
|
||||
importFrom(graphics,axis)
|
||||
importFrom(graphics,barplot)
|
||||
importFrom(graphics,par)
|
||||
importFrom(graphics,plot)
|
||||
importFrom(graphics,points)
|
||||
importFrom(graphics,text)
|
||||
importFrom(knitr,kable)
|
||||
importFrom(microbenchmark,microbenchmark)
|
||||
importFrom(pillar,pillar_shaft)
|
||||
importFrom(pillar,type_sum)
|
||||
importFrom(rlang,as_label)
|
||||
importFrom(rlang,enquos)
|
||||
importFrom(stats,complete.cases)
|
||||
importFrom(stats,glm)
|
||||
importFrom(stats,lm)
|
||||
importFrom(stats,pchisq)
|
||||
importFrom(stats,predict)
|
||||
importFrom(tidyr,gather)
|
||||
importFrom(tidyr,spread)
|
||||
importFrom(utils,browseURL)
|
||||
importFrom(utils,menu)
|
||||
importFrom(utils,read.csv)
|
||||
importFrom(utils,write.csv)
|
||||
@@ -1,762 +0,0 @@
|
||||
# AMR 0.8.0
|
||||
|
||||
|
||||
### Breaking
|
||||
* Determination of first isolates now **excludes** all 'unknown' microorganisms at default, i.e. microbial code `"UNKNOWN"`. They can be included with the new parameter `include_unknown`:
|
||||
```r
|
||||
first_isolate(..., include_unknown = TRUE)
|
||||
```
|
||||
For WHONET users, this means that all records/isolates with organism code `"con"` (*contamination*) will be excluded at default, since `as.mo("con") = "UNKNOWN"`. The function always shows a note with the number of 'unknown' microorganisms that were included or excluded.
|
||||
* For code consistency, classes `ab` and `mo` will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in `NA`:
|
||||
```r
|
||||
# how it works in base R:
|
||||
x <- factor("A")
|
||||
x[1] <- "B"
|
||||
#> Warning message:
|
||||
#> invalid factor level, NA generated
|
||||
|
||||
# how it now works similarly for classes 'mo' and 'ab':
|
||||
x <- as.mo("E. coli")
|
||||
x[1] <- "testvalue"
|
||||
#> Warning message:
|
||||
#> invalid microorganism code, NA generated
|
||||
```
|
||||
This is important, because a value like `"testvalue"` could never be understood by e.g. `mo_name()`, although the class would suggest a valid microbial code.
|
||||
* Function `freq()` has moved to a new package, [`clean`](https://github.com/msberends/clean) ([CRAN link](https://cran.r-project.org/package=clean)), since creating frequency tables actually does not fit the scope of this package. The `freq()` function still works, since it is re-exported from the `clean` package (which will be installed automatically upon updating this `AMR` package).
|
||||
* Renamed data set `septic_patients` to `example_isolates`
|
||||
|
||||
### New
|
||||
* Function `bug_drug_combinations()` to quickly get a `data.frame` with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with `mo_shortname()` at default:
|
||||
```r
|
||||
x <- bug_drug_combinations(example_isolates)
|
||||
#> NOTE: Using column `mo` as input for `col_mo`.
|
||||
x[1:4, ]
|
||||
#> mo ab S I R total
|
||||
#> 1 A. baumannii AMC 0 0 3 3
|
||||
#> 2 A. baumannii AMK 0 0 0 0
|
||||
#> 3 A. baumannii AMP 0 0 3 3
|
||||
#> 4 A. baumannii AMX 0 0 3 3
|
||||
#> NOTE: Use 'format()' on this result to get a publicable/printable format.
|
||||
|
||||
# change the transformation with the FUN argument to anything you like:
|
||||
x <- bug_drug_combinations(example_isolates, FUN = mo_gramstain)
|
||||
#> NOTE: Using column `mo` as input for `col_mo`.
|
||||
x[1:4, ]
|
||||
#> mo ab S I R total
|
||||
#> 1 Gram-negative AMC 469 89 174 732
|
||||
#> 2 Gram-negative AMK 251 0 2 253
|
||||
#> 3 Gram-negative AMP 227 0 405 632
|
||||
#> 4 Gram-negative AMX 227 0 405 632
|
||||
#> NOTE: Use 'format()' on this result to get a publicable/printable format.
|
||||
```
|
||||
You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R `format()` function:
|
||||
```r
|
||||
format(x, combine_IR = FALSE)
|
||||
```
|
||||
* Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for `portion_*` functions or `count_*` functions. This can be used to determine the empiric susceptibility of a combination therapy. A new parameter `only_all_tested` (**which defaults to `FALSE`**) replaces the old `also_single_tested` and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the `portion` and `count` help pages), where the %SI is being determined:
|
||||
|
||||
```r
|
||||
# --------------------------------------------------------------------
|
||||
# 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> - - - -
|
||||
# --------------------------------------------------------------------
|
||||
```
|
||||
|
||||
Since this is a major change, usage of the old `also_single_tested` will throw an informative error that it has been replaced by `only_all_tested`.
|
||||
* `tibble` printing support for classes `rsi`, `mic`, `disk`, `ab` `mo`. When using `tibble`s containing antimicrobial columns, values `S` will print in green, values `I` will print in yellow and values `R` will print in red. Microbial IDs (class `mo`) will emphasise on the genus and species, not on the kingdom.
|
||||
```r
|
||||
# (run this on your own console, as this page does not support colour printing)
|
||||
library(dplyr)
|
||||
example_isolates %>%
|
||||
select(mo:AMC) %>%
|
||||
as_tibble()
|
||||
```
|
||||
|
||||
### Changed
|
||||
* Many algorithm improvements for `as.mo()` (of which some led to additions to the `microorganisms` data set). Many thanks to all contributors that helped improving the algorithms.
|
||||
* Self-learning algorithm - the function now gains experience from previously determined microorganism IDs and learns from it (yielding 80-95% speed improvement for any guess after the first try)
|
||||
* Big improvement for misspelled input
|
||||
* These new trivial names known to the field are now understood: meningococcus, gonococcus, pneumococcus
|
||||
* Updated to the latest taxonomic data (updated to August 2019, from the International Journal of Systematic and Evolutionary Microbiology
|
||||
* Added support for Viridans Group Streptococci (VGS) and Milleri Group Streptococci (MGS)
|
||||
* Added support for *Blastocystis*
|
||||
* Added support for 5,000 new fungi
|
||||
* Added support for unknown yeasts and fungi
|
||||
* Changed most microorganism IDs to improve readability. For example, the old code `B_ENTRC_FAE` could have been both *E. faecalis* and *E. faecium*. Its new code is `B_ENTRC_FCLS` and *E. faecium* has become `B_ENTRC_FACM`. Also, the Latin character æ (ae) is now preserved at the start of each genus and species abbreviation. For example, the old code for *Aerococcus urinae* was `B_ARCCC_NAE`. This is now `B_AERCC_URIN`.
|
||||
**IMPORTANT:** Old microorganism IDs are still supported, but support will be dropped in a future version. Use `as.mo()` on your old codes to transform them to the new format. Using functions from the `mo_*` family (like `mo_name()` and `mo_gramstain()`) on old codes, will throw a warning.
|
||||
* More intelligent guessing for `as.ab()`, including bidirectional language support
|
||||
* Added support for the German national guideline (3MRGN/4MRGN) in the `mdro()` function, to determine multi-drug resistant organisms
|
||||
* Function `eucast_rules()`:
|
||||
* Fixed a bug for *Yersinia pseudotuberculosis*
|
||||
* Added more informative errors and warnings
|
||||
* Printed info now distinguishes between added and changes values
|
||||
* Using Verbose mode (i.e. `eucast_rules(..., verbose = TRUE)`) returns more informative and readable output
|
||||
* Using factors as input now adds missing factors levels when the function changes antibiotic results
|
||||
* Improved the internal auto-guessing function for determining antimicrobials in your data set (`AMR:::get_column_abx()`)
|
||||
* Removed class `atc` - using `as.atc()` is now deprecated in favour of `ab_atc()` and this will return a character, not the `atc` class anymore
|
||||
* Removed deprecated functions `abname()`, `ab_official()`, `atc_name()`, `atc_official()`, `atc_property()`, `atc_tradenames()`, `atc_trivial_nl()`
|
||||
* Fix and speed improvement for `mo_shortname()`
|
||||
* Fix for using `mo_*` functions where the coercion uncertainties and failures would not be available through `mo_uncertainties()` and `mo_failures()` anymore
|
||||
* Deprecated the `country` parameter of `mdro()` in favour of the already existing `guideline` parameter to support multiple guidelines within one country
|
||||
* The `name` of `RIF` is now Rifampicin instead of Rifampin
|
||||
* The `antibiotics` data set is now sorted by name and all cephalosporins now have their generation between brackets
|
||||
* Speed improvement for `guess_ab_col()` which is now 30 times faster for antibiotic abbreviations
|
||||
* Improved `filter_ab_class()` to be more reliable and to support 5th generation cephalosporins
|
||||
* Function `availability()` now uses `portion_R()` instead of `portion_IR()`, to comply with EUCAST insights
|
||||
* Functions `age()` and `age_groups()` now have a `na.rm` parameter to remove empty values
|
||||
* Renamed function `p.symbol()` to `p_symbol()` (the former is now deprecated and will be removed in a future version)
|
||||
* Using negative values for `x` in `age_groups()` will now introduce `NA`s and not return an error anymore
|
||||
* Fix for determining the system's language
|
||||
* Fix for `key_antibiotics()` on foreign systems
|
||||
* Added 80 new LIS codes for microorganisms
|
||||
* Relabeled the factor levels of `mdr_tb()`
|
||||
* Added more MIC factor levels (`as.mic()`)
|
||||
|
||||
#### Other
|
||||
* Added Prof. Dr. Casper Albers as doctoral advisor and added Dr. Judith Fonville, Eric Hazenberg, Dr. Bart Meijer, Dr. Dennis Souverein and Annick Lenglet as contributors
|
||||
* Cleaned the coding style of every single syntax line in this package with the help of the `lintr` package
|
||||
|
||||
# AMR 0.7.1
|
||||
|
||||
#### New
|
||||
* Function `rsi_df()` to transform a `data.frame` to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions `count_df()` and `portion_df()` to immediately show resistance percentages and number of available isolates:
|
||||
```r
|
||||
septic_patients %>%
|
||||
select(AMX, CIP) %>%
|
||||
rsi_df()
|
||||
# antibiotic interpretation value isolates
|
||||
# 1 Amoxicillin SI 0.4442636 546
|
||||
# 2 Amoxicillin R 0.5557364 683
|
||||
# 3 Ciprofloxacin SI 0.8381831 1181
|
||||
# 4 Ciprofloxacin R 0.1618169 228
|
||||
```
|
||||
* Support for all scientifically published pathotypes of *E. coli* to date (that we could find). Supported are:
|
||||
|
||||
* AIEC (Adherent-Invasive *E. coli*)
|
||||
* ATEC (Atypical Entero-pathogenic *E. coli*)
|
||||
* DAEC (Diffusely Adhering *E. coli*)
|
||||
* EAEC (Entero-Aggresive *E. coli*)
|
||||
* EHEC (Entero-Haemorrhagic *E. coli*)
|
||||
* EIEC (Entero-Invasive *E. coli*)
|
||||
* EPEC (Entero-Pathogenic *E. coli*)
|
||||
* ETEC (Entero-Toxigenic *E. coli*)
|
||||
* NMEC (Neonatal Meningitis‐causing *E. coli*)
|
||||
* STEC (Shiga-toxin producing *E. coli*)
|
||||
* UPEC (Uropathogenic *E. coli*)
|
||||
|
||||
All these lead to the microbial ID of *E. coli*:
|
||||
```r
|
||||
as.mo("UPEC")
|
||||
# B_ESCHR_COL
|
||||
mo_name("UPEC")
|
||||
# "Escherichia coli"
|
||||
mo_gramstain("EHEC")
|
||||
# "Gram-negative"
|
||||
```
|
||||
* Function `mo_info()` as an analogy to `ab_info()`. The `mo_info()` prints a list with the full taxonomy, authors, and the URL to the online database of a microorganism
|
||||
* Function `mo_synonyms()` to get all previously accepted taxonomic names of a microorganism
|
||||
|
||||
#### Changed
|
||||
* Column names of output `count_df()` and `portion_df()` are now lowercase
|
||||
* Fixed bug in translation of microorganism names
|
||||
* Fixed bug in determining taxonomic kingdoms
|
||||
* Algorithm improvements for `as.ab()` and `as.mo()` to understand even more severely misspelled input
|
||||
* Function `as.ab()` now allows spaces for coercing antibiotics names
|
||||
* Added `ggplot2` methods for automatically determining the scale type of classes `mo` and `ab`
|
||||
* Added names of object in the header in frequency tables, even when using pipes
|
||||
* Prevented `"bacteria"` from getting coerced by `as.ab()` because Bacterial is a brand name of trimethoprim (TMP)
|
||||
* Fixed a bug where setting an antibiotic would not work for `eucast_rules()` and `mdro()`
|
||||
* Fixed a EUCAST rule for Staphylococci, where amikacin resistance would not be inferred from tobramycin
|
||||
* Removed `latest_annual_release` from the `catalogue_of_life_version()` function
|
||||
* Removed antibiotic code `PVM1` from the `antibiotics` data set as this was a duplicate of `PME`
|
||||
* Fixed bug where not all old taxonomic names would be printed, when using a vector as input for `as.mo()`
|
||||
* Manually added *Trichomonas vaginalis* from the kingdom of Protozoa, which is missing from the Catalogue of Life
|
||||
* Small improvements to `plot()` and `barplot()` for MIC and RSI classes
|
||||
* Allow Catalogue of Life IDs to be coerced by `as.mo()`
|
||||
|
||||
#### Other
|
||||
* Fixed a note thrown by CRAN tests
|
||||
|
||||
# AMR 0.7.0
|
||||
|
||||
#### New
|
||||
* Support for translation of disk diffusion and MIC values to RSI values (i.e. antimicrobial interpretations). Supported guidelines are EUCAST (2011 to 2019) and CLSI (2011 to 2019). Use `as.rsi()` on an MIC value (created with `as.mic()`), a disk diffusion value (created with the new `as.disk()`) or on a complete date set containing columns with MIC or disk diffusion values.
|
||||
* Function `mo_name()` as alias of `mo_fullname()`
|
||||
* Added guidelines of the WHO to determine multi-drug resistance (MDR) for TB (`mdr_tb()`) and added a new vignette about MDR. Read this tutorial [here on our website](https://msberends.gitlab.io/AMR/articles/MDR.html).
|
||||
|
||||
#### Changed
|
||||
* Fixed a critical bug in `first_isolate()` where missing species would lead to incorrect FALSEs. This bug was not present in AMR v0.5.0, but was in v0.6.0 and v0.6.1.
|
||||
* Fixed a bug in `eucast_rules()` where antibiotics from WHONET software would not be recognised
|
||||
* Completely reworked the `antibiotics` data set:
|
||||
* All entries now have 3 different identifiers:
|
||||
* Column `ab` contains a human readable EARS-Net code, used by ECDC and WHO/WHONET - this is the primary identifier used in this package
|
||||
* Column `atc` contains the ATC code, used by WHO/WHOCC
|
||||
* Column `cid` contains the CID code (Compound ID), used by PubChem
|
||||
* Based on the Compound ID, almost 5,000 official brand names have been added from many different countries
|
||||
* All references to antibiotics in our package now use EARS-Net codes, like `AMX` for amoxicillin
|
||||
* Functions `atc_certe`, `ab_umcg` and `atc_trivial_nl` have been removed
|
||||
* All `atc_*` functions are superceded by `ab_*` functions
|
||||
* All output will be translated by using an included translation file which [can be viewed here](https://gitlab.com/msberends/AMR/blob/master/data-raw/translations.tsv).
|
||||
|
||||
Please [create an issue in one of our repositories](https://gitlab.com/msberends/AMR/issues/new?issue[title]=Translation%20suggestion) if you want additions in this file.
|
||||
* Improvements to plotting AMR results with `ggplot_rsi()`:
|
||||
* New parameter `colours` to set the bar colours
|
||||
* New parameters `title`, `subtitle`, `caption`, `x.title` and `y.title` to set titles and axis descriptions
|
||||
* Improved intelligence of looking up antibiotic columns in a data set using `guess_ab_col()`
|
||||
* Added ~5,000 more old taxonomic names to the `microorganisms.old` data set, which leads to better results finding when using the `as.mo()` function
|
||||
* This package now honours the new EUCAST insight (2019) that S and I are but classified as susceptible, where I is defined as 'increased exposure' and not 'intermediate' anymore. For functions like `portion_df()` and `count_df()` this means that their new parameter `combine_SI` is TRUE at default. Our plotting function `ggplot_rsi()` also reflects this change since it uses `count_df()` internally.
|
||||
* The `age()` function gained a new parameter `exact` to determine ages with decimals
|
||||
* Removed deprecated functions `guess_mo()`, `guess_atc()`, `EUCAST_rules()`, `interpretive_reading()`, `rsi()`
|
||||
* Frequency tables (`freq()`):
|
||||
* speed improvement for microbial IDs
|
||||
* fixed factor level names for R Markdown
|
||||
* when all values are unique it now shows a message instead of a warning
|
||||
* support for boxplots:
|
||||
```r
|
||||
septic_patients %>%
|
||||
freq(age) %>%
|
||||
boxplot()
|
||||
# grouped boxplots:
|
||||
septic_patients %>%
|
||||
group_by(hospital_id) %>%
|
||||
freq(age) %>%
|
||||
boxplot()
|
||||
```
|
||||
* Removed all hardcoded EUCAST rules and replaced them with a new reference file which [can be viewed here](https://gitlab.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv).
|
||||
|
||||
Please [create an issue in one of our repositories](https://gitlab.com/msberends/AMR/issues/new?issue[title]=EUCAST%20edit) if you want changes in this file.
|
||||
* Added ceftazidim intrinsic resistance to *Streptococci*
|
||||
* Changed default settings for `age_groups()`, to let groups of fives and tens end with 100+ instead of 120+
|
||||
* Fix for `freq()` for when all values are `NA`
|
||||
* Fix for `first_isolate()` for when dates are missing
|
||||
* Improved speed of `guess_ab_col()`
|
||||
* Function `as.mo()` now gently interprets any number of whitespace characters (like tabs) as one space
|
||||
* Function `as.mo()` now returns `UNKNOWN` for `"con"` (WHONET ID of 'contamination') and returns `NA` for `"xxx"`(WHONET ID of 'no growth')
|
||||
* Small algorithm fix for `as.mo()`
|
||||
* Removed viruses from data set `microorganisms.codes` and cleaned it up
|
||||
* Fix for `mo_shortname()` where species would not be determined correctly
|
||||
|
||||
#### Other
|
||||
* Support for R 3.6.0 and later by providing support for [staged install](https://developer.r-project.org/Blog/public/2019/02/14/staged-install/index.html)
|
||||
|
||||
# AMR 0.6.1
|
||||
|
||||
#### Changed
|
||||
* Fixed a critical bug when using `eucast_rules()` with `verbose = TRUE`
|
||||
* Coercion of microbial IDs are now written to the package namespace instead of the user's home folder, to comply with the CRAN policy
|
||||
|
||||
# AMR 0.6.0
|
||||
|
||||
**New website!**
|
||||
|
||||
We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.gitlab.io/AMR/) (built with the great [`pkgdown`](https://pkgdown.r-lib.org/))
|
||||
|
||||
* Contains the complete manual of this package and all of its functions with an explanation of their parameters
|
||||
* Contains a comprehensive tutorial about how to conduct antimicrobial resistance analysis, import data from WHONET or SPSS and many more.
|
||||
|
||||
#### New
|
||||
* **BREAKING**: removed deprecated functions, parameters and references to 'bactid'. Use `as.mo()` to identify an MO code.
|
||||
* Catalogue of Life as a new taxonomic source for data about microorganisms, which also contains all ITIS data we used previously. The `microorganisms` data set now contains:
|
||||
* All ~55,000 (sub)species from the kingdoms of Archaea, Bacteria and Protozoa
|
||||
* All ~3,000 (sub)species from these orders of the kingdom of Fungi: Eurotiales, Onygenales, Pneumocystales, Saccharomycetales and Schizosaccharomycetales (covering at least like all species of *Aspergillus*, *Candida*, *Pneumocystis*, *Saccharomyces* and *Trichophyton*)
|
||||
* All ~2,000 (sub)species from ~100 other relevant genera, from the kingdoms of Animalia and Plantae (like *Strongyloides* and *Taenia*)
|
||||
* All ~15,000 previously accepted names of included (sub)species that have been taxonomically renamed
|
||||
* The responsible author(s) and year of scientific publication
|
||||
|
||||
This data is updated annually - check the included version with the new function `catalogue_of_life_version()`.
|
||||
* Due to this change, some `mo` codes changed (e.g. *Streptococcus* changed from `B_STRPTC` to `B_STRPT`). A translation table is used internally to support older microorganism IDs, so users will not notice this difference.
|
||||
* New function `mo_rank()` for the taxonomic rank (genus, species, infraspecies, etc.)
|
||||
* New function `mo_url()` to get the direct URL of a species from the Catalogue of Life
|
||||
* Support for data from [WHONET](https://whonet.org/) and [EARS-Net](https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net) (European Antimicrobial Resistance Surveillance Network):
|
||||
* Exported files from WHONET can be read and used in this package. For functions like `first_isolate()` and `eucast_rules()`, all parameters will be filled in automatically.
|
||||
* This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the `antibiotics` data set now contains a column `ears_net`.
|
||||
* The function `as.mo()` now knows all WHONET species abbreviations too, because almost 2,000 microbial abbreviations were added to the `microorganisms.codes` data set.
|
||||
* New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:
|
||||
```r
|
||||
filter_aminoglycosides()
|
||||
filter_carbapenems()
|
||||
filter_cephalosporins()
|
||||
filter_1st_cephalosporins()
|
||||
filter_2nd_cephalosporins()
|
||||
filter_3rd_cephalosporins()
|
||||
filter_4th_cephalosporins()
|
||||
filter_fluoroquinolones()
|
||||
filter_glycopeptides()
|
||||
filter_macrolides()
|
||||
filter_tetracyclines()
|
||||
```
|
||||
The `antibiotics` data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the `antibiotics` data set.
|
||||
For example:
|
||||
```r
|
||||
septic_patients %>% filter_glycopeptides(result = "R")
|
||||
# Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R
|
||||
septic_patients %>% filter_glycopeptides(result = "R", scope = "all")
|
||||
# Filtering on glycopeptide antibacterials: all of `vanc` and `teic` is R
|
||||
```
|
||||
* All `ab_*` functions are deprecated and replaced by `atc_*` functions:
|
||||
```r
|
||||
ab_property -> atc_property()
|
||||
ab_name -> atc_name()
|
||||
ab_official -> atc_official()
|
||||
ab_trivial_nl -> atc_trivial_nl()
|
||||
ab_certe -> atc_certe()
|
||||
ab_umcg -> atc_umcg()
|
||||
ab_tradenames -> atc_tradenames()
|
||||
```
|
||||
These functions use `as.atc()` internally. The old `atc_property` has been renamed `atc_online_property()`. This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class `atc` or must be coerable to this class. Properties of these classes should start with the same class name, analogous to `as.mo()` and e.g. `mo_genus`.
|
||||
* New functions `set_mo_source()` and `get_mo_source()` to use your own predefined MO codes as input for `as.mo()` and consequently all `mo_*` functions
|
||||
* Support for the upcoming [`dplyr`](https://dplyr.tidyverse.org) version 0.8.0
|
||||
* New function `guess_ab_col()` to find an antibiotic column in a table
|
||||
* New function `mo_failures()` to review values that could not be coerced to a valid MO code, using `as.mo()`. This latter function will now only show a maximum of 10 uncoerced values and will refer to `mo_failures()`.
|
||||
* New function `mo_uncertainties()` to review values that could be coerced to a valid MO code using `as.mo()`, but with uncertainty.
|
||||
* New function `mo_renamed()` to get a list of all returned values from `as.mo()` that have had taxonomic renaming
|
||||
* New function `age()` to calculate the (patients) age in years
|
||||
* New function `age_groups()` to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.
|
||||
* New function `ggplot_rsi_predict()` as well as the base R `plot()` function can now be used for resistance prediction calculated with `resistance_predict()`:
|
||||
```r
|
||||
x <- resistance_predict(septic_patients, col_ab = "amox")
|
||||
plot(x)
|
||||
ggplot_rsi_predict(x)
|
||||
```
|
||||
* Functions `filter_first_isolate()` and `filter_first_weighted_isolate()` to shorten and fasten filtering on data sets with antimicrobial results, e.g.:
|
||||
```r
|
||||
septic_patients %>% filter_first_isolate(...)
|
||||
# or
|
||||
filter_first_isolate(septic_patients, ...)
|
||||
```
|
||||
is equal to:
|
||||
```r
|
||||
septic_patients %>%
|
||||
mutate(only_firsts = first_isolate(septic_patients, ...)) %>%
|
||||
filter(only_firsts == TRUE) %>%
|
||||
select(-only_firsts)
|
||||
```
|
||||
* New function `availability()` to check the number of available (non-empty) results in a `data.frame`
|
||||
* New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the *G*-test and more. These are also available (and even easier readable) on our website: https://msberends.gitlab.io/AMR.
|
||||
|
||||
#### Changed
|
||||
* Function `eucast_rules()`:
|
||||
* Updated EUCAST Clinical breakpoints to [version 9.0 of 1 January 2019](http://www.eucast.org/clinical_breakpoints/), the data set `septic_patients` now reflects these changes
|
||||
* Fixed a critical bug where some rules that depend on previous applied rules would not be applied adequately
|
||||
* Emphasised in manual that penicillin is meant as benzylpenicillin (ATC [J01CE01](https://www.whocc.no/atc_ddd_index/?code=J01CE01))
|
||||
* New info is returned when running this function, stating exactly what has been changed or added. Use `eucast_rules(..., verbose = TRUE)` to get a data set with all changed per bug and drug combination.
|
||||
* Removed data sets `microorganisms.oldDT`, `microorganisms.prevDT`, `microorganisms.unprevDT` and `microorganismsDT` since they were no longer needed and only contained info already available in the `microorganisms` data set
|
||||
* Added 65 antibiotics to the `antibiotics` data set, from the [Pharmaceuticals Community Register](http://ec.europa.eu/health/documents/community-register/html/atc.htm) of the European Commission
|
||||
* Removed columns `atc_group1_nl` and `atc_group2_nl` from the `antibiotics` data set
|
||||
* Functions `atc_ddd()` and `atc_groups()` have been renamed `atc_online_ddd()` and `atc_online_groups()`. The old functions are deprecated and will be removed in a future version.
|
||||
* Function `guess_mo()` is now deprecated in favour of `as.mo()` and will be removed in future versions
|
||||
* Function `guess_atc()` is now deprecated in favour of `as.atc()` and will be removed in future versions
|
||||
* Improvements for `as.mo()`:
|
||||
* Now handles incorrect spelling, like `i` instead of `y` and `f` instead of `ph`:
|
||||
```r
|
||||
# mo_fullname() uses as.mo() internally
|
||||
|
||||
mo_fullname("Sthafilokockus aaureuz")
|
||||
#> [1] "Staphylococcus aureus"
|
||||
|
||||
mo_fullname("S. klossi")
|
||||
#> [1] "Staphylococcus kloosii"
|
||||
```
|
||||
* Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default `allow_uncertain = TRUE` is equal to uncertainty level 2. Run `?as.mo` for more info about these levels.
|
||||
```r
|
||||
# equal:
|
||||
as.mo(..., allow_uncertain = TRUE)
|
||||
as.mo(..., allow_uncertain = 2)
|
||||
|
||||
# also equal:
|
||||
as.mo(..., allow_uncertain = FALSE)
|
||||
as.mo(..., allow_uncertain = 0)
|
||||
```
|
||||
Using `as.mo(..., allow_uncertain = 3)` could lead to very unreliable results.
|
||||
* Implemented the latest publication of Becker *et al.* (2019), for categorising coagulase-negative *Staphylococci*
|
||||
* All microbial IDs that found are now saved to a local file `~/.Rhistory_mo`. Use the new function `clean_mo_history()` to delete this file, which resets the algorithms.
|
||||
* Incoercible results will now be considered 'unknown', MO code `UNKNOWN`. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:
|
||||
```r
|
||||
mo_genus("qwerty", language = "es")
|
||||
# Warning:
|
||||
# one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.
|
||||
#> [1] "(género desconocido)"
|
||||
```
|
||||
* Fix for vector containing only empty values
|
||||
* Finds better results when input is in other languages
|
||||
* Better handling for subspecies
|
||||
* Better handling for *Salmonellae*, especially the 'city like' serovars like *Salmonella London*
|
||||
* Understanding of highly virulent *E. coli* strains like EIEC, EPEC and STEC
|
||||
* There will be looked for uncertain results at default - these results will be returned with an informative warning
|
||||
* Manual (help page) now contains more info about the algorithms
|
||||
* Progress bar will be shown when it takes more than 3 seconds to get results
|
||||
* Support for formatted console text
|
||||
* Console will return the percentage of uncoercable input
|
||||
* Function `first_isolate()`:
|
||||
* Fixed a bug where distances between dates would not be calculated right - in the `septic_patients` data set this yielded a difference of 0.15% more isolates
|
||||
* Will now use a column named like "patid" for the patient ID (parameter `col_patientid`), when this parameter was left blank
|
||||
* Will now use a column named like "key(...)ab" or "key(...)antibiotics" for the key antibiotics (parameter `col_keyantibiotics()`), when this parameter was left blank
|
||||
* Removed parameter `output_logical`, the function will now always return a logical value
|
||||
* Renamed parameter `filter_specimen` to `specimen_group`, although using `filter_specimen` will still work
|
||||
* A note to the manual pages of the `portion` functions, that low counts can influence the outcome and that the `portion` functions may camouflage this, since they only return the portion (albeit being dependent on the `minimum` parameter)
|
||||
* Merged data sets `microorganisms.certe` and `microorganisms.umcg` into `microorganisms.codes`
|
||||
* Function `mo_taxonomy()` now contains the kingdom too
|
||||
* Reduce false positives for `is.rsi.eligible()` using the new `threshold` parameter
|
||||
* New colours for `scale_rsi_colours()`
|
||||
* Summaries of class `mo` will now return the top 3 and the unique count, e.g. using `summary(mo)`
|
||||
* Small text updates to summaries of class `rsi` and `mic`
|
||||
* Function `as.rsi()`:
|
||||
* Now gives a warning when inputting MIC values
|
||||
* Now accepts high and low resistance: `"HIGH S"` will return `S`
|
||||
* Frequency tables (`freq()` function):
|
||||
* Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:
|
||||
```r
|
||||
# Determine genus of microorganisms (mo) in `septic_patients` data set:
|
||||
# OLD WAY
|
||||
septic_patients %>%
|
||||
mutate(genus = mo_genus(mo)) %>%
|
||||
freq(genus)
|
||||
# NEW WAY
|
||||
septic_patients %>%
|
||||
freq(mo_genus(mo))
|
||||
|
||||
# Even supports grouping variables:
|
||||
septic_patients %>%
|
||||
group_by(gender) %>%
|
||||
freq(mo_genus(mo))
|
||||
```
|
||||
* Header info is now available as a list, with the `header` function
|
||||
* The parameter `header` is now set to `TRUE` at default, even for markdown
|
||||
* Added header info for class `mo` to show unique count of families, genera and species
|
||||
* Now honours the `decimal.mark` setting, which just like `format` defaults to `getOption("OutDec")`
|
||||
* The new `big.mark` parameter will at default be `","` when `decimal.mark = "."` and `"."` otherwise
|
||||
* Fix for header text where all observations are `NA`
|
||||
* New parameter `droplevels` to exclude empty factor levels when input is a factor
|
||||
* Factor levels will be in header when present in input data (maximum of 5)
|
||||
* Fix for using `select()` on frequency tables
|
||||
* Function `scale_y_percent()` now contains the `limits` parameter
|
||||
* Automatic parameter filling for `mdro()`, `key_antibiotics()` and `eucast_rules()`
|
||||
* Updated examples for resistance prediction (`resistance_predict()` function)
|
||||
* Fix for `as.mic()` to support more values ending in (several) zeroes
|
||||
* if using different lengths of pattern and x in `%like%`, it will now return the call
|
||||
|
||||
#### Other
|
||||
* Updated licence text to emphasise GPL 2.0 and that this is an R package.
|
||||
|
||||
# AMR 0.5.0
|
||||
|
||||
#### New
|
||||
* Repository moved to GitLab: https://gitlab.com/msberends/AMR
|
||||
* Function `count_all` to get all available isolates (that like all `portion_*` and `count_*` functions also supports `summarise` and `group_by`), the old `n_rsi` is now an alias of `count_all`
|
||||
* Function `get_locale` to determine language for language-dependent output for some `mo_*` functions. This is now the default value for their `language` parameter, by which the system language will be used at default.
|
||||
* Data sets `microorganismsDT`, `microorganisms.prevDT`, `microorganisms.unprevDT` and `microorganisms.oldDT` to improve the speed of `as.mo`. They are for reference only, since they are primarily for internal use of `as.mo`.
|
||||
* Function `read.4D` to read from the 4D database of the MMB department of the UMCG
|
||||
* Functions `mo_authors` and `mo_year` to get specific values about the scientific reference of a taxonomic entry
|
||||
|
||||
#### Changed
|
||||
* Functions `MDRO`, `BRMO`, `MRGN` and `EUCAST_exceptional_phenotypes` were renamed to `mdro`, `brmo`, `mrgn` and `eucast_exceptional_phenotypes`
|
||||
* `EUCAST_rules` was renamed to `eucast_rules`, the old function still exists as a deprecated function
|
||||
* Big changes to the `eucast_rules` function:
|
||||
* Now also applies rules from the EUCAST 'Breakpoint tables for bacteria', version 8.1, 2018, http://www.eucast.org/clinical_breakpoints/ (see Source of the function)
|
||||
* New parameter `rules` to specify which rules should be applied (expert rules, breakpoints, others or all)
|
||||
* New parameter `verbose` which can be set to `TRUE` to get very specific messages about which columns and rows were affected
|
||||
* Better error handling when rules cannot be applied (i.e. new values could not be inserted)
|
||||
* The number of affected values will now only be measured once per row/column combination
|
||||
* Data set `septic_patients` now reflects these changes
|
||||
* Added parameter `pipe` for piperacillin (J01CA12), also to the `mdro` function
|
||||
* Small fixes to EUCAST clinical breakpoint rules
|
||||
* Added column `kingdom` to the microorganisms data set, and function `mo_kingdom` to look up values
|
||||
* Tremendous speed improvement for `as.mo` (and subsequently all `mo_*` functions), as empty values wil be ignored *a priori*
|
||||
* Fewer than 3 characters as input for `as.mo` will return NA
|
||||
* Function `as.mo` (and all `mo_*` wrappers) now supports genus abbreviations with "species" attached
|
||||
```r
|
||||
as.mo("E. species") # B_ESCHR
|
||||
mo_fullname("E. spp.") # "Escherichia species"
|
||||
as.mo("S. spp") # B_STPHY
|
||||
mo_fullname("S. species") # "Staphylococcus species"
|
||||
```
|
||||
* Added parameter `combine_IR` (TRUE/FALSE) to functions `portion_df` and `count_df`, to indicate that all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)
|
||||
* Fix for `portion_*(..., as_percent = TRUE)` when minimal number of isolates would not be met
|
||||
* Added parameter `also_single_tested` for `portion_*` and `count_*` functions to also include cases where not all antibiotics were tested but at least one of the tested antibiotics includes the target antimicribial interpretation, see `?portion`
|
||||
* Using `portion_*` functions now throws a warning when total available isolate is below parameter `minimum`
|
||||
* Functions `as.mo`, `as.rsi`, `as.mic`, `as.atc` and `freq` will not set package name as attribute anymore
|
||||
* Frequency tables - `freq()`:
|
||||
* Support for grouping variables, test with:
|
||||
```r
|
||||
septic_patients %>%
|
||||
group_by(hospital_id) %>%
|
||||
freq(gender)
|
||||
```
|
||||
* Support for (un)selecting columns:
|
||||
```r
|
||||
septic_patients %>%
|
||||
freq(hospital_id) %>%
|
||||
select(-count, -cum_count) # only get item, percent, cum_percent
|
||||
```
|
||||
* Check for `hms::is.hms`
|
||||
* Now prints in markdown at default in non-interactive sessions
|
||||
* No longer adds the factor level column and sorts factors on count again
|
||||
* Support for class `difftime`
|
||||
* New parameter `na`, to choose which character to print for empty values
|
||||
* New parameter `header` to turn the header info off (default when `markdown = TRUE`)
|
||||
* New parameter `title` to manually setbthe title of the frequency table
|
||||
* `first_isolate` now tries to find columns to use as input when parameters are left blank
|
||||
* Improvements for MDRO algorithm (function `mdro`)
|
||||
* Data set `septic_patients` is now a `data.frame`, not a tibble anymore
|
||||
* Removed diacritics from all authors (columns `microorganisms$ref` and `microorganisms.old$ref`) to comply with CRAN policy to only allow ASCII characters
|
||||
* Fix for `mo_property` not working properly
|
||||
* Fix for `eucast_rules` where some Streptococci would become ceftazidime R in EUCAST rule 4.5
|
||||
* Support for named vectors of class `mo`, useful for `top_freq()`
|
||||
* `ggplot_rsi` and `scale_y_percent` have `breaks` parameter
|
||||
* AI improvements for `as.mo`:
|
||||
* `"CRS"` -> *Stenotrophomonas maltophilia*
|
||||
* `"CRSM"` -> *Stenotrophomonas maltophilia*
|
||||
* `"MSSA"` -> *Staphylococcus aureus*
|
||||
* `"MSSE"` -> *Staphylococcus epidermidis*
|
||||
* Fix for `join` functions
|
||||
* Speed improvement for `is.rsi.eligible`, now 15-20 times faster
|
||||
* In `g.test`, when `sum(x)` is below 1000 or any of the expected values is below 5, Fisher's Exact Test will be suggested
|
||||
* `ab_name` will try to fall back on `as.atc` when no results are found
|
||||
* Removed the addin to view data sets
|
||||
* Percentages will now will rounded more logically (e.g. in `freq` function)
|
||||
|
||||
#### Other
|
||||
* New dependency on package `crayon`, to support formatted text in the console
|
||||
* Dependency `tidyr` is now mandatory (went to `Import` field) since `portion_df` and `count_df` rely on it
|
||||
* Updated vignettes to comply with README
|
||||
|
||||
|
||||
# AMR 0.4.0
|
||||
|
||||
#### New
|
||||
* The data set `microorganisms` now contains **all microbial taxonomic data from ITIS** (kingdoms Bacteria, Fungi and Protozoa), the Integrated Taxonomy Information System, available via https://itis.gov. The data set now contains more than 18,000 microorganisms with all known bacteria, fungi and protozoa according ITIS with genus, species, subspecies, family, order, class, phylum and subkingdom. The new data set `microorganisms.old` contains all previously known taxonomic names from those kingdoms.
|
||||
* New functions based on the existing function `mo_property`:
|
||||
* Taxonomic names: `mo_phylum`, `mo_class`, `mo_order`, `mo_family`, `mo_genus`, `mo_species`, `mo_subspecies`
|
||||
* Semantic names: `mo_fullname`, `mo_shortname`
|
||||
* Microbial properties: `mo_type`, `mo_gramstain`
|
||||
* Author and year: `mo_ref`
|
||||
|
||||
They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:
|
||||
```r
|
||||
mo_gramstain("E. coli")
|
||||
# [1] "Gram negative"
|
||||
mo_gramstain("E. coli", language = "de") # German
|
||||
# [1] "Gramnegativ"
|
||||
mo_gramstain("E. coli", language = "es") # Spanish
|
||||
# [1] "Gram negativo"
|
||||
mo_fullname("S. group A", language = "pt") # Portuguese
|
||||
# [1] "Streptococcus grupo A"
|
||||
```
|
||||
|
||||
Furthermore, former taxonomic names will give a note about the current taxonomic name:
|
||||
```r
|
||||
mo_gramstain("Esc blattae")
|
||||
# Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)
|
||||
# [1] "Gram negative"
|
||||
```
|
||||
* Functions `count_R`, `count_IR`, `count_I`, `count_SI` and `count_S` to selectively count resistant or susceptible isolates
|
||||
* Extra function `count_df` (which works like `portion_df`) to get all counts of S, I and R of a data set with antibiotic columns, with support for grouped variables
|
||||
* Function `is.rsi.eligible` to check for columns that have valid antimicrobial results, but do not have the `rsi` class yet. Transform the columns of your raw data with: `data %>% mutate_if(is.rsi.eligible, as.rsi)`
|
||||
* Functions `as.mo` and `is.mo` as replacements for `as.bactid` and `is.bactid` (since the `microoganisms` data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The `as.mo` function determines microbial IDs using intelligent rules:
|
||||
```r
|
||||
as.mo("E. coli")
|
||||
# [1] B_ESCHR_COL
|
||||
as.mo("MRSA")
|
||||
# [1] B_STPHY_AUR
|
||||
as.mo("S group A")
|
||||
# [1] B_STRPTC_GRA
|
||||
```
|
||||
And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:
|
||||
```r
|
||||
thousands_of_E_colis <- rep("E. coli", 25000)
|
||||
microbenchmark::microbenchmark(as.mo(thousands_of_E_colis), unit = "s")
|
||||
# Unit: seconds
|
||||
# min median max neval
|
||||
# 0.01817717 0.01843957 0.03878077 100
|
||||
```
|
||||
* Added parameter `reference_df` for `as.mo`, so users can supply their own microbial IDs, name or codes as a reference table
|
||||
* Renamed all previous references to `bactid` to `mo`, like:
|
||||
* Column names inputs of `EUCAST_rules`, `first_isolate` and `key_antibiotics`
|
||||
* Column names of datasets `microorganisms` and `septic_patients`
|
||||
* All old syntaxes will still work with this version, but will throw warnings
|
||||
* Function `labels_rsi_count` to print datalabels on a RSI `ggplot2` model
|
||||
* Functions `as.atc` and `is.atc` to transform/look up antibiotic ATC codes as defined by the WHO. The existing function `guess_atc` is now an alias of `as.atc`.
|
||||
|
||||
* Function `ab_property` and its aliases: `ab_name`, `ab_tradenames`, `ab_certe`, `ab_umcg` and `ab_trivial_nl`
|
||||
* Introduction to AMR as a vignette
|
||||
* Removed clipboard functions as it violated the CRAN policy
|
||||
* Renamed `septic_patients$sex` to `septic_patients$gender`
|
||||
|
||||
#### Changed
|
||||
* Added three antimicrobial agents to the `antibiotics` data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)
|
||||
* Added 163 trade names to the `antibiotics` data set, it now contains 298 different trade names in total, e.g.:
|
||||
```r
|
||||
ab_official("Bactroban")
|
||||
# [1] "Mupirocin"
|
||||
ab_name(c("Bactroban", "Amoxil", "Zithromax", "Floxapen"))
|
||||
# [1] "Mupirocin" "Amoxicillin" "Azithromycin" "Flucloxacillin"
|
||||
ab_atc(c("Bactroban", "Amoxil", "Zithromax", "Floxapen"))
|
||||
# [1] "R01AX06" "J01CA04" "J01FA10" "J01CF05"
|
||||
```
|
||||
* For `first_isolate`, rows will be ignored when there's no species available
|
||||
* Function `ratio` is now deprecated and will be removed in a future release, as it is not really the scope of this package
|
||||
* Fix for `as.mic` for values ending in zeroes after a real number
|
||||
* Small fix where *B. fragilis* would not be found in the `microorganisms.umcg` data set
|
||||
* Added `prevalence` column to the `microorganisms` data set
|
||||
* Added parameters `minimum` and `as_percent` to `portion_df`
|
||||
* Support for quasiquotation in the functions series `count_*` and `portions_*`, and `n_rsi`. This allows to check for more than 2 vectors or columns.
|
||||
```r
|
||||
septic_patients %>% select(amox, cipr) %>% count_IR()
|
||||
# which is the same as:
|
||||
septic_patients %>% count_IR(amox, cipr)
|
||||
|
||||
septic_patients %>% portion_S(amcl)
|
||||
septic_patients %>% portion_S(amcl, gent)
|
||||
septic_patients %>% portion_S(amcl, gent, pita)
|
||||
```
|
||||
* Edited `ggplot_rsi` and `geom_rsi` so they can cope with `count_df`. The new `fun` parameter has value `portion_df` at default, but can be set to `count_df`.
|
||||
* Fix for `ggplot_rsi` when the `ggplot2` package was not loaded
|
||||
* Added datalabels function `labels_rsi_count` to `ggplot_rsi`
|
||||
* Added possibility to set any parameter to `geom_rsi` (and `ggplot_rsi`) so you can set your own preferences
|
||||
* Fix for joins, where predefined suffices would not be honoured
|
||||
* Added parameter `quote` to the `freq` function
|
||||
* Added generic function `diff` for frequency tables
|
||||
* Added longest en shortest character length in the frequency table (`freq`) header of class `character`
|
||||
* Support for types (classes) list and matrix for `freq`
|
||||
```r
|
||||
my_matrix = with(septic_patients, matrix(c(age, gender), ncol = 2))
|
||||
freq(my_matrix)
|
||||
```
|
||||
For lists, subsetting is possible:
|
||||
```r
|
||||
my_list = list(age = septic_patients$age, gender = septic_patients$gender)
|
||||
my_list %>% freq(age)
|
||||
my_list %>% freq(gender)
|
||||
```
|
||||
|
||||
#### Other
|
||||
* More unit tests to ensure better integrity of functions
|
||||
|
||||
# AMR 0.3.0
|
||||
|
||||
#### New
|
||||
* **BREAKING**: `rsi_df` was removed in favour of new functions `portion_R`, `portion_IR`, `portion_I`, `portion_SI` and `portion_S` to selectively calculate resistance or susceptibility. These functions are 20 to 30 times faster than the old `rsi` function. The old function still works, but is deprecated.
|
||||
* New function `portion_df` to get all portions of S, I and R of a data set with antibiotic columns, with support for grouped variables
|
||||
* **BREAKING**: the methodology for determining first weighted isolates was changed. The antibiotics that are compared between isolates (call *key antibiotics*) to include more first isolates (afterwards called first *weighted* isolates) are now as follows:
|
||||
* Universal: amoxicillin, amoxicillin/clavlanic acid, cefuroxime, piperacillin/tazobactam, ciprofloxacin, trimethoprim/sulfamethoxazole
|
||||
* Gram-positive: vancomycin, teicoplanin, tetracycline, erythromycin, oxacillin, rifampicin
|
||||
* Gram-negative: gentamicin, tobramycin, colistin, cefotaxime, ceftazidime, meropenem
|
||||
* Support for `ggplot2`
|
||||
* New functions `geom_rsi`, `facet_rsi`, `scale_y_percent`, `scale_rsi_colours` and `theme_rsi`
|
||||
* New wrapper function `ggplot_rsi` to apply all above functions on a data set:
|
||||
* `septic_patients %>% select(tobr, gent) %>% ggplot_rsi` will show portions of S, I and R immediately in a pretty plot
|
||||
* Support for grouped variables, see `?ggplot_rsi`
|
||||
* Determining bacterial ID:
|
||||
* New functions `as.bactid` and `is.bactid` to transform/ look up microbial ID's.
|
||||
* The existing function `guess_bactid` is now an alias of `as.bactid`
|
||||
* New Becker classification for *Staphylococcus* to categorise them into Coagulase Negative *Staphylococci* (CoNS) and Coagulase Positve *Staphylococci* (CoPS)
|
||||
* New Lancefield classification for *Streptococcus* to categorise them into Lancefield groups
|
||||
* For convience, new descriptive statistical functions `kurtosis` and `skewness` that are lacking in base R - they are generic functions and have support for vectors, data.frames and matrices
|
||||
* Function `g.test` to perform the Χ<sup>2</sup> distributed [*G*-test](https://en.wikipedia.org/wiki/G-test), which use is the same as `chisq.test`
|
||||
* ~~Function `ratio` to transform a vector of values to a preset ratio~~
|
||||
* ~~For example: `ratio(c(10, 500, 10), ratio = "1:2:1")` would return `130, 260, 130`~~
|
||||
* Support for Addins menu in RStudio to quickly insert `%in%` or `%like%` (and give them keyboard shortcuts), or to view the datasets that come with this package
|
||||
* Function `p.symbol` to transform p values to their related symbols: `0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1`
|
||||
* Functions `clipboard_import` and `clipboard_export` as helper functions to quickly copy and paste from/to software like Excel and SPSS. These functions use the `clipr` package, but are a little altered to also support headless Linux servers (so you can use it in RStudio Server)
|
||||
* New for frequency tables (function `freq`):
|
||||
* A vignette to explain its usage
|
||||
* Support for `rsi` (antimicrobial resistance) to use as input
|
||||
* Support for `table` to use as input: `freq(table(x, y))`
|
||||
* Support for existing functions `hist` and `plot` to use a frequency table as input: `hist(freq(df$age))`
|
||||
* Support for `as.vector`, `as.data.frame`, `as_tibble` and `format`
|
||||
* Support for quasiquotation: `freq(mydata, mycolumn)` is the same as `mydata %>% freq(mycolumn)`
|
||||
* Function `top_freq` function to return the top/below *n* items as vector
|
||||
* Header of frequency tables now also show Mean Absolute Deviaton (MAD) and Interquartile Range (IQR)
|
||||
* Possibility to globally set the default for the amount of items to print, with `options(max.print.freq = n)` where *n* is your preset value
|
||||
|
||||
#### Changed
|
||||
* Improvements for forecasting with `resistance_predict` and added more examples
|
||||
* More antibiotics added as parameters for EUCAST rules
|
||||
* Updated version of the `septic_patients` data set to better reflect the reality
|
||||
* Pretty printing for tibbles removed as it is not really the scope of this package
|
||||
* Printing of `mic` and `rsi` classes now returns all values - use `freq` to check distributions
|
||||
* Improved speed of key antibiotics comparison for determining first isolates
|
||||
* Column names for the `key_antibiotics` function are now generic: 6 for broadspectrum ABs, 6 for Gram-positive specific and 6 for Gram-negative specific ABs
|
||||
* Speed improvement for the `abname` function
|
||||
* `%like%` now supports multiple patterns
|
||||
* Frequency tables are now actual `data.frame`s with altered console printing to make it look like a frequency table. Because of this, the parameter `toConsole` is not longer needed.
|
||||
* Fix for `freq` where the class of an item would be lost
|
||||
* Small translational improvements to the `septic_patients` dataset and the column `bactid` now has the new class `"bactid"`
|
||||
* Small improvements to the `microorganisms` dataset (especially for *Salmonella*) and the column `bactid` now has the new class `"bactid"`
|
||||
* Combined MIC/RSI values will now be coerced by the `rsi` and `mic` functions:
|
||||
* `as.rsi("<=0.002; S")` will return `S`
|
||||
* `as.mic("<=0.002; S")` will return `<=0.002`
|
||||
* Now possible to coerce MIC values with a space between operator and value, i.e. `as.mic("<= 0.002")` now works
|
||||
* Classes `rsi` and `mic` do not add the attribute `package.version` anymore
|
||||
* Added `"groups"` option for `atc_property(..., property)`. It will return a vector of the ATC hierarchy as defined by the [WHO](https://www.whocc.no/atc/structure_and_principles/). The new function `atc_groups` is a convenient wrapper around this.
|
||||
* Build-in host check for `atc_property` as it requires the host set by `url` to be responsive
|
||||
* Improved `first_isolate` algorithm to exclude isolates where bacteria ID or genus is unavailable
|
||||
* Fix for warning *hybrid evaluation forced for row_number* ([`924b62`](https://github.com/tidyverse/dplyr/commit/924b62)) from the `dplyr` package v0.7.5 and above
|
||||
* Support for empty values and for 1 or 2 columns as input for `guess_bactid` (now called `as.bactid`)
|
||||
* So `yourdata %>% select(genus, species) %>% as.bactid()` now also works
|
||||
* Other small fixes
|
||||
|
||||
#### Other
|
||||
* Added integration tests (check if everything works as expected) for all releases of R 3.1 and higher
|
||||
* Linux and macOS: https://travis-ci.org/msberends/AMR
|
||||
* Windows: https://ci.appveyor.com/project/msberends/amr
|
||||
* Added thesis advisors to DESCRIPTION file
|
||||
|
||||
# AMR 0.2.0
|
||||
|
||||
#### New
|
||||
* Full support for Windows, Linux and macOS
|
||||
* Full support for old R versions, only R-3.0.0 (April 2013) or later is needed (needed packages may have other dependencies)
|
||||
* Function `n_rsi` to count cases where antibiotic test results were available, to be used in conjunction with `dplyr::summarise`, see ?rsi
|
||||
* Function `guess_bactid` to **determine the ID** of a microorganism based on genus/species or known abbreviations like MRSA
|
||||
* Function `guess_atc` to **determine the ATC** of an antibiotic based on name, trade name, or known abbreviations
|
||||
* Function `freq` to create **frequency tables**, with additional info in a header
|
||||
* Function `MDRO` to **determine Multi Drug Resistant Organisms (MDRO)** with support for country-specific guidelines.
|
||||
* [Exceptional resistances defined by EUCAST](http://www.eucast.org/expert_rules_and_intrinsic_resistance) are also supported instead of countries alone
|
||||
* Functions `BRMO` and `MRGN` are wrappers for Dutch and German guidelines, respectively
|
||||
* New algorithm to determine weighted isolates, can now be `"points"` or `"keyantibiotics"`, see `?first_isolate`
|
||||
* New print format for `tibble`s and `data.table`s
|
||||
|
||||
#### Changed
|
||||
* Fixed `rsi` class for vectors that contain only invalid antimicrobial interpretations
|
||||
* Renamed dataset `ablist` to `antibiotics`
|
||||
* Renamed dataset `bactlist` to `microorganisms`
|
||||
* Added common abbreviations and trade names to the `antibiotics` dataset
|
||||
* Added more microorganisms to the `microorganisms` dataset
|
||||
* Added analysis examples on help page of dataset `septic_patients`
|
||||
* Added support for character vector in `join` functions
|
||||
* Added warnings when a join results in more rows after than before the join
|
||||
* Altered `%like%` to make it case insensitive
|
||||
* For parameters of functions `first_isolate` and `EUCAST_rules` column names are now case-insensitive
|
||||
* Functions `as.rsi` and `as.mic` now add the package name and version as attributes
|
||||
|
||||
#### Other
|
||||
* Expanded `README.md` with more examples
|
||||
* Added [ORCID](https://orcid.org) of authors to DESCRIPTION file
|
||||
* Added unit testing with the `testthat` package
|
||||
* Added build tests for Linux and macOS using Travis CI (https://travis-ci.org/msberends/AMR)
|
||||
* Added line coverage checking using CodeCov (https://codecov.io/gh/msberends/AMR/tree/master/R)
|
||||
|
||||
# AMR 0.1.1
|
||||
|
||||
* `EUCAST_rules` applies for amoxicillin even if ampicillin is missing
|
||||
* Edited column names to comply with GLIMS, the laboratory information system
|
||||
* Added more valid MIC values
|
||||
* Renamed 'Daily Defined Dose' to 'Defined Daily Dose'
|
||||
* Added barplots for `rsi` and `mic` classes
|
||||
|
||||
# AMR 0.1.0
|
||||
|
||||
* First submission to CRAN.
|
||||
@@ -1,384 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Transform to antibiotic ID
|
||||
#'
|
||||
#' Use this function to determine the antibiotic code of one or more antibiotics. The data set \code{\link{antibiotics}} will be searched for abbreviations, official names and synonyms (brand names).
|
||||
#' @param x character vector to determine to antibiotic ID
|
||||
#' @param ... arguments passed on to internal functions
|
||||
#' @rdname as.ab
|
||||
#' @keywords atc
|
||||
#' @inheritSection WHOCC WHOCC
|
||||
#' @export
|
||||
#' @importFrom dplyr %>% filter slice pull
|
||||
#' @details All entries in the \code{\link{antibiotics}} data set have three different identifiers: a human readable EARS-Net code (column \code{ab}, used by ECDC and WHONET), an ATC code (column \code{atc}, used by WHO), and a CID code (column \code{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.
|
||||
#'
|
||||
#' Use the \code{\link{ab_property}} functions to get properties based on the returned antibiotic ID, see Examples.
|
||||
#' @section Source:
|
||||
#' World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/}
|
||||
#'
|
||||
#' WHONET 2019 software: \url{http://www.whonet.org/software.html}
|
||||
#'
|
||||
#' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}
|
||||
#' @return Character (vector) with class \code{"ab"}. Unknown values will return \code{NA}.
|
||||
#' @seealso \code{\link{antibiotics}} for the dataframe that is being used to determine ATCs.
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @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
|
||||
#'
|
||||
#' # Use ab_* functions to get a specific properties (see ?ab_property);
|
||||
#' # they use as.ab() internally:
|
||||
#' ab_name("J01FA01") # "Erythromycin"
|
||||
#' ab_name("eryt") # "Erythromycin"
|
||||
as.ab <- function(x, ...) {
|
||||
if (is.ab(x)) {
|
||||
return(x)
|
||||
}
|
||||
|
||||
if (all(toupper(x) %in% AMR::antibiotics$ab)) {
|
||||
# valid AB code, but not yet right class
|
||||
return(structure(.Data = toupper(x),
|
||||
class = "ab"))
|
||||
}
|
||||
|
||||
x_bak <- x
|
||||
# remove diacritics
|
||||
x <- iconv(x, from = "UTF-8", to = "ASCII//TRANSLIT")
|
||||
x <- gsub('"', "", x, fixed = TRUE)
|
||||
# remove suffices
|
||||
x_bak_clean <- gsub("_(mic|rsi|dis[ck])$", "", x, ignore.case = TRUE)
|
||||
# remove disk concentrations, like LVX_NM -> LVX
|
||||
x_bak_clean <- gsub("_[A-Z]{2}[0-9_]{0,3}$", "", x_bak_clean, ignore.case = TRUE)
|
||||
# remove part between brackets if that's followed by another string
|
||||
x_bak_clean <- gsub("(.*)+ [(].*[)]", "\\1", x_bak_clean)
|
||||
# keep only max 1 space
|
||||
x_bak_clean <- trimws(gsub(" +", " ", x_bak_clean, ignore.case = TRUE))
|
||||
# non-character, space or number should be a slash
|
||||
x_bak_clean <- gsub("[^A-Za-z0-9 -]", "/", x_bak_clean)
|
||||
# spaces around non-characters must be removed: amox + clav -> amox/clav
|
||||
x_bak_clean <- gsub("(.*[a-zA-Z0-9]) ([^a-zA-Z0-9].*)", "\\1\\2", x_bak_clean)
|
||||
x_bak_clean <- gsub("(.*[^a-zA-Z0-9]) ([a-zA-Z0-9].*)", "\\1\\2", x_bak_clean)
|
||||
|
||||
x <- unique(x_bak_clean)
|
||||
x_new <- rep(NA_character_, length(x))
|
||||
x_unknown <- character(0)
|
||||
|
||||
for (i in seq_len(length(x))) {
|
||||
if (is.na(x[i]) | is.null(x[i])) {
|
||||
next
|
||||
}
|
||||
if (identical(x[i], "")) {
|
||||
x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
|
||||
next
|
||||
}
|
||||
# prevent "bacteria" from coercing to TMP, since Bacterial is a brand name of it
|
||||
if (identical(tolower(x[i]), "bacteria")) {
|
||||
x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
|
||||
next
|
||||
}
|
||||
|
||||
# exact AB code
|
||||
found <- AMR::antibiotics[which(AMR::antibiotics$ab == toupper(x[i])), ]$ab
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- found[1L]
|
||||
next
|
||||
}
|
||||
|
||||
# exact ATC code
|
||||
found <- AMR::antibiotics[which(AMR::antibiotics$atc == toupper(x[i])), ]$ab
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- found[1L]
|
||||
next
|
||||
}
|
||||
|
||||
# exact CID code
|
||||
found <- AMR::antibiotics[which(AMR::antibiotics$cid == x[i]), ]$ab
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- found[1L]
|
||||
next
|
||||
}
|
||||
|
||||
# exact name
|
||||
found <- AMR::antibiotics[which(toupper(AMR::antibiotics$name) == toupper(x[i])), ]$ab
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- found[1L]
|
||||
next
|
||||
}
|
||||
|
||||
# exact synonym
|
||||
synonym_found <- unlist(lapply(AMR::antibiotics$synonyms,
|
||||
function(s) if (toupper(x[i]) %in% toupper(s)) {
|
||||
TRUE
|
||||
} else {
|
||||
FALSE
|
||||
}))
|
||||
found <- AMR::antibiotics$ab[synonym_found == TRUE]
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- found[1L]
|
||||
next
|
||||
}
|
||||
|
||||
# exact abbreviation
|
||||
abbr_found <- unlist(lapply(AMR::antibiotics$abbreviations,
|
||||
function(a) if (toupper(x[i]) %in% toupper(a)) {
|
||||
TRUE
|
||||
} else {
|
||||
FALSE
|
||||
}))
|
||||
found <- AMR::antibiotics$ab[abbr_found == TRUE]
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- found[1L]
|
||||
next
|
||||
}
|
||||
|
||||
# first >=4 characters of name
|
||||
if (nchar(x[i]) >= 4) {
|
||||
found <- AMR::antibiotics[which(toupper(AMR::antibiotics$name) %like% paste0("^", x[i])), ]$ab
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- found[1L]
|
||||
next
|
||||
}
|
||||
}
|
||||
|
||||
# allow characters that resemble others, but only continue when having more than 3 characters
|
||||
if (nchar(x[i]) <= 3) {
|
||||
x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
|
||||
next
|
||||
}
|
||||
x_spelling <- tolower(x[i])
|
||||
x_spelling <- gsub("[iy]+", "[iy]+", x_spelling)
|
||||
x_spelling <- gsub("(c|k|q|qu|s|z|x|ks)+", "(c|k|q|qu|s|z|x|ks)+", x_spelling)
|
||||
x_spelling <- gsub("(ph|f|v)+", "(ph|f|v)+", x_spelling)
|
||||
x_spelling <- gsub("(th|t)+", "(th|t)+", x_spelling)
|
||||
x_spelling <- gsub("a+", "a+", x_spelling)
|
||||
x_spelling <- gsub("e+", "e+", x_spelling)
|
||||
x_spelling <- gsub("o+", "o+", x_spelling)
|
||||
# allow any ending of -in/-ine and -im/-ime
|
||||
x_spelling <- gsub("(\\[iy\\]\\+(n|m)|\\[iy\\]\\+(n|m)e\\+)$", "[iy]+(n|m)e*", x_spelling)
|
||||
# allow any ending of -ol/-ole
|
||||
x_spelling <- gsub("(o\\+l|o\\+le\\+)$", "o+le*", x_spelling)
|
||||
# allow any ending of -on/-one
|
||||
x_spelling <- gsub("(o\\+n|o\\+ne\\+)$", "o+ne*", x_spelling)
|
||||
# replace multiple same characters to single one with '+', like "ll" -> "l+"
|
||||
x_spelling <- gsub("(.)\\1+", "\\1+", x_spelling)
|
||||
|
||||
# try if name starts with it
|
||||
found <- AMR::antibiotics[which(AMR::antibiotics$name %like% paste0("^", x_spelling)), ]$ab
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- found[1L]
|
||||
next
|
||||
}
|
||||
# and try if any synonym starts with it
|
||||
synonym_found <- unlist(lapply(AMR::antibiotics$synonyms,
|
||||
function(s) if (any(s %like% paste0("^", x_spelling))) {
|
||||
TRUE
|
||||
} else {
|
||||
FALSE
|
||||
}))
|
||||
found <- AMR::antibiotics$ab[synonym_found == TRUE]
|
||||
if (length(found) > 0) {
|
||||
x_new[i] <- found[1L]
|
||||
next
|
||||
}
|
||||
|
||||
# try by removing all spaces
|
||||
if (x[i] %like% " ") {
|
||||
found <- suppressWarnings(as.ab(gsub(" +", "", x[i])))
|
||||
if (length(found) > 0 & !is.na(found)) {
|
||||
x_new[i] <- found[1L]
|
||||
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])))
|
||||
if (length(found) > 0 & !is.na(found)) {
|
||||
x_new[i] <- found[1L]
|
||||
next
|
||||
}
|
||||
}
|
||||
|
||||
if (!isFALSE(list(...)$initial_search)) {
|
||||
# transform back from other languages and try again
|
||||
x_translated <- paste(lapply(strsplit(x[i], "[^a-zA-Z0-9 ]"),
|
||||
function(y) {
|
||||
for (i in seq_len(length(y))) {
|
||||
y[i] <- ifelse(tolower(y[i]) %in% tolower(translations_file$replacement),
|
||||
translations_file[which(tolower(translations_file$replacement) == tolower(y[i]) &
|
||||
!isFALSE(translations_file$fixed)), "pattern"],
|
||||
y[i])
|
||||
}
|
||||
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
|
||||
}
|
||||
|
||||
if (!isFALSE(list(...)$initial_search2)) {
|
||||
# now also try to coerce brandname combinations like "Amoxy/clavulanic acid"
|
||||
x_translated <- paste(lapply(strsplit(x_translated, "[^a-zA-Z0-9 ]"),
|
||||
function(y) {
|
||||
for (i in seq_len(length(y))) {
|
||||
y_name <- suppressWarnings(ab_name(y[i], language = NULL, initial_search = FALSE, initial_search2 = FALSE))
|
||||
y[i] <- ifelse(!is.na(y_name),
|
||||
y_name,
|
||||
y[i])
|
||||
}
|
||||
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
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
# not found
|
||||
x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
|
||||
}
|
||||
|
||||
# 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) {
|
||||
warning("These ATC codes are not (yet) in the antibiotics data set: ",
|
||||
paste('"', sort(unique(x_unknown_ATCs)), '"', sep = "", collapse = ", "),
|
||||
".",
|
||||
call. = FALSE)
|
||||
}
|
||||
|
||||
if (length(x_unknown) > 0) {
|
||||
warning("These values could not be coerced to a valid antimicrobial ID: ",
|
||||
paste('"', sort(unique(x_unknown)), '"', sep = "", collapse = ", "),
|
||||
".",
|
||||
call. = FALSE)
|
||||
}
|
||||
|
||||
x_result <- data.frame(x = x_bak_clean, stringsAsFactors = FALSE) %>%
|
||||
left_join(data.frame(x = x, x_new = x_new, stringsAsFactors = FALSE), by = "x") %>%
|
||||
pull(x_new)
|
||||
|
||||
if (length(x_result) == 0) {
|
||||
x_result <- NA_character_
|
||||
}
|
||||
|
||||
structure(.Data = x_result,
|
||||
class = "ab")
|
||||
}
|
||||
|
||||
#' @rdname as.ab
|
||||
#' @export
|
||||
is.ab <- function(x) {
|
||||
identical(class(x), "ab")
|
||||
}
|
||||
|
||||
#' @exportMethod print.ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
print.ab <- function(x, ...) {
|
||||
cat("Class 'ab'\n")
|
||||
print(as.character(x), quote = FALSE)
|
||||
}
|
||||
|
||||
#' @exportMethod as.data.frame.ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
as.data.frame.ab <- function(x, ...) {
|
||||
# same as as.data.frame.character but with removed stringsAsFactors
|
||||
nm <- paste(deparse(substitute(x), width.cutoff = 500L),
|
||||
collapse = " ")
|
||||
if (!"nm" %in% names(list(...))) {
|
||||
as.data.frame.vector(x, ..., nm = nm)
|
||||
} else {
|
||||
as.data.frame.vector(x, ...)
|
||||
}
|
||||
}
|
||||
|
||||
#' @exportMethod [.ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[.ab" <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
#' @exportMethod [[.ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[[.ab" <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
#' @exportMethod [<-.ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[<-.ab" <- function(i, j, ..., value) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(i)
|
||||
class_integrity_check(y, "antimicrobial code", AMR::antibiotics$ab)
|
||||
}
|
||||
#' @exportMethod [[<-.ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
"[[<-.ab" <- function(i, j, ..., value) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(i)
|
||||
class_integrity_check(y, "antimicrobial code", AMR::antibiotics$ab)
|
||||
}
|
||||
#' @exportMethod c.ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
c.ab <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
class_integrity_check(y, "antimicrobial code", AMR::antibiotics$ab)
|
||||
}
|
||||
|
||||
#' @importFrom pillar type_sum
|
||||
#' @export
|
||||
type_sum.ab <- function(x) {
|
||||
"ab"
|
||||
}
|
||||
|
||||
#' @importFrom pillar pillar_shaft
|
||||
#' @export
|
||||
pillar_shaft.ab <- function(x, ...) {
|
||||
out <- format(x)
|
||||
out[is.na(x)] <- pillar::style_na("NA")
|
||||
pillar::new_pillar_shaft_simple(out, align = "left", min_width = 4)
|
||||
}
|
||||
-206
@@ -1,206 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Property of an antibiotic
|
||||
#'
|
||||
#' Use these functions to return a specific property of an antibiotic from the \code{\link{antibiotics}} data set. All input values will be evaluated internally with \code{\link{as.ab}}.
|
||||
#' @param x any (vector of) text that can be coerced to a valid microorganism code with \code{\link{as.ab}}
|
||||
#' @param tolower 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 \code{\link{antibiotics}} data set
|
||||
#' @param language language of the returned text, defaults to system language (see \code{\link{get_locale}}) and can also be set with \code{\link{getOption}("AMR_locale")}. Use \code{language = NULL} or \code{language = ""} to prevent translation.
|
||||
#' @param administration way of administration, either \code{"oral"} or \code{"iv"}
|
||||
#' @param units a logical to indicate whether the units instead of the DDDs itself must be returned, see Examples
|
||||
#' @param ... other parameters passed on to \code{\link{as.ab}}
|
||||
#' @details All output will be \link{translate}d where possible.
|
||||
#' @inheritSection as.ab Source
|
||||
#' @rdname ab_property
|
||||
#' @name ab_property
|
||||
#' @return \itemize{
|
||||
#' \item{An \code{integer} in case of \code{ab_cid}}
|
||||
#' \item{A named \code{list} in case of \code{ab_info} and multiple \code{ab_synonyms}/\code{ab_tradenames}}
|
||||
#' \item{A \code{double} in case of \code{ab_ddd}}
|
||||
#' \item{A \code{character} in all other cases}
|
||||
#' }
|
||||
#' @export
|
||||
#' @seealso \code{\link{antibiotics}}
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @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_name(x = c("AMC", "PLB")) # "Amoxicillin/clavulanic acid" "Polymyxin B"
|
||||
#' ab_name(x = c("AMC", "PLB"),
|
||||
#' tolower = TRUE) # "amoxicillin/clavulanic acid" "polymyxin B"
|
||||
#'
|
||||
#' ab_ddd("AMX", "oral") # 1
|
||||
#' ab_ddd("AMX", "oral", units = TRUE) # "g"
|
||||
#' ab_ddd("AMX", "iv") # 1
|
||||
#' ab_ddd("AMX", "iv", units = TRUE) # "g"
|
||||
#'
|
||||
#' ab_info("AMX") # all properties as a list
|
||||
#'
|
||||
#' # all ab_* functions use as.ab() internally:
|
||||
#' ab_name("Fluclox") # "Flucloxacillin"
|
||||
#' ab_name("fluklox") # "Flucloxacillin"
|
||||
#' ab_name("floxapen") # "Flucloxacillin"
|
||||
#' ab_name(21319) # "Flucloxacillin" (using CID)
|
||||
#' ab_name("J01CF05") # "Flucloxacillin" (using ATC)
|
||||
ab_name <- function(x, language = get_locale(), tolower = FALSE, ...) {
|
||||
x <- translate_AMR(ab_validate(x = x, property = "name", ...), language = language)
|
||||
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_atc <- function(x, ...) {
|
||||
ab_validate(x = x, property = "atc", ...)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_cid <- function(x, ...) {
|
||||
ab_validate(x = x, property = "cid", ...)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_synonyms <- function(x, ...) {
|
||||
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, ...) {
|
||||
ab_synonyms(x, ...)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_group <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(ab_validate(x = x, property = "group", ...), language = language)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_atc_group1 <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(ab_validate(x = x, property = "atc_group1", ...), language = language)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_atc_group2 <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(ab_validate(x = x, property = "atc_group2", ...), language = language)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_ddd <- function(x, administration = "oral", units = FALSE, ...) {
|
||||
if (!administration %in% c("oral", "iv")) {
|
||||
stop("`administration` must be 'oral' or 'iv'", call. = FALSE)
|
||||
}
|
||||
ddd_prop <- administration
|
||||
if (units == TRUE) {
|
||||
ddd_prop <- paste0(ddd_prop, "_units")
|
||||
} else {
|
||||
ddd_prop <- paste0(ddd_prop, "_ddd")
|
||||
}
|
||||
ab_validate(x = x, property = ddd_prop, ...)
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_info <- function(x, language = get_locale(), ...) {
|
||||
x <- AMR::as.ab(x, ...)
|
||||
base::list(ab = as.character(x),
|
||||
atc = ab_atc(x),
|
||||
cid = ab_cid(x),
|
||||
name = ab_name(x, language = language),
|
||||
group = ab_group(x, language = language),
|
||||
atc_group1 = ab_atc_group1(x, language = language),
|
||||
atc_group2 = ab_atc_group2(x, language = language),
|
||||
tradenames = ab_tradenames(x),
|
||||
ddd = list(oral = list(amount = ab_ddd(x, administration = "oral", units = FALSE),
|
||||
units = ab_ddd(x, administration = "oral", units = TRUE)),
|
||||
iv = list(amount = ab_ddd(x, administration = "iv", units = FALSE),
|
||||
units = ab_ddd(x, administration = "iv", units = TRUE))))
|
||||
}
|
||||
|
||||
#' @rdname ab_property
|
||||
#' @export
|
||||
ab_property <- function(x, property = "name", language = get_locale(), ...) {
|
||||
if (length(property) != 1L) {
|
||||
stop("'property' must be of length 1.")
|
||||
}
|
||||
if (!property %in% colnames(AMR::antibiotics)) {
|
||||
stop("invalid property: '", property, "' - use a column name of the `antibiotics` data set")
|
||||
}
|
||||
|
||||
translate_AMR(ab_validate(x = x, property = property, ...), language = language)
|
||||
}
|
||||
|
||||
ab_validate <- function(x, property, ...) {
|
||||
if (!"AMR" %in% base::.packages()) {
|
||||
library("AMR")
|
||||
# check onLoad() in R/zzz.R: data tables are created there.
|
||||
}
|
||||
|
||||
# try to catch an error when inputting an invalid parameter
|
||||
# so the 'call.' can be set to FALSE
|
||||
tryCatch(x[1L] %in% AMR::antibiotics[1, property],
|
||||
error = function(e) stop(e$message, call. = FALSE))
|
||||
x_bak <- x
|
||||
if (!all(x %in% AMR::antibiotics[, property])) {
|
||||
x <- data.frame(ab = AMR::as.ab(x, ...), stringsAsFactors = FALSE) %>%
|
||||
left_join(AMR::antibiotics, by = "ab") %>%
|
||||
pull(property)
|
||||
}
|
||||
if (property == "ab") {
|
||||
return(structure(x, class = property))
|
||||
} else if (property == "cid") {
|
||||
return(as.integer(x))
|
||||
} else if (property %like% "ddd") {
|
||||
return(as.double(x))
|
||||
} else {
|
||||
# return "(input)" for NAs
|
||||
x[is.na(x) & !is.na(x_bak)] <- paste0("(", x_bak[is.na(x) & !is.na(x_bak)], ")")
|
||||
return(x)
|
||||
}
|
||||
}
|
||||
@@ -1,194 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Age in years of individuals
|
||||
#'
|
||||
#' Calculates age in years based on a reference date, which is the sytem date at default.
|
||||
#' @param x date(s), will be coerced with \code{\link{as.POSIXlt}}
|
||||
#' @param reference reference date(s) (defaults to today), will be coerced with \code{\link{as.POSIXlt}} and cannot be lower than \code{x}
|
||||
#' @param exact a logical to indicate whether age calculation should be exact, i.e. with decimals. It divides the number of days of \href{https://en.wikipedia.org/wiki/Year-to-date}{year-to-date} (YTD) of \code{x} by the number of days in a year of \code{reference} (either 365 or 366).
|
||||
#' @param na.rm a logical to indicate whether missing values should be removed
|
||||
#' @return An integer (no decimals) if \code{exact = FALSE}, a double (with decimals) otherwise
|
||||
#' @seealso To split ages into groups, use the \code{\link{age_groups}} function.
|
||||
#' @importFrom dplyr if_else
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @export
|
||||
#' @examples
|
||||
#' # 10 random birth dates
|
||||
#' df <- data.frame(birth_date = Sys.Date() - runif(10) * 25000)
|
||||
#' # add ages
|
||||
#' df$age <- age(df$birth_date)
|
||||
#' # add exact ages
|
||||
#' df$age_exact <- age(df$birth_date, exact = TRUE)
|
||||
#'
|
||||
#' df
|
||||
age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE) {
|
||||
if (length(x) != length(reference)) {
|
||||
if (length(reference) == 1) {
|
||||
reference <- rep(reference, length(x))
|
||||
} else {
|
||||
stop("`x` and `reference` must be of same length, or `reference` must be of length 1.")
|
||||
}
|
||||
}
|
||||
x <- as.POSIXlt(x)
|
||||
reference <- as.POSIXlt(reference)
|
||||
|
||||
# from https://stackoverflow.com/a/25450756/4575331
|
||||
years_gap <- reference$year - x$year
|
||||
ages <- if_else(reference$mon < x$mon | (reference$mon == x$mon & reference$mday < x$mday),
|
||||
as.integer(years_gap - 1),
|
||||
as.integer(years_gap))
|
||||
|
||||
# add decimals
|
||||
if (exact == TRUE) {
|
||||
# get dates of `x` when `x` would have the year of `reference`
|
||||
x_in_reference_year <- as.POSIXlt(paste0(format(reference, "%Y"), format(x, "-%m-%d")))
|
||||
# get differences in days
|
||||
n_days_x_rest <- as.double(difftime(reference, x_in_reference_year, units = "days"))
|
||||
# get numbers of days the years of `reference` has for a reliable denominator
|
||||
n_days_reference_year <- as.POSIXlt(paste0(format(reference, "%Y"), "-12-31"))$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[mod < 0] <- 1 + mod[mod < 0]
|
||||
# and finally add to ages
|
||||
ages <- ages + mod
|
||||
}
|
||||
|
||||
if (any(ages < 0, na.rm = TRUE)) {
|
||||
ages[ages < 0] <- NA
|
||||
warning("NAs introduced for ages below 0.")
|
||||
}
|
||||
if (any(ages > 120, na.rm = TRUE)) {
|
||||
warning("Some ages are above 120.")
|
||||
}
|
||||
|
||||
if (isTRUE(na.rm)) {
|
||||
ages <- ages[!is.na(ages)]
|
||||
}
|
||||
|
||||
ages
|
||||
}
|
||||
|
||||
#' Split ages into age groups
|
||||
#'
|
||||
#' Split ages into age groups defined by the \code{split} parameter. This allows for easier demographic (antimicrobial resistance) analysis.
|
||||
#' @param x age, e.g. calculated with \code{\link{age}}
|
||||
#' @param split_at values to split \code{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 can be:
|
||||
#' \itemize{
|
||||
#' \item{A numeric vector. A vector of e.g. \code{c(10, 20)} will split on 0-9, 10-19 and 20+. A value of only \code{50} will split 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+).}
|
||||
#' \item{A character:}
|
||||
#' \itemize{
|
||||
#' \item{\code{"children"} or \code{"kids"}, equivalent of: \code{c(0, 1, 2, 4, 6, 13, 18)}. This will split on 0, 1, 2-3, 4-5, 6-12, 13-17 and 18+.}
|
||||
#' \item{\code{"elderly"} or \code{"seniors"}, equivalent of: \code{c(65, 75, 85)}. This will split on 0-64, 65-74, 75-84, 85+.}
|
||||
#' \item{\code{"fives"}, equivalent of: \code{1:20 * 5}. This will split on 0-4, 5-9, 10-14, ..., 90-94, 95-99, 100+.}
|
||||
#' \item{\code{"tens"}, equivalent of: \code{1:10 * 10}. This will split on 0-9, 10-19, 20-29, ... 80-89, 90-99, 100+.}
|
||||
#' }
|
||||
#' }
|
||||
#' @keywords age_group age
|
||||
#' @return Ordered \code{\link{factor}}
|
||||
#' @seealso To determine ages, based on one or more reference dates, use the \code{\link{age}} function.
|
||||
#' @export
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @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, "children")
|
||||
#' # same:
|
||||
#' age_groups(ages, c(1, 2, 4, 6, 13, 17))
|
||||
#'
|
||||
#' # resistance of ciprofloxacine per age group
|
||||
#' library(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")
|
||||
age_groups <- function(x, split_at = c(12, 25, 55, 75), na.rm = FALSE) {
|
||||
if (!is.numeric(x)) {
|
||||
stop("`x` and must be numeric, not a ", paste0(class(x), collapse = "/"), ".")
|
||||
}
|
||||
if (any(x < 0, na.rm = TRUE)) {
|
||||
x[x < 0] <- NA
|
||||
warning("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)]
|
||||
if (length(split_at) == 1) {
|
||||
# only 0 is available
|
||||
stop("invalid value for `split_at`.")
|
||||
}
|
||||
|
||||
# turn input values to 'split_at' indices
|
||||
y <- x
|
||||
labs <- split_at
|
||||
for (i in seq_len(length(split_at))) {
|
||||
y[x >= split_at[i]] <- i
|
||||
# create labels
|
||||
labs[i - 1] <- paste0(unique(c(split_at[i - 1], split_at[i] - 1)), collapse = "-")
|
||||
}
|
||||
|
||||
# last category
|
||||
labs[length(labs)] <- paste0(split_at[length(split_at)], "+")
|
||||
|
||||
agegroups <- factor(labs[y], levels = labs, ordered = TRUE)
|
||||
|
||||
if (isTRUE(na.rm)) {
|
||||
agegroups <- agegroups[!is.na(agegroups)]
|
||||
}
|
||||
|
||||
agegroups
|
||||
}
|
||||
@@ -1,70 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' The \code{AMR} Package
|
||||
#'
|
||||
#' Welcome to the \code{AMR} package.
|
||||
#' @details
|
||||
#' \code{AMR} is a free and open-source R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data.
|
||||
#'
|
||||
#' We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). 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:
|
||||
#' \itemize{
|
||||
#' \item{Reference for microorganisms, since it contains all microbial (sub)species from the Catalogue of Life}
|
||||
#' \item{Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines}
|
||||
#' \item{Calculating antimicrobial resistance}
|
||||
#' \item{Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO)}
|
||||
#' \item{Calculating empirical susceptibility of both mono therapy and combination therapy}
|
||||
#' \item{Predicting future antimicrobial resistance using regression models}
|
||||
#' \item{Getting properties for any microorganism (like Gram stain, species, genus or family)}
|
||||
#' \item{Getting properties for any antibiotic (like name, ATC code, defined daily dose or trade name)}
|
||||
#' \item{Plotting antimicrobial resistance}
|
||||
#' \item{Determining first isolates to be used for AMR analysis}
|
||||
#' \item{Applying EUCAST expert rules}
|
||||
#' \item{Descriptive statistics: frequency tables, kurtosis and skewness}
|
||||
#' }
|
||||
#' @section Authors:
|
||||
#' Matthijs S. Berends[1,2] Christian F. Luz[1], Erwin E.A. Hassing[2], Corinna Glasner[1], Alex W. Friedrich[1], Bhanu N.M. Sinha[1] \cr
|
||||
#'
|
||||
#' [1] Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands - \url{https://www.rug.nl} \url{https://www.umcg.nl} \cr
|
||||
#' [2] Certe Medical Diagnostics & Advice, Groningen, the Netherlands - \url{https://www.certe.nl}
|
||||
|
||||
#' @section Read more on our website!:
|
||||
#' On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
|
||||
#' @section Contact us:
|
||||
#' For suggestions, comments or questions, please contact us at:
|
||||
#'
|
||||
#' Matthijs S. Berends \cr
|
||||
#' m.s.berends [at] umcg [dot] nl \cr
|
||||
#' Department of Medical Microbiology, University of Groningen \cr
|
||||
#' University Medical Center Groningen \cr
|
||||
#' Post Office Box 30001 \cr
|
||||
#' 9700 RB Groningen
|
||||
#'
|
||||
#' If you have found a bug, please file a new issue at: \cr
|
||||
#' \url{https://gitlab.com/msberends/AMR/issues}
|
||||
#' @name AMR
|
||||
#' @rdname AMR
|
||||
#' @importFrom microbenchmark microbenchmark
|
||||
#' @importFrom knitr kable
|
||||
NULL
|
||||
-197
@@ -1,197 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Get ATC properties from WHOCC website
|
||||
#'
|
||||
#' Gets data from the WHO to determine properties of an ATC (e.g. an antibiotic) like name, defined daily dose (DDD) or standard unit. \cr \strong{This function requires an internet connection.}
|
||||
#' @param atc_code a character or character vector with ATC code(s) of antibiotic(s)
|
||||
#' @param property property of an ATC code. Valid values are \code{"ATC"}, \code{"Name"}, \code{"DDD"}, \code{"U"} (\code{"unit"}), \code{"Adm.R"}, \code{"Note"} and \code{groups}. For this last option, all hierarchical groups of an ATC code will be returned, see Examples.
|
||||
#' @param administration type of administration when using \code{property = "Adm.R"}, see Details
|
||||
#' @param url url of website of the WHO. The sign \code{\%s} can be used as a placeholder for ATC codes.
|
||||
#' @param ... parameters to pass on to \code{atc_property}
|
||||
#' @details
|
||||
#' Options for parameter \code{administration}:
|
||||
#' \itemize{
|
||||
#' \item{\code{"Implant"}}{ = Implant}
|
||||
#' \item{\code{"Inhal"}}{ = Inhalation}
|
||||
#' \item{\code{"Instill"}}{ = Instillation}
|
||||
#' \item{\code{"N"}}{ = nasal}
|
||||
#' \item{\code{"O"}}{ = oral}
|
||||
#' \item{\code{"P"}}{ = parenteral}
|
||||
#' \item{\code{"R"}}{ = rectal}
|
||||
#' \item{\code{"SL"}}{ = sublingual/buccal}
|
||||
#' \item{\code{"TD"}}{ = transdermal}
|
||||
#' \item{\code{"V"}}{ = vaginal}
|
||||
#' }
|
||||
#'
|
||||
#' Abbreviations of return values when using \code{property = "U"} (unit):
|
||||
#' \itemize{
|
||||
#' \item{\code{"g"}}{ = gram}
|
||||
#' \item{\code{"mg"}}{ = milligram}
|
||||
#' \item{\code{"mcg"}}{ = microgram}
|
||||
#' \item{\code{"U"}}{ = unit}
|
||||
#' \item{\code{"TU"}}{ = thousand units}
|
||||
#' \item{\code{"MU"}}{ = million units}
|
||||
#' \item{\code{"mmol"}}{ = millimole}
|
||||
#' \item{\code{"ml"}}{ = milliliter (e.g. eyedrops)}
|
||||
#' }
|
||||
#' @export
|
||||
#' @rdname atc_online
|
||||
#' @importFrom dplyr %>% progress_estimated
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @source \url{https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/}
|
||||
#' @examples
|
||||
#' \donttest{
|
||||
#' # oral DDD (Defined Daily Dose) of amoxicillin
|
||||
#' atc_online_property("J01CA04", "DDD", "O")
|
||||
#' # parenteral DDD (Defined Daily Dose) of amoxicillin
|
||||
#' atc_online_property("J01CA04", "DDD", "P")
|
||||
#'
|
||||
#' atc_online_property("J01CA04", property = "groups") # search hierarchical groups of amoxicillin
|
||||
#' # [1] "ANTIINFECTIVES FOR SYSTEMIC USE"
|
||||
#' # [2] "ANTIBACTERIALS FOR SYSTEMIC USE"
|
||||
#' # [3] "BETA-LACTAM ANTIBACTERIALS, PENICILLINS"
|
||||
#' # [4] "Penicillins with extended spectrum"
|
||||
#' }
|
||||
atc_online_property <- function(atc_code,
|
||||
property,
|
||||
administration = "O",
|
||||
url = "https://www.whocc.no/atc_ddd_index/?code=%s&showdescription=no") {
|
||||
|
||||
if (!all(c("curl", "rvest", "xml2") %in% rownames(utils::installed.packages()))) {
|
||||
stop("Packages 'xml2', 'rvest' and 'curl' are required for this function")
|
||||
}
|
||||
|
||||
if (!all(atc_code %in% AMR::antibiotics)) {
|
||||
atc_code <- as.character(ab_atc(atc_code))
|
||||
}
|
||||
|
||||
if (!curl::has_internet()) {
|
||||
message("There appears to be no internet connection.")
|
||||
return(rep(NA, length(atc_code)))
|
||||
}
|
||||
|
||||
if (length(property) != 1L) {
|
||||
stop("`property` must be of length 1", call. = FALSE)
|
||||
}
|
||||
if (length(administration) != 1L) {
|
||||
stop("`administration` must be of length 1", call. = FALSE)
|
||||
}
|
||||
|
||||
# also allow unit as property
|
||||
if (property %like% "unit") {
|
||||
property <- "U"
|
||||
}
|
||||
|
||||
# validation of properties
|
||||
valid_properties <- c("ATC", "Name", "DDD", "U", "Adm.R", "Note", "groups")
|
||||
valid_properties.bak <- valid_properties
|
||||
|
||||
property <- tolower(property)
|
||||
valid_properties <- tolower(valid_properties)
|
||||
|
||||
if (!property %in% valid_properties) {
|
||||
stop("Invalid `property`, use one of ", paste(valid_properties.bak, collapse = ", "), ".")
|
||||
}
|
||||
|
||||
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_estimated(n = length(atc_code))
|
||||
|
||||
for (i in seq_len(length(atc_code))) {
|
||||
|
||||
progress$tick()$print()
|
||||
|
||||
atc_url <- sub("%s", atc_code[i], url, fixed = TRUE)
|
||||
|
||||
if (property == "groups") {
|
||||
tbl <- xml2::read_html(atc_url) %>%
|
||||
rvest::html_node("#content") %>%
|
||||
rvest::html_children() %>%
|
||||
rvest::html_node("a")
|
||||
|
||||
# get URLS of items
|
||||
hrefs <- tbl %>% rvest::html_attr("href")
|
||||
# get text of items
|
||||
texts <- tbl %>% rvest::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 {
|
||||
tbl <- xml2::read_html(atc_url) %>%
|
||||
rvest::html_nodes("table") %>%
|
||||
rvest::html_table(header = TRUE) %>%
|
||||
as.data.frame(stringsAsFactors = FALSE)
|
||||
|
||||
# case insensitive column names
|
||||
colnames(tbl) <- tolower(colnames(tbl)) %>% gsub("^atc.*", "atc", .)
|
||||
|
||||
if (length(tbl) == 0) {
|
||||
warning("ATC not found: ", atc_code[i], ". Please check ", atc_url, ".", call. = FALSE)
|
||||
returnvalue[i] <- NA
|
||||
next
|
||||
}
|
||||
|
||||
if (property %in% c("atc", "name")) {
|
||||
# ATC and name are only in first row
|
||||
returnvalue[i] <- tbl[1, property]
|
||||
} else {
|
||||
if (!"adm.r" %in% colnames(tbl) | is.na(tbl[1, "adm.r"])) {
|
||||
returnvalue[i] <- NA
|
||||
next
|
||||
} else {
|
||||
for (j in seq_len(nrow(tbl))) {
|
||||
if (tbl[j, "adm.r"] == administration) {
|
||||
returnvalue[i] <- tbl[j, property]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (property == "groups" & length(returnvalue) == 1) {
|
||||
returnvalue <- returnvalue[[1]]
|
||||
}
|
||||
|
||||
returnvalue
|
||||
}
|
||||
|
||||
#' @rdname atc_online
|
||||
#' @export
|
||||
atc_online_groups <- function(atc_code, ...) {
|
||||
atc_online_property(atc_code = atc_code, property = "groups", ...)
|
||||
}
|
||||
|
||||
#' @rdname atc_online
|
||||
#' @export
|
||||
atc_online_ddd <- function(atc_code, ...) {
|
||||
atc_online_property(atc_code = atc_code, property = "ddd", ...)
|
||||
}
|
||||
@@ -1,92 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Check availability of columns
|
||||
#'
|
||||
#' Easy check for availability of columns in a data set. This makes it easy to get an idea of which antimicrobial combination can be used for calculation with e.g. \code{\link{portion_R}}.
|
||||
#' @param tbl a \code{data.frame} or \code{list}
|
||||
#' @param width number of characters to present the visual availability, defaults to filling the width of the console
|
||||
#' @details The function returns a \code{data.frame} with columns \code{"resistant"} and \code{"visual_resistance"}. The values in that columns are calculated with \code{\link{portion_R}}.
|
||||
#' @return \code{data.frame} with column names of \code{tbl} as row names
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
# @importFrom clean percentage
|
||||
#' @export
|
||||
#' @examples
|
||||
#' availability(example_isolates)
|
||||
#'
|
||||
#' library(dplyr)
|
||||
#' example_isolates %>% availability()
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' select_if(is.rsi) %>%
|
||||
#' availability()
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' filter(mo == as.mo("E. coli")) %>%
|
||||
#' select_if(is.rsi) %>%
|
||||
#' availability()
|
||||
availability <- function(tbl, width = NULL) {
|
||||
x <- base::sapply(tbl, function(x) {
|
||||
1 - base::sum(base::is.na(x)) / base::length(x)
|
||||
})
|
||||
n <- base::sapply(tbl, function(x) base::length(x[!base::is.na(x)]))
|
||||
R <- base::sapply(tbl, function(x) base::ifelse(is.rsi(x), portion_R(x, minimum = 0), NA))
|
||||
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)
|
||||
if (length(R[is.na(R)]) == ncol(tbl)) {
|
||||
df[, 1:3]
|
||||
} else {
|
||||
df
|
||||
}
|
||||
}
|
||||
@@ -1,175 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.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 \code{format} on the result to prettify it to a publicable/printable format, see Examples.
|
||||
#' @inheritParams eucast_rules
|
||||
#' @param combine_IR logical to indicate whether values R and I should be summed
|
||||
#' @param add_ab_group 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 with 100\% resistance for all tested antimicrobials must be removed from the table
|
||||
#' @param FUN the function to call on the \code{mo} column to transform the microorganism IDs, defaults to \code{\link{mo_shortname}}
|
||||
#' @param translate_ab a character of length 1 containing column names of the \code{\link{antibiotics}} data set
|
||||
#' @param ... arguments passed on to \code{FUN}
|
||||
#' @inheritParams rsi_df
|
||||
#' @inheritParams base::formatC
|
||||
#' @importFrom dplyr %>% rename group_by select mutate filter summarise ungroup
|
||||
#' @importFrom tidyr spread
|
||||
# @importFrom clean freq percentage
|
||||
#' @details The function \code{format} calculates the resistance per bug-drug combination. Use \code{combine_IR = FALSE} (default) to test R vs. S+I and \code{combine_IR = TRUE} to test R+I vs. S.
|
||||
#'
|
||||
#' The language of the output can be overwritten with \code{options(AMR_locale)}, please see \link{translate}.
|
||||
#' @export
|
||||
#' @rdname bug_drug_combinations
|
||||
#' @return The function \code{bug_drug_combinations} returns a \code{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, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' \donttest{
|
||||
#' x <- bug_drug_combinations(example_isolates)
|
||||
#' x
|
||||
#' format(x, translate_ab = "name (atc)")
|
||||
#'
|
||||
#' # Use FUN to change to transformation of microorganism codes
|
||||
#' x <- bug_drug_combinations(example_isolates,
|
||||
#' FUN = mo_gramstain)
|
||||
#'
|
||||
#' x <- bug_drug_combinations(example_isolates,
|
||||
#' FUN = function(x) ifelse(x == "B_ESCHR_COLI",
|
||||
#' "E. coli",
|
||||
#' "Others"))
|
||||
#' }
|
||||
bug_drug_combinations <- function(x,
|
||||
col_mo = NULL,
|
||||
FUN = mo_shortname,
|
||||
...) {
|
||||
if (!is.data.frame(x)) {
|
||||
stop("`x` must be a data frame.", call. = FALSE)
|
||||
}
|
||||
|
||||
# try to find columns based on type
|
||||
# -- mo
|
||||
if (is.null(col_mo)) {
|
||||
col_mo <- search_type_in_df(x = x, type = "mo")
|
||||
}
|
||||
if (is.null(col_mo)) {
|
||||
stop("`col_mo` must be set.", call. = FALSE)
|
||||
}
|
||||
|
||||
x <- x %>%
|
||||
as.data.frame(stringsAsFactors = FALSE) %>%
|
||||
mutate(mo = x %>%
|
||||
pull(col_mo) %>%
|
||||
FUN(...)) %>%
|
||||
group_by(mo) %>%
|
||||
select_if(is.rsi) %>%
|
||||
gather("ab", "value", -mo) %>%
|
||||
group_by(mo, ab) %>%
|
||||
summarise(S = sum(value == "S", na.rm = TRUE),
|
||||
I = sum(value == "I", na.rm = TRUE),
|
||||
R = sum(value == "R", na.rm = TRUE)) %>%
|
||||
ungroup() %>%
|
||||
mutate(total = S + I + R) %>%
|
||||
as.data.frame(stringsAsFactors = FALSE)
|
||||
|
||||
structure(.Data = x, class = c("bug_drug_combinations", class(x)))
|
||||
}
|
||||
|
||||
#' @importFrom dplyr everything rename %>% ungroup group_by summarise mutate_all arrange everything lag
|
||||
#' @importFrom tidyr spread
|
||||
#' @exportMethod format.bug_drug_combinations
|
||||
#' @export
|
||||
#' @rdname bug_drug_combinations
|
||||
format.bug_drug_combinations <- function(x,
|
||||
translate_ab = "name (ab, atc)",
|
||||
language = get_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 == ",", ".", ","),
|
||||
...) {
|
||||
x <- x %>% filter(total >= minimum)
|
||||
|
||||
if (remove_intrinsic_resistant == TRUE) {
|
||||
x <- x %>% filter(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", 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]), ab_txt[i])
|
||||
ab_txt[i] <- gsub("name", ab_name(ab[i], language = language), ab_txt[i])
|
||||
ab_txt[i]
|
||||
}
|
||||
ab_txt
|
||||
}
|
||||
|
||||
y <- x %>%
|
||||
mutate(ab = as.ab(ab),
|
||||
ab_txt = give_ab_name(ab = ab, format = translate_ab, language = language)) %>%
|
||||
group_by(ab, ab_txt, mo) %>%
|
||||
summarise(isolates = sum(isolates, na.rm = TRUE),
|
||||
total = sum(total, na.rm = TRUE)) %>%
|
||||
ungroup() %>%
|
||||
mutate(txt = paste0(percentage(isolates / total, decimal.mark = decimal.mark, big.mark = big.mark),
|
||||
" (", trimws(format(isolates, big.mark = big.mark)), "/",
|
||||
trimws(format(total, big.mark = big.mark)), ")")) %>%
|
||||
select(ab, ab_txt, mo, txt) %>%
|
||||
spread(mo, txt) %>%
|
||||
mutate_all(~ifelse(is.na(.), "", .)) %>%
|
||||
mutate(ab_group = ab_group(ab, language = language),
|
||||
ab_txt) %>%
|
||||
select(ab_group, ab_txt, everything(), -ab) %>%
|
||||
arrange(ab_group, ab_txt) %>%
|
||||
mutate(ab_group = ifelse(ab_group != lag(ab_group) | is.na(lag(ab_group)), ab_group, ""))
|
||||
|
||||
if (add_ab_group == FALSE) {
|
||||
y <- y %>% select(-ab_group) %>% rename("Drug" = ab_txt)
|
||||
colnames(y)[1] <- translate_AMR(colnames(y)[1], language = get_locale(), only_unknown = FALSE)
|
||||
} else {
|
||||
y <- y %>% rename("Group" = ab_group,
|
||||
"Drug" = ab_txt)
|
||||
colnames(y)[1:2] <- translate_AMR(colnames(y)[1:2], language = get_locale(), only_unknown = FALSE)
|
||||
}
|
||||
y
|
||||
}
|
||||
|
||||
#' @exportMethod print.bug_drug_combinations
|
||||
#' @export
|
||||
#' @importFrom crayon blue
|
||||
print.bug_drug_combinations <- function(x, ...) {
|
||||
print(as.data.frame(x, stringsAsFactors = FALSE))
|
||||
message(blue("NOTE: Use 'format()' on this result to get a publicable/printable format."))
|
||||
}
|
||||
@@ -1,132 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' The Catalogue of Life
|
||||
#'
|
||||
#' This package contains the complete taxonomic tree of almost all microorganisms from the authoritative and comprehensive Catalogue of Life.
|
||||
#' @section Catalogue of Life:
|
||||
#' \if{html}{\figure{logo_col.png}{options: height=40px style=margin-bottom:5px} \cr}
|
||||
#' This package contains the complete taxonomic tree of almost all microorganisms (~70,000 species) from the authoritative and comprehensive Catalogue of Life (\url{http://www.catalogueoflife.org}). The Catalogue of Life is the most comprehensive and authoritative global index of species currently available.
|
||||
#'
|
||||
#' \link[=catalogue_of_life]{Click here} for more information about the included taxa. Check which version of the Catalogue of Life was included in this package with \code{\link{catalogue_of_life_version}()}.
|
||||
#' @section Included taxa:
|
||||
#' Included are:
|
||||
#' \itemize{
|
||||
#' \item{All ~61,000 (sub)species from the kingdoms of Archaea, Bacteria, Chromista and Protozoa}
|
||||
#' \item{All ~8,500 (sub)species from these orders of the kingdom of Fungi: Eurotiales, Microascales, Mucorales, Onygenales, Pneumocystales, Saccharomycetales, Schizosaccharomycetales and Tremellales. 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 (like all species of \emph{Aspergillus}, \emph{Candida}, \emph{Cryptococcus}, \emph{Histplasma}, \emph{Pneumocystis}, \emph{Saccharomyces} and \emph{Trichophyton}).}
|
||||
#' \item{All ~150 (sub)species from ~100 other relevant genera from the kingdom of Animalia (like \emph{Strongyloides} and \emph{Taenia})}
|
||||
#' \item{All ~23,000 previously accepted names of all included (sub)species (these were taxonomically renamed)}
|
||||
#' \item{The complete taxonomic tree of all included (sub)species: from kingdom to subspecies}
|
||||
#' \item{The responsible author(s) and year of scientific publication}
|
||||
#' }
|
||||
#'
|
||||
#' The Catalogue of Life (\url{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: \url{https://gitlab.com/msberends/AMR/blob/master/data-raw/reproduction_of_microorganisms.R}.
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @name catalogue_of_life
|
||||
#' @rdname catalogue_of_life
|
||||
#' @seealso Data set \code{\link{microorganisms}} for the actual data. \cr
|
||||
#' Function \code{\link{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("Chlamydia psittaci")
|
||||
#' # Note: 'Chlamydia psittaci' (Page, 1968) was renamed
|
||||
#' # 'Chlamydophila psittaci' (Everett et al., 1999)
|
||||
#' # [1] "C. psittaci"
|
||||
#'
|
||||
#' # Get any property from the entire taxonomic tree for all included species
|
||||
#' mo_class("E. coli")
|
||||
#' # [1] "Gammaproteobacteria"
|
||||
#'
|
||||
#' mo_family("E. coli")
|
||||
#' # [1] "Enterobacteriaceae"
|
||||
#'
|
||||
#' mo_gramstain("E. coli") # based on kingdom and phylum, see ?mo_gramstain
|
||||
#' # [1] "Gram negative"
|
||||
#'
|
||||
#' mo_ref("E. coli")
|
||||
#' # [1] "Castellani et al., 1919"
|
||||
#'
|
||||
#' # Do not get mistaken - the package only includes microorganisms
|
||||
#' mo_kingdom("C. elegans")
|
||||
#' # [1] "Bacteria" # Bacteria?!
|
||||
#' mo_name("C. elegans")
|
||||
#' # [1] "Chroococcus limneticus elegans" # Because a microorganism was found
|
||||
NULL
|
||||
|
||||
#' Version info of included Catalogue of Life
|
||||
#'
|
||||
#' This function returns information about the included data from the Catalogue of Life.
|
||||
#' @seealso \code{\link{microorganisms}}
|
||||
#' @details For DSMZ, see \code{?microorganisms}.
|
||||
#' @return a \code{list}, which prints in pretty format
|
||||
#' @inheritSection catalogue_of_life Catalogue of Life
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @importFrom crayon bold underline
|
||||
#' @importFrom dplyr filter
|
||||
#' @export
|
||||
#' @examples
|
||||
#' library(dplyr)
|
||||
#' library(clean)
|
||||
#' microorganisms %>% freq(kingdom)
|
||||
#' microorganisms %>% group_by(kingdom) %>% freq(phylum, nmax = NULL)
|
||||
catalogue_of_life_version <- function() {
|
||||
# see the `catalogue_of_life` list in R/data.R
|
||||
lst <- list(catalogue_of_life =
|
||||
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(filter(AMR::microorganisms, source == "CoL"))),
|
||||
deutsche_sammlung_von_mikroorganismen_und_zellkulturen =
|
||||
list(version = "Prokaryotic Nomenclature Up-to-Date from DSMZ",
|
||||
url = catalogue_of_life$url_DSMZ,
|
||||
yearmonth = catalogue_of_life$yearmonth_DSMZ,
|
||||
n = nrow(filter(AMR::microorganisms, source == "DSMZ"))),
|
||||
total_included =
|
||||
list(
|
||||
n_total_species = nrow(AMR::microorganisms),
|
||||
n_total_synonyms = nrow(AMR::microorganisms.old)))
|
||||
|
||||
structure(.Data = lst,
|
||||
class = c("catalogue_of_life_version", "list"))
|
||||
}
|
||||
|
||||
#' @exportMethod print.catalogue_of_life_version
|
||||
#' @export
|
||||
#' @noRd
|
||||
print.catalogue_of_life_version <- function(x, ...) {
|
||||
lst <- x
|
||||
cat(paste0(bold("Included in this AMR package are:\n\n"),
|
||||
underline(lst$catalogue_of_life$version), "\n",
|
||||
" Available at: ", lst$catalogue_of_life$url, "\n",
|
||||
" Number of included species: ", format(lst$catalogue_of_life$n, big.mark = ","), "\n",
|
||||
underline(paste0(lst$deutsche_sammlung_von_mikroorganismen_und_zellkulturen$version, " (",
|
||||
lst$deutsche_sammlung_von_mikroorganismen_und_zellkulturen$yearmonth, ")")), "\n",
|
||||
" Available at: ", lst$deutsche_sammlung_von_mikroorganismen_und_zellkulturen$url, "\n",
|
||||
" Number of included species: ", format(lst$deutsche_sammlung_von_mikroorganismen_und_zellkulturen$n, big.mark = ","), "\n\n",
|
||||
"=> Total number of species included: ", format(lst$total_included$n_total_species, big.mark = ","), "\n",
|
||||
"=> Total number of synonyms included: ", format(lst$total_included$n_total_synonyms, big.mark = ","), "\n\n",
|
||||
"See for more info ?microorganisms and ?catalogue_of_life.\n"))
|
||||
}
|
||||
@@ -1,174 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Count isolates
|
||||
#'
|
||||
#' @description These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in \code{dplyr}s \code{\link[dplyr]{summarise}} and support grouped variables, see \emph{Examples}.
|
||||
#'
|
||||
#' \code{count_R} and \code{count_IR} can be used to count resistant isolates, \code{count_S} and \code{count_SI} can be used to count susceptible isolates.\cr
|
||||
#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with \code{\link{as.rsi}} if needed.
|
||||
#' @inheritParams portion
|
||||
#' @inheritSection as.rsi Interpretation of S, I and R
|
||||
#' @details These functions are meant to count isolates. Use the \code{\link{portion}_*} functions to calculate microbial resistance.
|
||||
#'
|
||||
#' The function \code{n_rsi} is an alias of \code{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 \code{\link{n_distinct}}. Their function is equal to \code{count_S(...) + count_IR(...)}.
|
||||
#'
|
||||
#' The function \code{count_df} takes any variable from \code{data} that has an \code{"rsi"} class (created with \code{\link{as.rsi}}) and counts the amounts of S, I and R. The resulting \emph{tidy data} (see Source) \code{data.frame} will have three rows (S/I/R) and a column for each variable with class \code{"rsi"}.
|
||||
#'
|
||||
#' The function \code{rsi_df} works exactly like \code{count_df}, but adds the percentage of S, I and R.
|
||||
#' @inheritSection portion Combination therapy
|
||||
#' @source Wickham H. \strong{Tidy Data.} The Journal of Statistical Software, vol. 59, 2014. \url{http://vita.had.co.nz/papers/tidy-data.html}
|
||||
#' @seealso \code{\link{portion}_*} to calculate microbial resistance and susceptibility.
|
||||
#' @keywords resistance susceptibility rsi antibiotics isolate isolates
|
||||
#' @return Integer
|
||||
#' @rdname count
|
||||
#' @name count
|
||||
#' @export
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' # example_isolates is a data set available in the AMR package.
|
||||
#' ?example_isolates
|
||||
#'
|
||||
#' # Count resistant isolates
|
||||
#' count_R(example_isolates$AMX)
|
||||
#' count_IR(example_isolates$AMX)
|
||||
#'
|
||||
#' # Or susceptible isolates
|
||||
#' count_S(example_isolates$AMX)
|
||||
#' count_SI(example_isolates$AMX)
|
||||
#'
|
||||
#' # Count all available isolates
|
||||
#' count_all(example_isolates$AMX)
|
||||
#' n_rsi(example_isolates$AMX)
|
||||
#'
|
||||
#' # Since n_rsi counts available isolates, you can
|
||||
#' # calculate back to count e.g. non-susceptible isolates.
|
||||
#' # This results in the same:
|
||||
#' count_SI(example_isolates$AMX)
|
||||
#' portion_SI(example_isolates$AMX) * n_rsi(example_isolates$AMX)
|
||||
#'
|
||||
#' library(dplyr)
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(R = count_R(CIP),
|
||||
#' I = count_I(CIP),
|
||||
#' S = count_S(CIP),
|
||||
#' n1 = count_all(CIP), # the actual total; sum of all three
|
||||
#' n2 = n_rsi(CIP), # same - analogous to n_distinct
|
||||
#' total = n()) # NOT the number of tested isolates!
|
||||
#'
|
||||
#' # Count co-resistance between amoxicillin/clav acid and gentamicin,
|
||||
#' # so we can see that combination therapy does a lot more than mono therapy.
|
||||
#' # Please mind that `portion_SI` calculates percentages right away instead.
|
||||
#' count_SI(example_isolates$AMC) # 1433
|
||||
#' count_all(example_isolates$AMC) # 1879
|
||||
#'
|
||||
#' count_SI(example_isolates$GEN) # 1399
|
||||
#' count_all(example_isolates$GEN) # 1855
|
||||
#'
|
||||
#' with(example_isolates,
|
||||
#' count_SI(AMC, GEN)) # 1764
|
||||
#' with(example_isolates,
|
||||
#' n_rsi(AMC, GEN)) # 1936
|
||||
#'
|
||||
#' # Get portions S/I/R immediately of all rsi 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_R <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_IR <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = c("I", "R"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_I <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = "I",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_SI <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_S <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = "S",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_all <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I", "R"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
n_rsi <- count_all
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_df <- function(data,
|
||||
translate_ab = "name",
|
||||
language = get_locale(),
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE) {
|
||||
|
||||
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))
|
||||
}
|
||||
@@ -1,225 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Data set with ~450 antibiotics
|
||||
#'
|
||||
#' A data set containing all antibiotics. Use \code{\link{as.ab}} or one of the \code{\link{ab_property}} functions to retrieve values from this data set. Three identifiers are included in this data set: an antibiotic ID (\code{ab}, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (\code{atc}) as defined by the WHO, and a Compound ID (\code{cid}) as found in PubChem. Other properties in this data set are derived from one or more of these codes.
|
||||
#' @format A \code{\link{data.frame}} with 453 observations and 13 variables:
|
||||
#' \describe{
|
||||
#' \item{\code{ab}}{Antibiotic ID as used in this package (like \code{AMC}), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available}
|
||||
#' \item{\code{atc}}{ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC, like \code{J01CR02}}
|
||||
#' \item{\code{cid}}{Compound ID as found in PubChem}
|
||||
#' \item{\code{name}}{Official name as used by WHONET/EARS-Net or the WHO}
|
||||
#' \item{\code{group}}{A short and concise group name, based on WHONET and WHOCC definitions}
|
||||
#' \item{\code{atc_group1}}{Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC, like \code{"Macrolides, lincosamides and streptogramins"}}
|
||||
#' \item{\code{atc_group2}}{Official chemical subgroup (4th level ATC code) as defined by the WHOCC, like \code{"Macrolides"}}
|
||||
#' \item{\code{abbr}}{List of abbreviations as used in many countries, also for antibiotic susceptibility testing (AST)}
|
||||
#' \item{\code{synonyms}}{Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID}
|
||||
#' \item{\code{oral_ddd}}{Defined Daily Dose (DDD), oral treatment}
|
||||
#' \item{\code{oral_units}}{Units of \code{ddd_units}}
|
||||
#' \item{\code{iv_ddd}}{Defined Daily Dose (DDD), parenteral treatment}
|
||||
#' \item{\code{iv_units}}{Units of \code{iv_ddd}}
|
||||
#' }
|
||||
#' @details Properties that are based on an ATC code are only available when an ATC is available. These properties are: \code{atc_group1}, \code{atc_group2}, \code{oral_ddd}, \code{oral_units}, \code{iv_ddd} and \code{iv_units}
|
||||
#'
|
||||
#' Synonyms (i.e. trade names) are derived from the Compound ID (\code{cid}) and consequently only available where a CID is available.
|
||||
#' @source World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): \url{https://www.whocc.no/atc_ddd_index/}
|
||||
#'
|
||||
#' WHONET 2019 software: \url{http://www.whonet.org/software.html}
|
||||
#'
|
||||
#' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}
|
||||
#' @inheritSection WHOCC WHOCC
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @seealso \code{\link{microorganisms}}
|
||||
"antibiotics"
|
||||
|
||||
#' Data set with ~70,000 microorganisms
|
||||
#'
|
||||
#' A data set containing the microbial taxonomy of six kingdoms from the Catalogue of Life. MO codes can be looked up using \code{\link{as.mo}}.
|
||||
#' @inheritSection catalogue_of_life Catalogue of Life
|
||||
#' @format A \code{\link{data.frame}} with 69,465 observations and 16 variables:
|
||||
#' \describe{
|
||||
#' \item{\code{mo}}{ID of microorganism as used by this package}
|
||||
#' \item{\code{col_id}}{Catalogue of Life ID}
|
||||
#' \item{\code{fullname}}{Full name, like \code{"Escherichia coli"}}
|
||||
#' \item{\code{kingdom}, \code{phylum}, \code{class}, \code{order}, \code{family}, \code{genus}, \code{species}, \code{subspecies}}{Taxonomic rank of the microorganism}
|
||||
#' \item{\code{rank}}{Text of the taxonomic rank of the microorganism, like \code{"species"} or \code{"genus"}}
|
||||
#' \item{\code{ref}}{Author(s) and year of concerning scientific publication}
|
||||
#' \item{\code{species_id}}{ID of the species as used by the Catalogue of Life}
|
||||
#' \item{\code{source}}{Either "CoL", "DSMZ" (see Source) or "manually added"}
|
||||
#' \item{\code{prevalence}}{Prevalence of the microorganism, see \code{?as.mo}}
|
||||
#' }
|
||||
#' @details Manually added were:
|
||||
#' \itemize{
|
||||
#' \item{11 entries of \emph{Streptococcus} (beta-haemolytic: groups A, B, C, D, F, G, H, K and unspecified; other: viridans, milleri)}
|
||||
#' \item{2 entries of \emph{Staphylococcus} (coagulase-negative [CoNS] and coagulase-positive [CoPS])}
|
||||
#' \item{3 entries of \emph{Trichomonas} (\emph{Trichomonas vaginalis}, and its family and genus)}
|
||||
#' \item{1 entry of \emph{Blastocystis} (\emph{Blastocystis hominis}), although it officially does not exist (Noel et al. 2005, PMID 15634993)}
|
||||
#' \item{5 other 'undefined' entries (unknown, unknown Gram negatives, unknown Gram positives, unknown yeast and unknown fungus)}
|
||||
#' \item{9,460 species from the DSMZ (Deutsche Sammlung von Mikroorganismen und Zellkulturen) since the DSMZ contain the latest taxonomic information based on recent publications}
|
||||
#' }
|
||||
#' @section About the records from DSMZ (see source):
|
||||
#' Names of prokaryotes are defined as being validly published by the International Code of Nomenclature of Bacteria. Validly published are all names which are included in the Approved Lists of Bacterial Names and the names subsequently published in the International Journal of Systematic Bacteriology (IJSB) and, from January 2000, in the International Journal of Systematic and Evolutionary Microbiology (IJSEM) as original articles or in the validation lists.
|
||||
#'
|
||||
#' From: \url{https://www.dsmz.de/support/bacterial-nomenclature-up-to-date-downloads/readme.html}
|
||||
#' @source Catalogue of Life: Annual Checklist (public online taxonomic database), \url{http://www.catalogueoflife.org} (check included annual version with \code{\link{catalogue_of_life_version}()}).
|
||||
#'
|
||||
#' Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Germany, Prokaryotic Nomenclature Up-to-Date, \url{http://www.dsmz.de/bacterial-diversity/prokaryotic-nomenclature-up-to-date} (check included version with \code{\link{catalogue_of_life_version}()}).
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @seealso \code{\link{as.mo}}, \code{\link{mo_property}}, \code{\link{microorganisms.codes}}
|
||||
"microorganisms"
|
||||
|
||||
catalogue_of_life <- list(
|
||||
year = 2018,
|
||||
version = "Catalogue of Life: {year} Annual Checklist",
|
||||
url_CoL = "http://www.catalogueoflife.org/annual-checklist/{year}/",
|
||||
url_DSMZ = "https://www.dsmz.de/services/online-tools/prokaryotic-nomenclature-up-to-date/prokaryotic-nomenclature-up-to-date/genus-search",
|
||||
yearmonth_DSMZ = "August 2019"
|
||||
)
|
||||
|
||||
#' 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 \code{\link{as.mo}}.
|
||||
#' @inheritSection catalogue_of_life Catalogue of Life
|
||||
#' @format A \code{\link{data.frame}} with 24,246 observations and 5 variables:
|
||||
#' \describe{
|
||||
#' \item{\code{col_id}}{Catalogue of Life ID that was originally given}
|
||||
#' \item{\code{col_id_new}}{New Catalogue of Life ID that responds to an entry in the \code{\link{microorganisms}} data set}
|
||||
#' \item{\code{fullname}}{Old full taxonomic name of the microorganism}
|
||||
#' \item{\code{ref}}{Author(s) and year of concerning scientific publication}
|
||||
#' \item{\code{prevalence}}{Prevalence of the microorganism, see \code{?as.mo}}
|
||||
#' }
|
||||
#' @source Catalogue of Life: Annual Checklist (public online taxonomic database), \url{http://www.catalogueoflife.org} (check included annual version with \code{\link{catalogue_of_life_version}()}).
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @seealso \code{\link{as.mo}} \code{\link{mo_property}} \code{\link{microorganisms}}
|
||||
"microorganisms.old"
|
||||
|
||||
#' Translation table for common microorganism codes
|
||||
#'
|
||||
#' A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with \code{\link{set_mo_source}}.
|
||||
#' @format A \code{\link{data.frame}} with 5,006 observations and 2 variables:
|
||||
#' \describe{
|
||||
#' \item{\code{code}}{Commonly used code of a microorganism}
|
||||
#' \item{\code{mo}}{ID of the microorganism in the \code{\link{microorganisms}} data set}
|
||||
#' }
|
||||
#' @inheritSection catalogue_of_life Catalogue of Life
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @seealso \code{\link{as.mo}} \code{\link{microorganisms}}
|
||||
"microorganisms.codes"
|
||||
|
||||
#' Data set with 2,000 blood culture isolates
|
||||
#'
|
||||
#' An anonymised data set containing 2,000 microbial blood culture isolates with their full antibiograms found 4 different hospitals in the Netherlands, between 2001 and 2017. This \code{data.frame} can be used to practice AMR analysis. For examples, please read \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{the tutorial on our website}.
|
||||
#' @format A \code{\link{data.frame}} with 2,000 observations and 49 variables:
|
||||
#' \describe{
|
||||
#' \item{\code{date}}{date of receipt at the laboratory}
|
||||
#' \item{\code{hospital_id}}{ID of the hospital, from A to D}
|
||||
#' \item{\code{ward_icu}}{logical to determine if ward is an intensive care unit}
|
||||
#' \item{\code{ward_clinical}}{logical to determine if ward is a regular clinical ward}
|
||||
#' \item{\code{ward_outpatient}}{logical to determine if ward is an outpatient clinic}
|
||||
#' \item{\code{age}}{age of the patient}
|
||||
#' \item{\code{gender}}{gender of the patient}
|
||||
#' \item{\code{patient_id}}{ID of the patient, first 10 characters of an SHA hash containing irretrievable information}
|
||||
#' \item{\code{mo}}{ID of microorganism created with \code{\link{as.mo}}, see also \code{\link{microorganisms}}}
|
||||
#' \item{\code{PEN:RIF}}{40 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}); these column names occur in \code{\link{antibiotics}} data set and can be translated with \code{\link{ab_name}}}
|
||||
#' }
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
"example_isolates"
|
||||
|
||||
#' Data set with 500 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 data itself was based on our \code{\link{example_isolates}} data set.
|
||||
#' @format A \code{\link{data.frame}} with 500 observations and 53 variables:
|
||||
#' \describe{
|
||||
#' \item{\code{Identification number}}{ID of the sample}
|
||||
#' \item{\code{Specimen number}}{ID of the specimen}
|
||||
#' \item{\code{Organism}}{Name of the microorganism. Before analysis, you should transform this to a valid microbial class, using \code{\link{as.mo}}.}
|
||||
#' \item{\code{Country}}{Country of origin}
|
||||
#' \item{\code{Laboratory}}{Name of laboratory}
|
||||
#' \item{\code{Last name}}{Last name of patient}
|
||||
#' \item{\code{First name}}{Initial of patient}
|
||||
#' \item{\code{Sex}}{Gender of patient}
|
||||
#' \item{\code{Age}}{Age of patient}
|
||||
#' \item{\code{Age category}}{Age group, can also be looked up using \code{\link{age_groups}}}
|
||||
#' \item{\code{Date of admission}}{Date of hospital admission}
|
||||
#' \item{\code{Specimen date}}{Date when specimen was received at laboratory}
|
||||
#' \item{\code{Specimen type}}{Specimen type or group}
|
||||
#' \item{\code{Specimen type (Numeric)}}{Translation of \code{"Specimen type"}}
|
||||
#' \item{\code{Reason}}{Reason of request with Differential Diagnosis}
|
||||
#' \item{\code{Isolate number}}{ID of isolate}
|
||||
#' \item{\code{Organism type}}{Type of microorganism, can also be looked up using \code{\link{mo_type}}}
|
||||
#' \item{\code{Serotype}}{Serotype of microorganism}
|
||||
#' \item{\code{Beta-lactamase}}{Microorganism produces beta-lactamase?}
|
||||
#' \item{\code{ESBL}}{Microorganism produces extended spectrum beta-lactamase?}
|
||||
#' \item{\code{Carbapenemase}}{Microorganism produces carbapenemase?}
|
||||
#' \item{\code{MRSA screening test}}{Microorganism is possible MRSA?}
|
||||
#' \item{\code{Inducible clindamycin resistance}}{Clindamycin can be induced?}
|
||||
#' \item{\code{Comment}}{Other comments}
|
||||
#' \item{\code{Date of data entry}}{Date this data was entered in WHONET}
|
||||
#' \item{\code{AMP_ND10:CIP_EE}}{27 different antibiotics. You can lookup the abbreviatons in the \code{\link{antibiotics}} data set, or use e.g. \code{\link{ab_name}("AMP")} to get the official name immediately. Before analysis, you should transform this to a valid antibiotic class, using \code{\link{as.rsi}}.}
|
||||
#' }
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
"WHONET"
|
||||
|
||||
#' Data set for RSI interpretation
|
||||
#'
|
||||
#' Data set to interpret MIC and disk diffusion to RSI values. Included guidelines are CLSI (2011-2019) and EUCAST (2011-2019). Use \code{\link{as.rsi}} to transform MICs or disks measurements to RSI values.
|
||||
#' @format A \code{\link{data.frame}} with 11,559 observations and 9 variables:
|
||||
#' \describe{
|
||||
#' \item{\code{guideline}}{Name of the guideline}
|
||||
#' \item{\code{mo}}{Microbial ID, see \code{\link{as.mo}}}
|
||||
#' \item{\code{ab}}{Antibiotic ID, see \code{\link{as.ab}}}
|
||||
#' \item{\code{ref_tbl}}{Info about where the guideline rule can be found}
|
||||
#' \item{\code{S_mic}}{Lowest MIC value that leads to "S"}
|
||||
#' \item{\code{R_mic}}{Highest MIC value that leads to "R"}
|
||||
#' \item{\code{dose_disk}}{Dose of the used disk diffusion method}
|
||||
#' \item{\code{S_disk}}{Lowest number of millimeters that leads to "S"}
|
||||
#' \item{\code{R_disk}}{Highest number of millimeters that leads to "R"}
|
||||
#' }
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
"rsi_translation"
|
||||
|
||||
# transforms data set to data.frame with only ASCII values, to comply with CRAN policies
|
||||
dataset_UTF8_to_ASCII <- function(df) {
|
||||
trans <- function(vect) {
|
||||
iconv(vect, from = "UTF-8", to = "ASCII//TRANSLIT")
|
||||
}
|
||||
df <- as.data.frame(df, stringsAsFactors = FALSE)
|
||||
for (i in seq_len(NCOL(df))) {
|
||||
col <- df[, i]
|
||||
if (is.list(col)) {
|
||||
for (j in seq_len(length(col))) {
|
||||
col[[j]] <- trans(col[[j]])
|
||||
}
|
||||
df[, i] <- list(col)
|
||||
} else {
|
||||
if (is.factor(col)) {
|
||||
levels(col) <- trans(levels(col))
|
||||
} else if (is.character(col)) {
|
||||
col <- trans(col)
|
||||
} else {
|
||||
col
|
||||
}
|
||||
df[, i] <- col
|
||||
}
|
||||
}
|
||||
df
|
||||
}
|
||||
@@ -1,40 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Deprecated functions
|
||||
#'
|
||||
#' These functions are so-called '\link{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).
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @export
|
||||
#' @keywords internal
|
||||
#' @name AMR-deprecated
|
||||
#' @rdname AMR-deprecated
|
||||
as.atc <- function(x) {
|
||||
.Deprecated("ab_atc", package = "AMR")
|
||||
AMR::ab_atc(x)
|
||||
}
|
||||
|
||||
#' @rdname AMR-deprecated
|
||||
#' @export
|
||||
p.symbol <- function(...) {
|
||||
.Deprecated("p_symbol", package = "AMR")
|
||||
AMR::p_symbol(...)
|
||||
}
|
||||
@@ -1,106 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Class 'disk'
|
||||
#'
|
||||
#' This transforms a vector to a new class \code{disk}, which is a growth zone size (around an antibiotic disk) in millimeters between 6 and 99.
|
||||
#' @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 \code{\link{as.rsi}}. It supports guidelines from EUCAST and CLSI.
|
||||
#' @return Ordered integer factor with new class \code{disk}
|
||||
#' @keywords disk
|
||||
#' @export
|
||||
#' @seealso \code{\link{as.rsi}}
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' # interpret disk values
|
||||
#' as.rsi(x = 12,
|
||||
#' mo = as.mo("S. pneumoniae"),
|
||||
#' ab = "AMX",
|
||||
#' guideline = "EUCAST")
|
||||
#' as.rsi(x = 12,
|
||||
#' mo = as.mo("S. pneumoniae"),
|
||||
#' ab = "AMX",
|
||||
#' guideline = "CLSI")
|
||||
as.disk <- function(x, na.rm = FALSE) {
|
||||
if (is.disk(x)) {
|
||||
x
|
||||
} else {
|
||||
x <- x %>% unlist()
|
||||
if (na.rm == TRUE) {
|
||||
x <- x[!is.na(x)]
|
||||
}
|
||||
x.bak <- x
|
||||
|
||||
na_before <- length(x[is.na(x)])
|
||||
|
||||
# force it to be integer
|
||||
x <- suppressWarnings(as.integer(x))
|
||||
|
||||
# disks can never be less than 9 mm (size of a disk) or more than 50 mm
|
||||
x[x < 6 | x > 99] <- 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)] %>%
|
||||
unique() %>%
|
||||
sort()
|
||||
list_missing <- paste0('"', list_missing, '"', collapse = ", ")
|
||||
warning(na_after - na_before, " results truncated (",
|
||||
round(((na_after - na_before) / length(x)) * 100),
|
||||
"%) that were invalid disk zones: ",
|
||||
list_missing, call. = FALSE)
|
||||
}
|
||||
|
||||
class(x) <- c("disk", "integer")
|
||||
x
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname as.disk
|
||||
#' @export
|
||||
#' @importFrom dplyr %>%
|
||||
is.disk <- function(x) {
|
||||
class(x) %>% identical(c("disk", "integer"))
|
||||
}
|
||||
|
||||
#' @exportMethod print.disk
|
||||
#' @export
|
||||
#' @noRd
|
||||
print.disk <- function(x, ...) {
|
||||
cat("Class 'disk'\n")
|
||||
print(as.integer(x), quote = FALSE)
|
||||
}
|
||||
|
||||
#' @importFrom pillar type_sum
|
||||
#' @export
|
||||
type_sum.disk <- function(x) {
|
||||
"disk"
|
||||
}
|
||||
|
||||
#' @importFrom pillar pillar_shaft
|
||||
#' @export
|
||||
pillar_shaft.disk <- function(x, ...) {
|
||||
out <- trimws(format(x))
|
||||
out[is.na(x)] <- pillar::style_na(NA)
|
||||
pillar::new_pillar_shaft_simple(out, align = "right", min_width = 3)
|
||||
}
|
||||
@@ -1,856 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
# global variables
|
||||
EUCAST_VERSION_BREAKPOINTS <- "9.0, 2019"
|
||||
EUCAST_VERSION_EXPERT_RULES <- "3.1, 2016"
|
||||
|
||||
#' EUCAST rules
|
||||
#'
|
||||
#' Apply susceptibility rules as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, \url{http://eucast.org}), see \emph{Source}. This includes (1) expert rules, (2) intrinsic resistance and (3) inferred resistance as defined in their breakpoint tables.
|
||||
#' @param x data with antibiotic columns, like e.g. \code{AMX} and \code{AMC}
|
||||
#' @param info print progress
|
||||
#' @param rules a character vector that specifies which rules should be applied - one or more of \code{c("breakpoints", "expert", "other", "all")}
|
||||
#' @param verbose a logical to turn Verbose mode on and off (default is off). In Verbose mode, the function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way.
|
||||
#' @param ... column name of an antibiotic, see section Antibiotics
|
||||
#' @inheritParams first_isolate
|
||||
#' @details
|
||||
#' \strong{Note:} This function does not translate MIC values to RSI values. Use \code{\link{as.rsi}} for that. \cr
|
||||
#' \strong{Note:} When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance.
|
||||
#'
|
||||
#' The file containing all EUCAST rules is located here: \url{https://gitlab.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv}.
|
||||
#'
|
||||
#' @section Antibiotics:
|
||||
#' To define antibiotics column names, leave as it is to determine it automatically with \code{\link{guess_ab_col}} or input a text (case-insensitive), or use \code{NULL} to skip a column (e.g. \code{TIC = NULL} to skip ticarcillin). Manually defined but non-existing columns will be skipped with a warning.
|
||||
#'
|
||||
#' The following antibiotics are used for the functions \code{\link{eucast_rules}} and \code{\link{mdro}}. These are shown below in the format '\strong{antimicrobial ID}: name (\href{https://www.whocc.no/atc/structure_and_principles/}{ATC code})', sorted by name:
|
||||
#'
|
||||
#' \strong{AMK}: amikacin (\href{https://www.whocc.no/atc_ddd_index/?code=J01GB06}{J01GB06}),
|
||||
#' \strong{AMX}: amoxicillin (\href{https://www.whocc.no/atc_ddd_index/?code=J01CA04}{J01CA04}),
|
||||
#' \strong{AMC}: amoxicillin/clavulanic acid (\href{https://www.whocc.no/atc_ddd_index/?code=J01CR02}{J01CR02}),
|
||||
#' \strong{AMP}: ampicillin (\href{https://www.whocc.no/atc_ddd_index/?code=J01CA01}{J01CA01}),
|
||||
#' \strong{AZM}: azithromycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01FA10}{J01FA10}),
|
||||
#' \strong{AZL}: azlocillin (\href{https://www.whocc.no/atc_ddd_index/?code=J01CA09}{J01CA09}),
|
||||
#' \strong{ATM}: aztreonam (\href{https://www.whocc.no/atc_ddd_index/?code=J01DF01}{J01DF01}),
|
||||
#' \strong{CAP}: capreomycin (\href{https://www.whocc.no/atc_ddd_index/?code=J04AB30}{J04AB30}),
|
||||
#' \strong{RID}: cefaloridine (\href{https://www.whocc.no/atc_ddd_index/?code=J01DB02}{J01DB02}),
|
||||
#' \strong{CZO}: cefazolin (\href{https://www.whocc.no/atc_ddd_index/?code=J01DB04}{J01DB04}),
|
||||
#' \strong{FEP}: cefepime (\href{https://www.whocc.no/atc_ddd_index/?code=J01DE01}{J01DE01}),
|
||||
#' \strong{CTX}: cefotaxime (\href{https://www.whocc.no/atc_ddd_index/?code=J01DD01}{J01DD01}),
|
||||
#' \strong{FOX}: cefoxitin (\href{https://www.whocc.no/atc_ddd_index/?code=J01DC01}{J01DC01}),
|
||||
#' \strong{CED}: cefradine (\href{https://www.whocc.no/atc_ddd_index/?code=J01DB09}{J01DB09}),
|
||||
#' \strong{CAZ}: ceftazidime (\href{https://www.whocc.no/atc_ddd_index/?code=J01DD02}{J01DD02}),
|
||||
#' \strong{CRO}: ceftriaxone (\href{https://www.whocc.no/atc_ddd_index/?code=J01DD04}{J01DD04}),
|
||||
#' \strong{CXM}: cefuroxime (\href{https://www.whocc.no/atc_ddd_index/?code=J01DC02}{J01DC02}),
|
||||
#' \strong{CHL}: chloramphenicol (\href{https://www.whocc.no/atc_ddd_index/?code=J01BA01}{J01BA01}),
|
||||
#' \strong{CIP}: ciprofloxacin (\href{https://www.whocc.no/atc_ddd_index/?code=J01MA02}{J01MA02}),
|
||||
#' \strong{CLR}: clarithromycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01FA09}{J01FA09}),
|
||||
#' \strong{CLI}: clindamycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01FF01}{J01FF01}),
|
||||
#' \strong{COL}: colistin (\href{https://www.whocc.no/atc_ddd_index/?code=J01XB01}{J01XB01}),
|
||||
#' \strong{DAP}: daptomycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01XX09}{J01XX09}),
|
||||
#' \strong{DOX}: doxycycline (\href{https://www.whocc.no/atc_ddd_index/?code=J01AA02}{J01AA02}),
|
||||
#' \strong{ETP}: ertapenem (\href{https://www.whocc.no/atc_ddd_index/?code=J01DH03}{J01DH03}),
|
||||
#' \strong{ERY}: erythromycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01FA01}{J01FA01}),
|
||||
#' \strong{ETH}: ethambutol (\href{https://www.whocc.no/atc_ddd_index/?code=J04AK02}{J04AK02}),
|
||||
#' \strong{FLC}: flucloxacillin (\href{https://www.whocc.no/atc_ddd_index/?code=J01CF05}{J01CF05}),
|
||||
#' \strong{FOS}: fosfomycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01XX01}{J01XX01}),
|
||||
#' \strong{FUS}: fusidic acid (\href{https://www.whocc.no/atc_ddd_index/?code=J01XC01}{J01XC01}),
|
||||
#' \strong{GAT}: gatifloxacin (\href{https://www.whocc.no/atc_ddd_index/?code=J01MA16}{J01MA16}),
|
||||
#' \strong{GEN}: gentamicin (\href{https://www.whocc.no/atc_ddd_index/?code=J01GB03}{J01GB03}),
|
||||
#' \strong{IPM}: imipenem (\href{https://www.whocc.no/atc_ddd_index/?code=J01DH51}{J01DH51}),
|
||||
#' \strong{INH}: isoniazid (\href{https://www.whocc.no/atc_ddd_index/?code=J04AC01}{J04AC01}),
|
||||
#' \strong{KAN}: kanamycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01GB04}{J01GB04}),
|
||||
#' \strong{LVX}: levofloxacin (\href{https://www.whocc.no/atc_ddd_index/?code=J01MA12}{J01MA12}),
|
||||
#' \strong{LIN}: lincomycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01FF02}{J01FF02}),
|
||||
#' \strong{LNZ}: linezolid (\href{https://www.whocc.no/atc_ddd_index/?code=J01XX08}{J01XX08}),
|
||||
#' \strong{MEM}: meropenem (\href{https://www.whocc.no/atc_ddd_index/?code=J01DH02}{J01DH02}),
|
||||
#' \strong{MTR}: metronidazole (\href{https://www.whocc.no/atc_ddd_index/?code=J01XD01}{J01XD01}),
|
||||
#' \strong{MEZ}: mezlocillin (\href{https://www.whocc.no/atc_ddd_index/?code=J01CA10}{J01CA10}),
|
||||
#' \strong{MNO}: minocycline (\href{https://www.whocc.no/atc_ddd_index/?code=J01AA08}{J01AA08}),
|
||||
#' \strong{MFX}: moxifloxacin (\href{https://www.whocc.no/atc_ddd_index/?code=J01MA14}{J01MA14}),
|
||||
#' \strong{NAL}: nalidixic acid (\href{https://www.whocc.no/atc_ddd_index/?code=J01MB02}{J01MB02}),
|
||||
#' \strong{NEO}: neomycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01GB05}{J01GB05}),
|
||||
#' \strong{NET}: netilmicin (\href{https://www.whocc.no/atc_ddd_index/?code=J01GB07}{J01GB07}),
|
||||
#' \strong{NIT}: nitrofurantoin (\href{https://www.whocc.no/atc_ddd_index/?code=J01XE01}{J01XE01}),
|
||||
#' \strong{NOR}: norfloxacin (\href{https://www.whocc.no/atc_ddd_index/?code=J01MA06}{J01MA06}),
|
||||
#' \strong{NOV}: novobiocin (an ATCvet code: \href{https://www.whocc.no/atc_ddd_index/?code=QJ01XX95}{QJ01XX95}),
|
||||
#' \strong{OFX}: ofloxacin (\href{https://www.whocc.no/atc_ddd_index/?code=J01MA01}{J01MA01}),
|
||||
#' \strong{OXA}: oxacillin (\href{https://www.whocc.no/atc_ddd_index/?code=J01CF04}{J01CF04}),
|
||||
#' \strong{PEN}: penicillin G (\href{https://www.whocc.no/atc_ddd_index/?code=J01CE01}{J01CE01}),
|
||||
#' \strong{PIP}: piperacillin (\href{https://www.whocc.no/atc_ddd_index/?code=J01CA12}{J01CA12}),
|
||||
#' \strong{TZP}: piperacillin/tazobactam (\href{https://www.whocc.no/atc_ddd_index/?code=J01CR05}{J01CR05}),
|
||||
#' \strong{PLB}: polymyxin B (\href{https://www.whocc.no/atc_ddd_index/?code=J01XB02}{J01XB02}),
|
||||
#' \strong{PRI}: pristinamycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01FG01}{J01FG01}),
|
||||
#' \strong{PZA}: pyrazinamide (\href{https://www.whocc.no/atc_ddd_index/?code=J04AK01}{J04AK01}),
|
||||
#' \strong{QDA}: quinupristin/dalfopristin (\href{https://www.whocc.no/atc_ddd_index/?code=J01FG02}{J01FG02}),
|
||||
#' \strong{RIB}: rifabutin (\href{https://www.whocc.no/atc_ddd_index/?code=J04AB04}{J04AB04}),
|
||||
#' \strong{RIF}: rifampicin (\href{https://www.whocc.no/atc_ddd_index/?code=J04AB02}{J04AB02}),
|
||||
#' \strong{RIF}: rifampin (\href{https://www.whocc.no/atc_ddd_index/?code=J04AB02}{J04AB02}),
|
||||
#' \strong{RFP}: rifapentine (\href{https://www.whocc.no/atc_ddd_index/?code=J04AB05}{J04AB05}),
|
||||
#' \strong{RXT}: roxithromycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01FA06}{J01FA06}),
|
||||
#' \strong{SIS}: sisomicin (\href{https://www.whocc.no/atc_ddd_index/?code=J01GB08}{J01GB08}),
|
||||
#' \strong{TEC}: teicoplanin (\href{https://www.whocc.no/atc_ddd_index/?code=J01XA02}{J01XA02}),
|
||||
#' \strong{TCY}: tetracycline (\href{https://www.whocc.no/atc_ddd_index/?code=J01AA07}{J01AA07}),
|
||||
#' \strong{TIC}: ticarcillin (\href{https://www.whocc.no/atc_ddd_index/?code=J01CA13}{J01CA13}),
|
||||
#' \strong{TGC}: tigecycline (\href{https://www.whocc.no/atc_ddd_index/?code=J01AA12}{J01AA12}),
|
||||
#' \strong{TOB}: tobramycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01GB01}{J01GB01}),
|
||||
#' \strong{TMP}: trimethoprim (\href{https://www.whocc.no/atc_ddd_index/?code=J01EA01}{J01EA01}),
|
||||
#' \strong{SXT}: trimethoprim/sulfamethoxazole (\href{https://www.whocc.no/atc_ddd_index/?code=J01EE01}{J01EE01}),
|
||||
#' \strong{VAN}: vancomycin (\href{https://www.whocc.no/atc_ddd_index/?code=J01XA01}{J01XA01}).
|
||||
#' @keywords interpretive eucast reading resistance
|
||||
#' @rdname eucast_rules
|
||||
#' @export
|
||||
#' @importFrom dplyr %>% select pull mutate_at vars group_by summarise n
|
||||
#' @importFrom crayon bold bgGreen bgYellow bgRed black green blue italic strip_style white red make_style
|
||||
#' @importFrom utils menu
|
||||
#' @return The input of \code{x}, possibly with edited values of antibiotics. Or, if \code{verbose = TRUE}, a \code{data.frame} with all original and new values of the affected bug-drug combinations.
|
||||
#' @source
|
||||
#' \itemize{
|
||||
#' \item{
|
||||
#' EUCAST Expert Rules. Version 2.0, 2012. \cr
|
||||
#' Leclercq et al. \strong{EUCAST expert rules in antimicrobial susceptibility testing.} \emph{Clin Microbiol Infect.} 2013;19(2):141-60. \cr
|
||||
#' \url{https://doi.org/10.1111/j.1469-0691.2011.03703.x}
|
||||
#' }
|
||||
#' \item{
|
||||
#' EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes Tables. Version 3.1, 2016. \cr
|
||||
#' \url{http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf}
|
||||
#' }
|
||||
#' \item{
|
||||
#' EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 9.0, 2019. \cr
|
||||
#' \url{http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_9.0_Breakpoint_Tables.xlsx}
|
||||
#' }
|
||||
#' }
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' a <- data.frame(mo = c("Staphylococcus aureus",
|
||||
#' "Enterococcus faecalis",
|
||||
#' "Escherichia coli",
|
||||
#' "Klebsiella pneumoniae",
|
||||
#' "Pseudomonas aeruginosa"),
|
||||
#' VAN = "-", # Vancomycin
|
||||
#' AMX = "-", # Amoxicillin
|
||||
#' COL = "-", # Colistin
|
||||
#' CAZ = "-", # Ceftazidime
|
||||
#' CXM = "-", # Cefuroxime
|
||||
#' PEN = "S", # Penicillin G
|
||||
#' FOX = "S", # Cefoxitin
|
||||
#' stringsAsFactors = FALSE)
|
||||
#'
|
||||
#' a
|
||||
#' # mo VAN AMX COL CAZ CXM PEN FOX
|
||||
#' # 1 Staphylococcus aureus - - - - - S S
|
||||
#' # 2 Enterococcus faecalis - - - - - S S
|
||||
#' # 3 Escherichia coli - - - - - S S
|
||||
#' # 4 Klebsiella pneumoniae - - - - - S S
|
||||
#' # 5 Pseudomonas aeruginosa - - - - - S S
|
||||
#'
|
||||
#'
|
||||
#' # apply EUCAST rules: 18 results are forced as R or S
|
||||
#' b <- eucast_rules(a)
|
||||
#'
|
||||
#' b
|
||||
#' # mo VAN AMX COL CAZ CXM PEN FOX
|
||||
#' # 1 Staphylococcus aureus - S R R S S S
|
||||
#' # 2 Enterococcus faecalis - - R R R S R
|
||||
#' # 3 Escherichia coli R - - - - R S
|
||||
#' # 4 Klebsiella pneumoniae R R - - - R S
|
||||
#' # 5 Pseudomonas aeruginosa R R - - R R R
|
||||
#'
|
||||
#'
|
||||
#' \donttest{
|
||||
#' # do not apply EUCAST rules, but rather get a data.frame
|
||||
#' # with 18 rows, containing all details about the transformations:
|
||||
#' c <- eucast_rules(a, verbose = TRUE)
|
||||
#' }
|
||||
eucast_rules <- function(x,
|
||||
col_mo = NULL,
|
||||
info = TRUE,
|
||||
rules = c("breakpoints", "expert", "other", "all"),
|
||||
verbose = FALSE,
|
||||
...) {
|
||||
|
||||
if (verbose == TRUE & interactive()) {
|
||||
txt <- paste0("WARNING: In Verbose mode, the eucast_rules() function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way.",
|
||||
"\n\nThis may overwrite your existing data if you use e.g.:",
|
||||
"\ndata <- eucast_rules(data, verbose = TRUE)\n\nDo you want to continue?")
|
||||
if ("rstudioapi" %in% rownames(utils::installed.packages())) {
|
||||
q_continue <- rstudioapi::showQuestion("Using verbose = TRUE with eucast_rules()", txt)
|
||||
} else {
|
||||
q_continue <- menu(choices = c("OK", "Cancel"), graphics = TRUE, title = txt)
|
||||
}
|
||||
if (q_continue %in% c(FALSE, 2)) {
|
||||
message("Cancelled, returning original data")
|
||||
return(x)
|
||||
}
|
||||
}
|
||||
|
||||
if (!is.data.frame(x)) {
|
||||
stop("`x` must be a data frame.", call. = FALSE)
|
||||
}
|
||||
|
||||
# try to find columns based on type
|
||||
# -- mo
|
||||
if (is.null(col_mo)) {
|
||||
col_mo <- search_type_in_df(x = x, type = "mo")
|
||||
}
|
||||
if (is.null(col_mo)) {
|
||||
stop("`col_mo` must be set.", call. = FALSE)
|
||||
}
|
||||
|
||||
if (!all(rules %in% c("breakpoints", "expert", "other", "all"))) {
|
||||
stop("`rules` must be one or more of: 'breakpoints', 'expert', 'other', 'all'.")
|
||||
}
|
||||
|
||||
if (is.null(col_mo)) {
|
||||
stop("`col_mo` must be set")
|
||||
}
|
||||
|
||||
decimal.mark <- getOption("OutDec")
|
||||
big.mark <- ifelse(decimal.mark != ",", ",", ".")
|
||||
formatnr <- function(x) {
|
||||
trimws(format(x, big.mark = big.mark, decimal.mark = decimal.mark))
|
||||
}
|
||||
|
||||
grey <- make_style("grey")
|
||||
|
||||
warned <- FALSE
|
||||
|
||||
txt_error <- function() {
|
||||
cat("", bgRed(white(" ERROR ")), "\n\n")
|
||||
}
|
||||
txt_warning <- function() {
|
||||
if (warned == FALSE) {
|
||||
cat("", bgYellow(black(" WARNING ")))
|
||||
}
|
||||
warned <<- TRUE
|
||||
}
|
||||
txt_ok <- function(no_added, no_changed) {
|
||||
if (warned == FALSE) {
|
||||
if (no_added + no_changed == 0) {
|
||||
cat(pillar::style_subtle(" (no changes)\n"))
|
||||
} else {
|
||||
# opening
|
||||
cat(grey(" ("))
|
||||
# additions
|
||||
if (no_added > 0) {
|
||||
if (no_added == 1) {
|
||||
cat(green("1 value added"))
|
||||
} else {
|
||||
cat(green(formatnr(no_added), "values added"))
|
||||
}
|
||||
}
|
||||
# separator
|
||||
if (no_added > 0 & no_changed > 0) {
|
||||
cat(grey(", "))
|
||||
}
|
||||
# changes
|
||||
if (no_changed > 0) {
|
||||
if (no_changed == 1) {
|
||||
cat(blue("1 value changed"))
|
||||
} else {
|
||||
cat(blue(formatnr(no_changed), "values changed"))
|
||||
}
|
||||
}
|
||||
# closing
|
||||
cat(grey(")\n"))
|
||||
}
|
||||
warned <<- FALSE
|
||||
}
|
||||
}
|
||||
|
||||
cols_ab <- get_column_abx(x = x,
|
||||
soft_dependencies = c("AMC",
|
||||
"AMK",
|
||||
"AMX",
|
||||
"AMP",
|
||||
"AZM",
|
||||
"AZL",
|
||||
"ATM",
|
||||
"RID",
|
||||
"FEP",
|
||||
"CTX",
|
||||
"FOX",
|
||||
"CED",
|
||||
"CAZ",
|
||||
"CRO",
|
||||
"CXM",
|
||||
"CHL",
|
||||
"CIP",
|
||||
"CLR",
|
||||
"CLI",
|
||||
"FLC",
|
||||
"COL",
|
||||
"CZO",
|
||||
"DAP",
|
||||
"DOX",
|
||||
"ETP",
|
||||
"ERY",
|
||||
"FOS",
|
||||
"FUS",
|
||||
"GEN",
|
||||
"IPM",
|
||||
"KAN",
|
||||
"LVX",
|
||||
"LIN",
|
||||
"LNZ",
|
||||
"MEM",
|
||||
"MEZ",
|
||||
"MNO",
|
||||
"MFX",
|
||||
"NAL",
|
||||
"NEO",
|
||||
"NET",
|
||||
"NIT",
|
||||
"NOR",
|
||||
"NOV",
|
||||
"OFX",
|
||||
"OXA",
|
||||
"PEN",
|
||||
"PIP",
|
||||
"TZP",
|
||||
"PLB",
|
||||
"PRI",
|
||||
"QDA",
|
||||
"RIF",
|
||||
"RXT",
|
||||
"SIS",
|
||||
"TEC",
|
||||
"TCY",
|
||||
"TIC",
|
||||
"TGC",
|
||||
"TOB",
|
||||
"TMP",
|
||||
"SXT",
|
||||
"VAN"),
|
||||
hard_dependencies = NULL,
|
||||
verbose = verbose,
|
||||
...)
|
||||
|
||||
AMC <- cols_ab["AMC"]
|
||||
AMK <- cols_ab["AMK"]
|
||||
AMP <- cols_ab["AMP"]
|
||||
AMX <- cols_ab["AMX"]
|
||||
ATM <- cols_ab["ATM"]
|
||||
AZL <- cols_ab["AZL"]
|
||||
AZM <- cols_ab["AZM"]
|
||||
CAZ <- cols_ab["CAZ"]
|
||||
CED <- cols_ab["CED"]
|
||||
CHL <- cols_ab["CHL"]
|
||||
CIP <- cols_ab["CIP"]
|
||||
CLI <- cols_ab["CLI"]
|
||||
CLR <- cols_ab["CLR"]
|
||||
COL <- cols_ab["COL"]
|
||||
CRO <- cols_ab["CRO"]
|
||||
CTX <- cols_ab["CTX"]
|
||||
CXM <- cols_ab["CXM"]
|
||||
CZO <- cols_ab["CZO"]
|
||||
DAP <- cols_ab["DAP"]
|
||||
DOX <- cols_ab["DOX"]
|
||||
ERY <- cols_ab["ERY"]
|
||||
ETP <- cols_ab["ETP"]
|
||||
FEP <- cols_ab["FEP"]
|
||||
FLC <- cols_ab["FLC"]
|
||||
FOS <- cols_ab["FOS"]
|
||||
FOX <- cols_ab["FOX"]
|
||||
FUS <- cols_ab["FUS"]
|
||||
GEN <- cols_ab["GEN"]
|
||||
IPM <- cols_ab["IPM"]
|
||||
KAN <- cols_ab["KAN"]
|
||||
LIN <- cols_ab["LIN"]
|
||||
LNZ <- cols_ab["LNZ"]
|
||||
LVX <- cols_ab["LVX"]
|
||||
MEM <- cols_ab["MEM"]
|
||||
MEZ <- cols_ab["MEZ"]
|
||||
MFX <- cols_ab["MFX"]
|
||||
MNO <- cols_ab["MNO"]
|
||||
NAL <- cols_ab["NAL"]
|
||||
NEO <- cols_ab["NEO"]
|
||||
NET <- cols_ab["NET"]
|
||||
NIT <- cols_ab["NIT"]
|
||||
NOR <- cols_ab["NOR"]
|
||||
NOV <- cols_ab["NOV"]
|
||||
OFX <- cols_ab["OFX"]
|
||||
OXA <- cols_ab["OXA"]
|
||||
PEN <- cols_ab["PEN"]
|
||||
PIP <- cols_ab["PIP"]
|
||||
PLB <- cols_ab["PLB"]
|
||||
PRI <- cols_ab["PRI"]
|
||||
QDA <- cols_ab["QDA"]
|
||||
RID <- cols_ab["RID"]
|
||||
RIF <- cols_ab["RIF"]
|
||||
RXT <- cols_ab["RXT"]
|
||||
SIS <- cols_ab["SIS"]
|
||||
SXT <- cols_ab["SXT"]
|
||||
TCY <- cols_ab["TCY"]
|
||||
TEC <- cols_ab["TEC"]
|
||||
TGC <- cols_ab["TGC"]
|
||||
TIC <- cols_ab["TIC"]
|
||||
TMP <- cols_ab["TMP"]
|
||||
TOB <- cols_ab["TOB"]
|
||||
TZP <- cols_ab["TZP"]
|
||||
VAN <- cols_ab["VAN"]
|
||||
|
||||
ab_missing <- function(ab) {
|
||||
all(ab %in% c(NULL, NA))
|
||||
}
|
||||
|
||||
verbose_info <- data.frame(row = integer(0),
|
||||
col = character(0),
|
||||
mo_fullname = character(0),
|
||||
old = as.rsi(character(0)),
|
||||
new = as.rsi(character(0)),
|
||||
rule = character(0),
|
||||
rule_group = character(0),
|
||||
rule_name = character(0),
|
||||
stringsAsFactors = FALSE)
|
||||
|
||||
# helper function for editing the table
|
||||
edit_rsi <- function(to, rule, rows, cols) {
|
||||
cols <- unique(cols[!is.na(cols) & !is.null(cols)])
|
||||
if (length(rows) > 0 & length(cols) > 0) {
|
||||
before_df <- x_original
|
||||
|
||||
tryCatch(
|
||||
# insert into original table
|
||||
x_original[rows, cols] <<- to,
|
||||
warning = function(w) {
|
||||
if (w$message %like% "invalid factor level") {
|
||||
x_original <<- x_original %>% mutate_at(vars(cols), ~factor(x = as.character(.), levels = c(to, levels(.))))
|
||||
x <<- x %>% mutate_at(vars(cols), ~factor(x = as.character(.), levels = c(to, levels(.))))
|
||||
x_original[rows, cols] <<- to
|
||||
warning('Value "', to, '" added to the factor levels of column(s) `', paste(cols, collapse = "`, `"), "` because this value was not an existing factor level.\nA better way is to use as.rsi() on beforehand on antimicrobial columns to guarantee the right structure.", call. = FALSE)
|
||||
txt_warning()
|
||||
warned <<- FALSE
|
||||
} else {
|
||||
warning(w$message, call. = FALSE)
|
||||
txt_warning()
|
||||
cat("\n") # txt_warning() does not append a "\n" on itself
|
||||
}
|
||||
},
|
||||
error = function(e) {
|
||||
txt_error()
|
||||
stop(paste0("In row(s) ", paste(rows[1:min(length(rows), 10)], collapse = ","),
|
||||
ifelse(length(rows) > 10, "...", ""),
|
||||
" while writing value '", to,
|
||||
"' to column(s) `", paste(cols, collapse = "`, `"),
|
||||
"`:\n", e$message),
|
||||
call. = FALSE)
|
||||
}
|
||||
)
|
||||
|
||||
tryCatch(
|
||||
x[rows, cols] <<- x_original[rows, cols],
|
||||
error = function(e) {
|
||||
stop(paste0("In row(s) ", paste(rows[1:min(length(rows), 10)], collapse = ","),
|
||||
"... while writing value '", to,
|
||||
"' to column(s) `", paste(cols, collapse = "`, `"),
|
||||
"`:\n", e$message), call. = FALSE)
|
||||
}
|
||||
)
|
||||
|
||||
# before_df might not be a data.frame, but a tibble or data.table instead
|
||||
old <- as.data.frame(before_df, stringsAsFactors = FALSE)[rows, ]
|
||||
track_changes <- list(added = 0,
|
||||
changed = 0)
|
||||
for (i in seq_len(length(cols))) {
|
||||
verbose_new <- data.frame(row = rows,
|
||||
col = cols[i],
|
||||
mo_fullname = x[rows, "fullname"],
|
||||
old = as.rsi(as.character(old[, cols[i]]), warn = FALSE),
|
||||
new = as.rsi(as.character(x[rows, cols[i]])),
|
||||
rule = strip_style(rule[1]),
|
||||
rule_group = strip_style(rule[2]),
|
||||
rule_name = strip_style(rule[3]),
|
||||
stringsAsFactors = FALSE)
|
||||
colnames(verbose_new) <- c("row", "col", "mo_fullname", "old", "new", "rule", "rule_group", "rule_name")
|
||||
verbose_new <- verbose_new %>% filter(old != new | is.na(old))
|
||||
# save changes to data set 'verbose_info'
|
||||
verbose_info <<- rbind(verbose_info, verbose_new)
|
||||
# count adds and changes
|
||||
track_changes$added <- track_changes$added + verbose_new %>% filter(is.na(old)) %>% nrow()
|
||||
track_changes$changed <- track_changes$changed + verbose_new %>% filter(!is.na(old)) %>% nrow()
|
||||
}
|
||||
# after the applied changes: return list with counts of added and changed
|
||||
return(track_changes)
|
||||
}
|
||||
# no changes were applied: return number of (new) changes: none.
|
||||
return(list(added = 0,
|
||||
changed = 0))
|
||||
}
|
||||
|
||||
# save original table
|
||||
x_original <- x
|
||||
|
||||
# join to microorganisms data set
|
||||
suppressWarnings(
|
||||
x <- x %>%
|
||||
mutate_at(vars(col_mo), as.mo) %>%
|
||||
left_join_microorganisms(by = col_mo, suffix = c("_oldcols", "")) %>%
|
||||
mutate(gramstain = mo_gramstain(pull(., col_mo), language = "en"),
|
||||
genus_species = paste(genus, species)) %>%
|
||||
as.data.frame(stringsAsFactors = FALSE)
|
||||
)
|
||||
|
||||
if (info == TRUE) {
|
||||
cat(paste0(
|
||||
"\nRules by the ", bold("European Committee on Antimicrobial Susceptibility Testing (EUCAST)"),
|
||||
"\n", blue("http://eucast.org/"), "\n"))
|
||||
}
|
||||
|
||||
# since ampicillin ^= amoxicillin, get the first from the latter (not in original EUCAST table)
|
||||
if (!ab_missing(AMP) & !ab_missing(AMX)) {
|
||||
if (verbose == TRUE) {
|
||||
cat("\n VERBOSE: transforming",
|
||||
length(which(x[, AMX] == "S" & !x[, AMP] %in% c("S", "I", "R"))),
|
||||
"empty ampicillin fields to 'S' based on amoxicillin. ")
|
||||
cat("\n VERBOSE: transforming",
|
||||
length(which(x[, AMX] == "I" & !x[, AMP] %in% c("S", "I", "R"))),
|
||||
"empty ampicillin fields to 'I' based on amoxicillin. ")
|
||||
cat("\n VERBOSE: transforming",
|
||||
length(which(x[, AMX] == "R" & !x[, AMP] %in% c("S", "I", "R"))),
|
||||
"empty ampicillin fields to 'R' based on amoxicillin. \n")
|
||||
}
|
||||
x[which(x[, AMX] == "S" & !x[, AMP] %in% c("S", "I", "R")), AMP] <- "S"
|
||||
x[which(x[, AMX] == "I" & !x[, AMP] %in% c("S", "I", "R")), AMP] <- "I"
|
||||
x[which(x[, AMX] == "R" & !x[, AMP] %in% c("S", "I", "R")), AMP] <- "R"
|
||||
} else if (ab_missing(AMP) & !ab_missing(AMX)) {
|
||||
# ampicillin column is missing, but amoxicillin is available
|
||||
message(blue(paste0("NOTE: Using column `", bold(AMX), "` as input for ampicillin (J01CA01) since many EUCAST rules depend on it.")))
|
||||
AMP <- AMX
|
||||
}
|
||||
|
||||
# nolint start
|
||||
# antibiotic classes
|
||||
aminoglycosides <- c(TOB, GEN, KAN, NEO, NET, SIS)
|
||||
tetracyclines <- c(DOX, MNO, TCY) # since EUCAST v3.1 tigecycline (TGC) is set apart
|
||||
polymyxins <- c(PLB, COL)
|
||||
macrolides <- c(ERY, AZM, RXT, CLR) # since EUCAST v3.1 clinda is set apart
|
||||
glycopeptides <- c(VAN, TEC)
|
||||
streptogramins <- c(QDA, PRI) # should officially also be quinupristin/dalfopristin
|
||||
aminopenicillins <- c(AMP, AMX)
|
||||
cephalosporins <- c(FEP, CTX, FOX, CED, CAZ, CRO, CXM, CZO)
|
||||
cephalosporins_without_CAZ <- cephalosporins[cephalosporins != ifelse(is.null(CAZ), "", CAZ)]
|
||||
carbapenems <- c(ETP, IPM, MEM)
|
||||
ureidopenicillins <- c(PIP, TZP, AZL, MEZ)
|
||||
all_betalactams <- c(aminopenicillins, cephalosporins, carbapenems, ureidopenicillins, AMC, OXA, FLC, PEN)
|
||||
fluoroquinolones <- c(OFX, CIP, NOR, LVX, MFX)
|
||||
# nolint end
|
||||
|
||||
# Help function to get available antibiotic column names ------------------
|
||||
get_antibiotic_columns <- function(x, df) {
|
||||
x <- trimws(unlist(strsplit(x, ",", fixed = TRUE)))
|
||||
y <- character(0)
|
||||
for (i in seq_len(length(x))) {
|
||||
if (is.function(get(x[i]))) {
|
||||
stop("Column ", x[i], " is also a function. Please create an issue on github.com/msberends/AMR/issues.")
|
||||
}
|
||||
y <- c(y, tryCatch(get(x[i]), error = function(e) ""))
|
||||
}
|
||||
y[y != "" & y %in% colnames(df)]
|
||||
}
|
||||
get_antibiotic_names <- function(x) {
|
||||
x %>%
|
||||
strsplit(",") %>%
|
||||
unlist() %>%
|
||||
trimws() %>%
|
||||
sapply(function(x) if (x %in% AMR::antibiotics$ab) ab_name(x, language = NULL, tolower = TRUE) else x) %>%
|
||||
sort() %>%
|
||||
paste(collapse = ", ")
|
||||
}
|
||||
format_antibiotic_names <- function(ab_names, ab_results) {
|
||||
ab_names <- trimws(unlist(strsplit(ab_names, ",")))
|
||||
ab_results <- trimws(unlist(strsplit(ab_results, ",")))
|
||||
if (length(ab_results) == 1) {
|
||||
if (length(ab_names) == 1) {
|
||||
# like FOX S
|
||||
x <- paste(ab_names, "is")
|
||||
} else if (length(ab_names) == 2) {
|
||||
# like PEN,FOX S
|
||||
x <- paste(paste0(ab_names, collapse = " and "), "are both")
|
||||
} else {
|
||||
# like PEN,FOX,GEN S (although dependency on > 2 ABx does not exist at the moment)
|
||||
x <- paste(paste0(ab_names, collapse = " and "), "are all")
|
||||
}
|
||||
return(paste0(x, " '", ab_results, "'"))
|
||||
} else {
|
||||
if (length(ab_names) == 2) {
|
||||
# like PEN,FOX S,R
|
||||
paste0(ab_names[1], " is '", ab_results[1], "' and ",
|
||||
ab_names[2], " is '", ab_results[2], "'")
|
||||
} else {
|
||||
# like PEN,FOX,GEN S,R,R (although dependency on > 2 ABx does not exist at the moment)
|
||||
paste0(ab_names[1], " is '", ab_results[1], "' and ",
|
||||
ab_names[2], " is '", ab_results[2], "' and ",
|
||||
ab_names[3], " is '", ab_results[3], "'")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
eucast_rules_df <- eucast_rules_file # internal data file
|
||||
no_added <- 0
|
||||
no_changed <- 0
|
||||
for (i in seq_len(nrow(eucast_rules_df))) {
|
||||
|
||||
rule_previous <- eucast_rules_df[max(1, i - 1), "reference.rule"]
|
||||
rule_current <- eucast_rules_df[i, "reference.rule"]
|
||||
rule_next <- eucast_rules_df[min(nrow(eucast_rules_df), i + 1), "reference.rule"]
|
||||
rule_group_previous <- eucast_rules_df[max(1, i - 1), "reference.rule_group"]
|
||||
rule_group_current <- eucast_rules_df[i, "reference.rule_group"]
|
||||
if (is.na(eucast_rules_df[i, 4])) {
|
||||
rule_text <- paste0("always report as '", eucast_rules_df[i, 7], "': ", get_antibiotic_names(eucast_rules_df[i, 6]))
|
||||
} else {
|
||||
rule_text <- paste0("report as '", eucast_rules_df[i, 7], "' when ",
|
||||
format_antibiotic_names(ab_names = get_antibiotic_names(eucast_rules_df[i, 4]),
|
||||
ab_results = eucast_rules_df[i, 5]), ": ",
|
||||
get_antibiotic_names(eucast_rules_df[i, 6]))
|
||||
}
|
||||
if (i == 1) {
|
||||
rule_previous <- ""
|
||||
rule_group_previous <- ""
|
||||
}
|
||||
if (i == nrow(eucast_rules_df)) {
|
||||
rule_next <- ""
|
||||
}
|
||||
|
||||
# don't apply rules if user doesn't want to apply them
|
||||
if (rule_group_current %like% "breakpoint" & !any(c("all", "breakpoints") %in% rules)) {
|
||||
next
|
||||
}
|
||||
if (rule_group_current %like% "expert" & !any(c("all", "expert") %in% rules)) {
|
||||
next
|
||||
}
|
||||
if (rule_group_current %like% "other" & !any(c("all", "other") %in% rules)) {
|
||||
next
|
||||
}
|
||||
|
||||
|
||||
if (info == TRUE) {
|
||||
# Print rule (group) ------------------------------------------------------
|
||||
if (rule_group_current != rule_group_previous) {
|
||||
# is new rule group, one of Breakpoints, Expert Rules and Other
|
||||
cat(bold(
|
||||
case_when(
|
||||
rule_group_current %like% "breakpoint" ~
|
||||
paste0("\nEUCAST Clinical Breakpoints (v", EUCAST_VERSION_BREAKPOINTS, ")\n"),
|
||||
rule_group_current %like% "expert" ~
|
||||
paste0("\nEUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v", EUCAST_VERSION_EXPERT_RULES, ")\n"),
|
||||
TRUE ~
|
||||
"\nOther rules\n"
|
||||
)
|
||||
))
|
||||
}
|
||||
# Print rule -------------------------------------------------------------
|
||||
if (rule_current != rule_previous) {
|
||||
# is new rule within group, print its name
|
||||
if (rule_current %in% c(AMR::microorganisms$family,
|
||||
AMR::microorganisms$fullname)) {
|
||||
cat(italic(rule_current))
|
||||
} else {
|
||||
cat(rule_current)
|
||||
}
|
||||
warned <- FALSE
|
||||
}
|
||||
}
|
||||
|
||||
# Get rule from file ------------------------------------------------------
|
||||
col_mo_property <- eucast_rules_df[i, 1]
|
||||
like_is_one_of <- eucast_rules_df[i, 2]
|
||||
|
||||
# be sure to comprise all coagulase-negative/-positive Staphylococci when they are mentioned
|
||||
if (eucast_rules_df[i, 3] %like% "coagulase-") {
|
||||
suppressWarnings(
|
||||
all_staph <- AMR::microorganisms %>%
|
||||
filter(genus == "Staphylococcus") %>%
|
||||
mutate(CNS_CPS = mo_name(mo, Becker = "all"))
|
||||
)
|
||||
if (eucast_rules_df[i, 3] %like% "coagulase-") {
|
||||
eucast_rules_df[i, 3] <- paste0("^(",
|
||||
paste0(all_staph %>%
|
||||
filter(CNS_CPS %like% "coagulase-negative") %>%
|
||||
pull(fullname),
|
||||
collapse = "|"),
|
||||
")$")
|
||||
} else {
|
||||
eucast_rules_df[i, 3] <- paste0("^(",
|
||||
paste0(all_staph %>%
|
||||
filter(CNS_CPS %like% "coagulase-positive") %>%
|
||||
pull(fullname),
|
||||
collapse = "|"),
|
||||
")$")
|
||||
}
|
||||
like_is_one_of <- "like"
|
||||
}
|
||||
|
||||
if (like_is_one_of == "is") {
|
||||
mo_value <- paste0("^", eucast_rules_df[i, 3], "$")
|
||||
} else if (like_is_one_of == "one_of") {
|
||||
# so 'Clostridium, Actinomyces, ...' will turn into '^(Clostridium|Actinomyces|...)$'
|
||||
mo_value <- paste0("^(",
|
||||
paste(trimws(unlist(strsplit(eucast_rules_df[i, 3], ",", fixed = TRUE))),
|
||||
collapse = "|"),
|
||||
")$")
|
||||
} else if (like_is_one_of == "like") {
|
||||
mo_value <- eucast_rules_df[i, 3]
|
||||
} else {
|
||||
stop("invalid like_is_one_of", call. = FALSE)
|
||||
}
|
||||
|
||||
source_antibiotics <- eucast_rules_df[i, 4]
|
||||
source_value <- trimws(unlist(strsplit(eucast_rules_df[i, 5], ",", fixed = TRUE)))
|
||||
target_antibiotics <- eucast_rules_df[i, 6]
|
||||
target_value <- eucast_rules_df[i, 7]
|
||||
|
||||
if (is.na(source_antibiotics)) {
|
||||
rows <- tryCatch(which(x[, col_mo_property] %like% mo_value),
|
||||
error = function(e) integer(0))
|
||||
} else {
|
||||
source_antibiotics <- get_antibiotic_columns(source_antibiotics, x)
|
||||
if (length(source_value) == 1 & length(source_antibiotics) > 1) {
|
||||
source_value <- rep(source_value, length(source_antibiotics))
|
||||
}
|
||||
if (length(source_antibiotics) == 0) {
|
||||
rows <- integer(0)
|
||||
} else if (length(source_antibiotics) == 1) {
|
||||
rows <- tryCatch(which(x[, col_mo_property] %like% mo_value
|
||||
& x[, source_antibiotics[1L]] == source_value[1L]),
|
||||
error = function(e) integer(0))
|
||||
} else if (length(source_antibiotics) == 2) {
|
||||
rows <- tryCatch(which(x[, col_mo_property] %like% mo_value
|
||||
& x[, source_antibiotics[1L]] == source_value[1L]
|
||||
& x[, source_antibiotics[2L]] == source_value[2L]),
|
||||
error = function(e) integer(0))
|
||||
} else if (length(source_antibiotics) == 3) {
|
||||
rows <- tryCatch(which(x[, col_mo_property] %like% mo_value
|
||||
& x[, source_antibiotics[1L]] == source_value[1L]
|
||||
& x[, source_antibiotics[2L]] == source_value[2L]
|
||||
& x[, source_antibiotics[3L]] == source_value[3L]),
|
||||
error = function(e) integer(0))
|
||||
} else {
|
||||
stop("only 3 antibiotics supported for source_antibiotics ", call. = FALSE)
|
||||
}
|
||||
}
|
||||
|
||||
cols <- get_antibiotic_columns(target_antibiotics, x)
|
||||
|
||||
# Apply rule on data ------------------------------------------------------
|
||||
# this will return the unique number of changes
|
||||
run_changes <- edit_rsi(to = target_value,
|
||||
rule = c(rule_text, rule_group_current, rule_current),
|
||||
rows = rows,
|
||||
cols = cols)
|
||||
no_added <- no_added + run_changes$added
|
||||
no_changed <- no_changed + run_changes$changed
|
||||
|
||||
# Print number of new changes ---------------------------------------------
|
||||
if (info == TRUE & rule_next != rule_current) {
|
||||
# print only on last one of rules in this group
|
||||
txt_ok(no_added = no_added, no_changed = no_changed)
|
||||
# and reset counters
|
||||
no_added <- 0
|
||||
no_changed <- 0
|
||||
}
|
||||
}
|
||||
|
||||
# Print overview ----------------------------------------------------------
|
||||
if (info == TRUE) {
|
||||
if (verbose == TRUE) {
|
||||
wouldve <- "would have "
|
||||
} else {
|
||||
wouldve <- ""
|
||||
}
|
||||
|
||||
verbose_info <- verbose_info %>%
|
||||
arrange(row, rule_group, rule_name, col)
|
||||
|
||||
cat(paste0("\n", grey(strrep("-", options()$width - 1)), "\n"))
|
||||
cat(bold(paste("EUCAST rules", paste0(wouldve, "affected"),
|
||||
formatnr(n_distinct(verbose_info$row)),
|
||||
"out of", formatnr(nrow(x_original)),
|
||||
"rows, making a total of", formatnr(nrow(verbose_info)), "edits\n")))
|
||||
|
||||
n_added <- verbose_info %>% filter(is.na(old)) %>% nrow()
|
||||
n_changed <- verbose_info %>% filter(!is.na(old)) %>% nrow()
|
||||
|
||||
# print added values ----
|
||||
if (n_added == 0) {
|
||||
colour <- cat # is function
|
||||
} else {
|
||||
colour <- green # is function
|
||||
}
|
||||
cat(colour(paste0("=> ", wouldve, "added ",
|
||||
bold(formatnr(verbose_info %>%
|
||||
filter(is.na(old)) %>%
|
||||
nrow()), "test results"),
|
||||
"\n")))
|
||||
if (n_added > 0) {
|
||||
verbose_info %>%
|
||||
filter(is.na(old)) %>%
|
||||
group_by(new) %>%
|
||||
summarise(n = n()) %>%
|
||||
mutate(plural = ifelse(n > 1, "s", ""),
|
||||
txt = paste0(formatnr(n), " test result", plural, " added as ", new)) %>%
|
||||
pull(txt) %>%
|
||||
paste(" -", ., collapse = "\n") %>%
|
||||
cat()
|
||||
}
|
||||
|
||||
# print changed values ----
|
||||
if (n_changed == 0) {
|
||||
colour <- cat # is function
|
||||
} else {
|
||||
colour <- blue # is function
|
||||
}
|
||||
if (n_added + n_changed > 0) {
|
||||
cat("\n")
|
||||
}
|
||||
cat(colour(paste0("=> ", wouldve, "changed ",
|
||||
bold(formatnr(verbose_info %>%
|
||||
filter(!is.na(old)) %>%
|
||||
nrow()), "test results"),
|
||||
"\n")))
|
||||
if (n_changed > 0) {
|
||||
verbose_info %>%
|
||||
filter(!is.na(old)) %>%
|
||||
group_by(old, new) %>%
|
||||
summarise(n = n()) %>%
|
||||
mutate(plural = ifelse(n > 1, "s", ""),
|
||||
txt = paste0(formatnr(n), " test result", plural, " changed from ", old, " to ", new)) %>%
|
||||
pull(txt) %>%
|
||||
paste(" -", ., collapse = "\n") %>%
|
||||
cat()
|
||||
cat("\n")
|
||||
}
|
||||
cat(paste0(grey(strrep("-", options()$width - 1)), "\n"))
|
||||
|
||||
if (verbose == FALSE & nrow(verbose_info) > 0) {
|
||||
cat(paste("\nUse", bold("eucast_rules(..., verbose = TRUE)"), "(on your original data) to get a data.frame with all specified edits instead.\n\n"))
|
||||
} else if (verbose == TRUE) {
|
||||
cat(paste0("\nUsed 'Verbose mode' (", bold("verbose = TRUE"), "), which returns a data.frame with all specified edits.\nUse ", bold("verbose = FALSE"), " to apply the rules on your data.\n\n"))
|
||||
}
|
||||
}
|
||||
|
||||
# Return data set ---------------------------------------------------------
|
||||
if (verbose == TRUE) {
|
||||
verbose_info
|
||||
} else {
|
||||
x_original
|
||||
}
|
||||
}
|
||||
@@ -1,47 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Extended functions
|
||||
#'
|
||||
#' These functions are extensions of functions in other packages.
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @export
|
||||
#' @keywords internal
|
||||
#' @name extended-functions
|
||||
#' @rdname extended-functions
|
||||
#' @exportMethod scale_type.mo
|
||||
#' @export
|
||||
scale_type.mo <- function(x) {
|
||||
# fix for:
|
||||
# "Don't know how to automatically pick scale for object of type mo. Defaulting to continuous."
|
||||
# "Error: Discrete value supplied to continuous scale"
|
||||
"discrete"
|
||||
}
|
||||
|
||||
#' @rdname extended-functions
|
||||
#' @exportMethod scale_type.ab
|
||||
#' @export
|
||||
scale_type.ab <- function(x) {
|
||||
# fix for:
|
||||
# "Don't know how to automatically pick scale for object of type mo. Defaulting to continuous."
|
||||
# "Error: Discrete value supplied to continuous scale"
|
||||
"discrete"
|
||||
}
|
||||
@@ -1,324 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Filter isolates on result in antibiotic class
|
||||
#'
|
||||
#' Filter isolates on results in specific antibiotic variables based on their class (ATC groups). This makes it easy to get a list of isolates that were tested for e.g. any aminoglycoside.
|
||||
#' @param x a data set
|
||||
#' @param ab_class an antimicrobial class, like \code{"carbapenems"}, as can be found in \code{AMR::antibiotics$group}
|
||||
#' @param result an antibiotic result: S, I or R (or a combination of more of them)
|
||||
#' @param scope the scope to check which variables to check, can be \code{"any"} (default) or \code{"all"}
|
||||
#' @param ... parameters passed on to \code{filter_at} from the \code{dplyr} package
|
||||
#' @details The \code{group} column in \code{\link{antibiotics}} data set will be searched for \code{ab_class} (case-insensitive). If no results are found, the \code{atc_group1} and \code{atc_group2} columns will be searched. Next, \code{x} will be checked for column names with a value in any abbreviations, codes or official names found in the \code{antibiotics} data set.
|
||||
#' @rdname filter_ab_class
|
||||
#' @keywords filter fillter_class
|
||||
#' @importFrom dplyr filter_at %>% select vars any_vars all_vars
|
||||
#' @importFrom crayon bold blue
|
||||
#' @export
|
||||
#' @examples
|
||||
#' library(dplyr)
|
||||
#'
|
||||
#' # filter on isolates that have any result for any aminoglycoside
|
||||
#' example_isolates %>% filter_aminoglycosides()
|
||||
#'
|
||||
#' # this is essentially the same as (but without determination of column names):
|
||||
#' example_isolates %>%
|
||||
#' filter_at(.vars = vars(c("GEN", "TOB", "AMK", "KAN")),
|
||||
#' .vars_predicate = any_vars(. %in% c("S", "I", "R")))
|
||||
#'
|
||||
#'
|
||||
#' # filter on isolates that show resistance to ANY aminoglycoside
|
||||
#' example_isolates %>% filter_aminoglycosides("R")
|
||||
#'
|
||||
#' # filter on isolates that show resistance to ALL aminoglycosides
|
||||
#' example_isolates %>% filter_aminoglycosides("R", "all")
|
||||
#'
|
||||
#' # filter on isolates that show resistance to
|
||||
#' # any aminoglycoside and any fluoroquinolone
|
||||
#' example_isolates %>%
|
||||
#' filter_aminoglycosides("R") %>%
|
||||
#' filter_fluoroquinolones("R")
|
||||
#'
|
||||
#' # filter on isolates that show resistance to
|
||||
#' # all aminoglycosides and all fluoroquinolones
|
||||
#' example_isolates %>%
|
||||
#' filter_aminoglycosides("R", "all") %>%
|
||||
#' filter_fluoroquinolones("R", "all")
|
||||
filter_ab_class <- function(x,
|
||||
ab_class,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
scope <- scope[1L]
|
||||
if (is.null(result)) {
|
||||
result <- c("S", "I", "R")
|
||||
}
|
||||
# make result = "SI" work too:
|
||||
result <- unlist(strsplit(result, ""))
|
||||
|
||||
if (!all(result %in% c("S", "I", "R"))) {
|
||||
stop("`result` must be one or more of: S, I, R", call. = FALSE)
|
||||
}
|
||||
if (!all(scope %in% c("any", "all"))) {
|
||||
stop("`scope` must be one of: any, all", call. = FALSE)
|
||||
}
|
||||
|
||||
vars_df <- colnames(x)[tolower(colnames(x)) %in% tolower(ab_class_vars(ab_class))]
|
||||
ab_group <- find_ab_group(ab_class)
|
||||
|
||||
if (length(vars_df) > 0) {
|
||||
if (length(result) == 1) {
|
||||
operator <- " is "
|
||||
} else {
|
||||
operator <- " is one of "
|
||||
}
|
||||
if (scope == "any") {
|
||||
scope_txt <- " or "
|
||||
scope_fn <- any_vars
|
||||
} else {
|
||||
scope_txt <- " and "
|
||||
scope_fn <- all_vars
|
||||
if (length(vars_df) > 1) {
|
||||
operator <- gsub("is", "are", operator)
|
||||
}
|
||||
}
|
||||
if (length(vars_df) > 1) {
|
||||
scope <- paste(scope, "of columns ")
|
||||
} else {
|
||||
scope <- "column "
|
||||
}
|
||||
message(blue(paste0("Filtering on ", ab_group, ": ", scope,
|
||||
paste(bold(paste0("`", vars_df, "`")), collapse = scope_txt), operator, toString(result))))
|
||||
x %>%
|
||||
filter_at(vars(vars_df),
|
||||
scope_fn(. %in% result),
|
||||
...)
|
||||
} else {
|
||||
warning(paste0("no antibiotics of class ", ab_group, " found, leaving data unchanged"), call. = FALSE)
|
||||
x
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_aminoglycosides <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "aminoglycoside",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_carbapenems <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "carbapenem",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_cephalosporins <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "cephalosporin",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_1st_cephalosporins <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "cephalosporins (1st gen.)",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_2nd_cephalosporins <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "cephalosporins (2nd gen.)",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_3rd_cephalosporins <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "cephalosporins (3rd gen.)",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_4th_cephalosporins <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "cephalosporins (4th gen.)",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_5th_cephalosporins <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "cephalosporins (5th gen.)",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_fluoroquinolones <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "fluoroquinolone",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_glycopeptides <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "glycopeptide",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_macrolides <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "macrolide",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @rdname filter_ab_class
|
||||
#' @export
|
||||
filter_tetracyclines <- function(x,
|
||||
result = NULL,
|
||||
scope = "any",
|
||||
...) {
|
||||
filter_ab_class(x = x,
|
||||
ab_class = "tetracycline",
|
||||
result = result,
|
||||
scope = scope,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @importFrom dplyr %>% filter_at vars any_vars select
|
||||
ab_class_vars <- function(ab_class) {
|
||||
ab_class <- gsub("[^a-z0-9]+", ".*", ab_class)
|
||||
ab_vars <- AMR::antibiotics %>%
|
||||
filter(group %like% ab_class) %>%
|
||||
select(ab:name, abbreviations, synonyms) %>%
|
||||
unlist() %>%
|
||||
as.matrix() %>%
|
||||
as.character() %>%
|
||||
paste(collapse = "|") %>%
|
||||
strsplit("|", fixed = TRUE) %>%
|
||||
unlist() %>%
|
||||
unique()
|
||||
ab_vars <- ab_vars[!ab_vars %in% c(NA, "", "NA") & nchar(ab_vars) > 2]
|
||||
if (length(ab_vars) == 0) {
|
||||
# try again, searching atc_group1 and atc_group2 columns
|
||||
ab_vars <- AMR::antibiotics %>%
|
||||
filter_at(vars(c("atc_group1", "atc_group2")), any_vars(. %like% ab_class)) %>%
|
||||
select(ab:name, abbreviations, synonyms) %>%
|
||||
unlist() %>%
|
||||
as.matrix() %>%
|
||||
as.character() %>%
|
||||
paste(collapse = "|") %>%
|
||||
strsplit("|", fixed = TRUE) %>%
|
||||
unlist() %>%
|
||||
unique()
|
||||
ab_vars <- ab_vars[!ab_vars %in% c(NA, "", "NA") & nchar(ab_vars) > 2]
|
||||
}
|
||||
ab_vars
|
||||
}
|
||||
|
||||
#' @importFrom dplyr %>% filter pull
|
||||
find_ab_group <- function(ab_class) {
|
||||
ifelse(ab_class %in% c("aminoglycoside",
|
||||
"carbapenem",
|
||||
"cephalosporin",
|
||||
"fluoroquinolone",
|
||||
"glycopeptide",
|
||||
"macrolide",
|
||||
"tetracycline"),
|
||||
paste0(ab_class, "s"),
|
||||
AMR::antibiotics %>%
|
||||
filter(ab %in% ab_class_vars(ab_class)) %>%
|
||||
pull(group) %>%
|
||||
unique() %>%
|
||||
tolower() %>%
|
||||
paste(collapse = "/")
|
||||
)
|
||||
}
|
||||
@@ -1,540 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Determine first (weighted) isolates
|
||||
#'
|
||||
#' Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type.
|
||||
#' @param x a \code{data.frame} containing isolates.
|
||||
#' @param col_date column name of the result date (or date that is was received on the lab), defaults to the first column of 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 \code{\link{as.mo}}), defaults to the first column of class \code{mo}. Values will be coerced using \code{\link{as.mo}}.
|
||||
#' @param col_testcode column name of the test codes. Use \code{col_testcode = NULL} to \strong{not} exclude certain test codes (like test codes for screening). In that case \code{testcodes_exclude} will be ignored.
|
||||
#' @param col_specimen column name of the specimen type or group
|
||||
#' @param col_icu column name of the logicals (\code{TRUE}/\code{FALSE}) whether a ward or department is an Intensive Care Unit (ICU)
|
||||
#' @param col_keyantibiotics column name of the key antibiotics to determine first \emph{weighted} isolates, see \code{\link{key_antibiotics}}. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use \code{col_keyantibiotics = FALSE} to prevent this.
|
||||
#' @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 character vector with test codes that should be excluded (case-insensitive)
|
||||
#' @param icu_exclude logical whether ICU isolates should be excluded (rows with value \code{TRUE} in column \code{col_icu})
|
||||
#' @param specimen_group value in column \code{col_specimen} to filter on
|
||||
#' @param type type to determine weighed isolates; can be \code{"keyantibiotics"} or \code{"points"}, see Details
|
||||
#' @param ignore_I logical to determine whether antibiotic interpretations with \code{"I"} will be ignored when \code{type = "keyantibiotics"}, see Details
|
||||
#' @param points_threshold points until the comparison of key antibiotics will lead to inclusion of an isolate when \code{type = "points"}, see Details
|
||||
#' @param info print progress
|
||||
#' @param include_unknown logical to determine whether 'unknown' microorganisms should be included too, i.e. microbial code \code{"UNKNOWN"}, which defaults to \code{FALSE}. For WHONET users, this means that all records with organism code \code{"con"} (\emph{contamination}) will be excluded at default. Isolates with a microbial ID of \code{NA} will always be excluded as first isolate.
|
||||
#' @param ... parameters passed on to the \code{first_isolate} function
|
||||
#' @details \strong{WHY THIS IS SO IMPORTANT} \cr
|
||||
#' To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode \href{https://www.ncbi.nlm.nih.gov/pubmed/17304462}{[1]}. If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all \emph{S. aureus} isolates would be overestimated, because you included this MRSA more than once. It would be \href{https://en.wikipedia.org/wiki/Selection_bias}{selection bias}.
|
||||
#'
|
||||
#' All isolates with a microbial ID of \code{NA} will be excluded as first isolate.
|
||||
#'
|
||||
#' The functions \code{filter_first_isolate} and \code{filter_first_weighted_isolate} are helper functions to quickly filter on first isolates. The function \code{filter_first_isolate} is essentially equal to:
|
||||
#' \preformatted{
|
||||
#' x \%>\%
|
||||
#' mutate(only_firsts = first_isolate(x, ...)) \%>\%
|
||||
#' filter(only_firsts == TRUE) \%>\%
|
||||
#' select(-only_firsts)
|
||||
#' }
|
||||
#' The function \code{filter_first_weighted_isolate} is essentially equal to:
|
||||
#' \preformatted{
|
||||
#' x \%>\%
|
||||
#' mutate(keyab = key_antibiotics(.)) \%>\%
|
||||
#' mutate(only_weighted_firsts = first_isolate(x,
|
||||
#' col_keyantibiotics = "keyab", ...)) \%>\%
|
||||
#' filter(only_weighted_firsts == TRUE) \%>\%
|
||||
#' select(-only_weighted_firsts)
|
||||
#' }
|
||||
#' @section Key antibiotics:
|
||||
#' There are two ways to determine whether isolates can be included as first \emph{weighted} isolates which will give generally the same results: \cr
|
||||
#'
|
||||
#' \strong{1. Using} \code{type = "keyantibiotics"} \strong{and parameter} \code{ignore_I} \cr
|
||||
#' Any difference from S to R (or vice versa) will (re)select an isolate as a first weighted isolate. With \code{ignore_I = FALSE}, also differences from I to S|R (or vice versa) will lead to this. This is a reliable method and 30-35 times faster than method 2. Read more about this in the \code{\link{key_antibiotics}} function. \cr
|
||||
#'
|
||||
#' \strong{2. Using} \code{type = "points"} \strong{and parameter} \code{points_threshold} \cr
|
||||
#' A difference from I to S|R (or vice versa) means 0.5 points, a difference from S to R (or vice versa) means 1 point. When the sum of points exceeds \code{points_threshold}, which default to \code{2}, an isolate will be (re)selected as a first weighted isolate.
|
||||
#' @rdname first_isolate
|
||||
#' @keywords isolate isolates first
|
||||
#' @seealso \code{\link{key_antibiotics}}
|
||||
#' @export
|
||||
#' @importFrom dplyr arrange_at lag between row_number filter mutate arrange pull ungroup
|
||||
#' @importFrom crayon blue bold silver
|
||||
# @importFrom clean percentage
|
||||
#' @return Logical vector
|
||||
#' @source Methodology of this function is based on: \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' # `example_isolates` is a dataset available in the AMR package.
|
||||
#' # See ?example_isolates.
|
||||
#'
|
||||
#' library(dplyr)
|
||||
#' # Filter on first isolates:
|
||||
#' example_isolates %>%
|
||||
#' mutate(first_isolate = first_isolate(.,
|
||||
#' col_date = "date",
|
||||
#' col_patient_id = "patient_id",
|
||||
#' col_mo = "mo")) %>%
|
||||
#' filter(first_isolate == TRUE)
|
||||
#'
|
||||
#' # Which can be shortened to:
|
||||
#' example_isolates %>%
|
||||
#' filter_first_isolate()
|
||||
#' # or for first weighted isolates:
|
||||
#' example_isolates %>%
|
||||
#' filter_first_weighted_isolate()
|
||||
#'
|
||||
#' # Now let's see if first isolates matter:
|
||||
#' A <- example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(count = n_rsi(GEN), # gentamicin availability
|
||||
#' resistance = portion_IR(GEN)) # gentamicin resistance
|
||||
#'
|
||||
#' B <- example_isolates %>%
|
||||
#' filter_first_weighted_isolate() %>% # the 1st isolate filter
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(count = n_rsi(GEN), # gentamicin availability
|
||||
#' resistance = portion_IR(GEN)) # gentamicin resistance
|
||||
#'
|
||||
#' # Have a look at A and B.
|
||||
#' # B is more reliable because every isolate is only counted once.
|
||||
#' # Gentamicin resitance in hospital D appears to be 3.1% higher than
|
||||
#' # when you (erroneously) would have used all isolates for analysis.
|
||||
#'
|
||||
#'
|
||||
#' ## OTHER EXAMPLES:
|
||||
#'
|
||||
#' \dontrun{
|
||||
#'
|
||||
#' # set key antibiotics to a new variable
|
||||
#' x$keyab <- key_antibiotics(x)
|
||||
#'
|
||||
#' x$first_isolate <- first_isolate(x)
|
||||
#'
|
||||
#' x$first_isolate_weighed <- first_isolate(x, col_keyantibiotics = 'keyab')
|
||||
#'
|
||||
#' x$first_blood_isolate <- first_isolate(x, specimen_group = "Blood")
|
||||
#' }
|
||||
first_isolate <- function(x,
|
||||
col_date = NULL,
|
||||
col_patient_id = NULL,
|
||||
col_mo = NULL,
|
||||
col_testcode = NULL,
|
||||
col_specimen = NULL,
|
||||
col_icu = NULL,
|
||||
col_keyantibiotics = NULL,
|
||||
episode_days = 365,
|
||||
testcodes_exclude = NULL,
|
||||
icu_exclude = FALSE,
|
||||
specimen_group = NULL,
|
||||
type = "keyantibiotics",
|
||||
ignore_I = TRUE,
|
||||
points_threshold = 2,
|
||||
info = TRUE,
|
||||
include_unknown = FALSE,
|
||||
...) {
|
||||
|
||||
if (!is.data.frame(x)) {
|
||||
stop("`x` must be a data.frame.", call. = FALSE)
|
||||
}
|
||||
|
||||
dots <- unlist(list(...))
|
||||
if (length(dots) != 0) {
|
||||
# backwards compatibility with old parameters
|
||||
dots.names <- dots %>% names()
|
||||
if ("filter_specimen" %in% dots.names) {
|
||||
specimen_group <- dots[which(dots.names == "filter_specimen")]
|
||||
}
|
||||
if ("tbl" %in% dots.names) {
|
||||
x <- dots[which(dots.names == "tbl")]
|
||||
}
|
||||
}
|
||||
|
||||
# try to find columns based on type
|
||||
# -- mo
|
||||
if (is.null(col_mo)) {
|
||||
col_mo <- search_type_in_df(x = x, type = "mo")
|
||||
}
|
||||
if (is.null(col_mo)) {
|
||||
stop("`col_mo` must be set.", call. = FALSE)
|
||||
}
|
||||
|
||||
# -- date
|
||||
if (is.null(col_date)) {
|
||||
col_date <- search_type_in_df(x = x, type = "date")
|
||||
}
|
||||
if (is.null(col_date)) {
|
||||
stop("`col_date` must be set.", call. = FALSE)
|
||||
}
|
||||
# convert to Date (pipes/pull for supporting tibbles too)
|
||||
dates <- x %>% pull(col_date) %>% as.Date()
|
||||
dates[is.na(dates)] <- as.Date("1970-01-01")
|
||||
x[, col_date] <- dates
|
||||
|
||||
# -- patient id
|
||||
if (is.null(col_patient_id)) {
|
||||
if (all(c("First name", "Last name", "Sex") %in% colnames(x))) {
|
||||
# WHONET support
|
||||
x <- x %>% mutate(patient_id = paste(`First name`, `Last name`, Sex))
|
||||
col_patient_id <- "patient_id"
|
||||
message(blue(paste0("NOTE: Using combined columns `", bold("First name"), "`, `", bold("Last name"), "` and `", bold("Sex"), "` as input for `col_patient_id`")))
|
||||
} else {
|
||||
col_patient_id <- search_type_in_df(x = x, type = "patient_id")
|
||||
}
|
||||
}
|
||||
if (is.null(col_patient_id)) {
|
||||
stop("`col_patient_id` must be set.", call. = FALSE)
|
||||
}
|
||||
|
||||
# -- key antibiotics
|
||||
if (is.null(col_keyantibiotics)) {
|
||||
col_keyantibiotics <- search_type_in_df(x = x, type = "keyantibiotics")
|
||||
}
|
||||
if (isFALSE(col_keyantibiotics)) {
|
||||
col_keyantibiotics <- NULL
|
||||
}
|
||||
|
||||
# -- specimen
|
||||
if (is.null(col_specimen) & !is.null(specimen_group)) {
|
||||
col_specimen <- search_type_in_df(x = x, type = "specimen")
|
||||
}
|
||||
if (isFALSE(col_specimen)) {
|
||||
col_specimen <- NULL
|
||||
}
|
||||
|
||||
# check if columns exist
|
||||
check_columns_existance <- function(column, tblname = x) {
|
||||
if (NROW(tblname) <= 1 | NCOL(tblname) <= 1) {
|
||||
stop("Please check tbl for existance.")
|
||||
}
|
||||
|
||||
if (!is.null(column)) {
|
||||
if (!(column %in% colnames(tblname))) {
|
||||
stop("Column `", column, "` not found.")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
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_keyantibiotics)
|
||||
|
||||
# create new dataframe with original row index
|
||||
x <- x %>%
|
||||
mutate(newvar_row_index = seq_len(nrow(x)),
|
||||
newvar_mo = x %>% pull(col_mo) %>% as.mo(),
|
||||
newvar_genus_species = paste(mo_genus(newvar_mo), mo_species(newvar_mo)),
|
||||
newvar_date = x %>% pull(col_date),
|
||||
newvar_patient_id = x %>% pull(col_patient_id))
|
||||
|
||||
if (is.null(col_testcode)) {
|
||||
testcodes_exclude <- NULL
|
||||
}
|
||||
# remove testcodes
|
||||
if (!is.null(testcodes_exclude) & info == TRUE) {
|
||||
message(blue(paste0("[Criterion] Excluded test codes: ", toString(testcodes_exclude))))
|
||||
}
|
||||
|
||||
if (is.null(col_icu)) {
|
||||
icu_exclude <- FALSE
|
||||
} else {
|
||||
x <- x %>%
|
||||
mutate(col_icu = x %>% pull(col_icu) %>% as.logical())
|
||||
}
|
||||
|
||||
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(blue(paste0("[Criterion] Excluded other than specimen group '", specimen_group, "'")))
|
||||
}
|
||||
}
|
||||
if (!is.null(col_keyantibiotics)) {
|
||||
x <- x %>% mutate(key_ab = x %>% pull(col_keyantibiotics))
|
||||
}
|
||||
|
||||
if (is.null(testcodes_exclude)) {
|
||||
testcodes_exclude <- ""
|
||||
}
|
||||
|
||||
# arrange data to the right sorting
|
||||
if (is.null(specimen_group)) {
|
||||
# not filtering on specimen
|
||||
if (icu_exclude == FALSE) {
|
||||
if (info == TRUE & !is.null(col_icu)) {
|
||||
message(blue("[Criterion] Included isolates from ICU"))
|
||||
}
|
||||
x <- x %>%
|
||||
arrange(newvar_patient_id,
|
||||
newvar_genus_species,
|
||||
newvar_date)
|
||||
row.start <- 1
|
||||
row.end <- nrow(x)
|
||||
} else {
|
||||
if (info == TRUE) {
|
||||
message(blue("[Criterion] Excluded isolates from ICU"))
|
||||
}
|
||||
x <- x %>%
|
||||
arrange_at(c(col_icu,
|
||||
"newvar_patient_id",
|
||||
"newvar_genus_species",
|
||||
"newvar_date"))
|
||||
|
||||
suppressWarnings(
|
||||
row.start <- which(x %>% pull(col_icu) == FALSE) %>% min(na.rm = TRUE)
|
||||
)
|
||||
suppressWarnings(
|
||||
row.end <- which(x %>% pull(col_icu) == FALSE) %>% max(na.rm = TRUE)
|
||||
)
|
||||
}
|
||||
|
||||
} else {
|
||||
# filtering on specimen and only analyse these row to save time
|
||||
if (icu_exclude == FALSE) {
|
||||
if (info == TRUE & !is.null(col_icu)) {
|
||||
message(blue("[Criterion] Included isolates from ICU.\n"))
|
||||
}
|
||||
x <- x %>%
|
||||
arrange_at(c(col_specimen,
|
||||
"newvar_patient_id",
|
||||
"newvar_genus_species",
|
||||
"newvar_date"))
|
||||
suppressWarnings(
|
||||
row.start <- which(x %>% pull(col_specimen) == specimen_group) %>% min(na.rm = TRUE)
|
||||
)
|
||||
suppressWarnings(
|
||||
row.end <- which(x %>% pull(col_specimen) == specimen_group) %>% max(na.rm = TRUE)
|
||||
)
|
||||
} else {
|
||||
if (info == TRUE) {
|
||||
message(blue("[Criterion] Excluded isolates from ICU"))
|
||||
}
|
||||
x <- x %>%
|
||||
arrange_at(c(col_icu,
|
||||
col_specimen,
|
||||
"newvar_patient_id",
|
||||
"newvar_genus_species",
|
||||
"newvar_date"))
|
||||
suppressWarnings(
|
||||
row.start <- min(which(x %>% pull(col_specimen) == specimen_group
|
||||
& x %>% pull(col_icu) == FALSE),
|
||||
na.rm = TRUE)
|
||||
)
|
||||
suppressWarnings(
|
||||
row.end <- max(which(x %>% pull(col_specimen) == specimen_group &
|
||||
x %>% pull(col_icu) == FALSE),
|
||||
na.rm = TRUE)
|
||||
)
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
# no isolates found
|
||||
if (abs(row.start) == Inf | abs(row.end) == Inf) {
|
||||
if (info == TRUE) {
|
||||
message(paste("=> Found", bold("no isolates")))
|
||||
}
|
||||
return(rep(FALSE, nrow(x)))
|
||||
}
|
||||
|
||||
# did find some isolates - add new index numbers of rows
|
||||
x <- x %>% mutate(newvar_row_index_sorted = seq_len(nrow(.)))
|
||||
|
||||
scope.size <- row.end - row.start + 1
|
||||
|
||||
identify_new_year <- function(x, episode_days) {
|
||||
# I asked on StackOverflow:
|
||||
# https://stackoverflow.com/questions/42122245/filter-one-row-every-year
|
||||
if (length(x) == 1) {
|
||||
return(TRUE)
|
||||
}
|
||||
indices <- integer(0)
|
||||
start <- x[1]
|
||||
ind <- 1
|
||||
indices[ind] <- ind
|
||||
for (i in 2:length(x)) {
|
||||
if (isTRUE(as.numeric(x[i] - start) >= episode_days)) {
|
||||
ind <- ind + 1
|
||||
indices[ind] <- i
|
||||
start <- x[i]
|
||||
}
|
||||
}
|
||||
result <- rep(FALSE, length(x))
|
||||
result[indices] <- TRUE
|
||||
return(result)
|
||||
}
|
||||
|
||||
# Analysis of first isolate ----
|
||||
all_first <- x %>%
|
||||
mutate(other_pat_or_mo = if_else(newvar_patient_id == lag(newvar_patient_id)
|
||||
& newvar_genus_species == lag(newvar_genus_species),
|
||||
FALSE,
|
||||
TRUE)) %>%
|
||||
group_by(newvar_patient_id,
|
||||
newvar_genus_species) %>%
|
||||
mutate(more_than_episode_ago = identify_new_year(x = newvar_date,
|
||||
episode_days = episode_days)) %>%
|
||||
ungroup()
|
||||
|
||||
weighted.notice <- ""
|
||||
if (!is.null(col_keyantibiotics)) {
|
||||
weighted.notice <- "weighted "
|
||||
if (info == TRUE) {
|
||||
if (type == "keyantibiotics") {
|
||||
message(blue(paste0("[Criterion] Inclusion based on key antibiotics, ",
|
||||
ifelse(ignore_I == FALSE, "not ", ""),
|
||||
"ignoring I")))
|
||||
}
|
||||
if (type == "points") {
|
||||
message(blue(paste0("[Criterion] Inclusion based on key antibiotics, using points threshold of "
|
||||
, points_threshold)))
|
||||
}
|
||||
}
|
||||
type_param <- type
|
||||
|
||||
all_first <- all_first %>%
|
||||
mutate(key_ab_lag = lag(key_ab)) %>%
|
||||
mutate(key_ab_other = !key_antibiotics_equal(y = key_ab,
|
||||
z = key_ab_lag,
|
||||
type = type_param,
|
||||
ignore_I = ignore_I,
|
||||
points_threshold = points_threshold,
|
||||
info = info)) %>%
|
||||
mutate(
|
||||
real_first_isolate =
|
||||
if_else(
|
||||
newvar_row_index_sorted %>% between(row.start, row.end)
|
||||
& newvar_genus_species != ""
|
||||
& (other_pat_or_mo | more_than_episode_ago | key_ab_other),
|
||||
TRUE,
|
||||
FALSE))
|
||||
|
||||
} else {
|
||||
# no key antibiotics
|
||||
all_first <- all_first %>%
|
||||
mutate(
|
||||
real_first_isolate =
|
||||
if_else(
|
||||
newvar_row_index_sorted %>% between(row.start, row.end)
|
||||
& newvar_genus_species != ""
|
||||
& (other_pat_or_mo | more_than_episode_ago),
|
||||
TRUE,
|
||||
FALSE))
|
||||
|
||||
}
|
||||
|
||||
# first one as TRUE
|
||||
all_first[row.start, "real_first_isolate"] <- TRUE
|
||||
# no tests that should be included, or ICU
|
||||
if (!is.null(col_testcode)) {
|
||||
all_first[which(all_first[, col_testcode] %in% tolower(testcodes_exclude)), "real_first_isolate"] <- FALSE
|
||||
}
|
||||
if (icu_exclude == TRUE) {
|
||||
all_first[which(all_first[, col_icu] == TRUE), "real_first_isolate"] <- FALSE
|
||||
}
|
||||
|
||||
decimal.mark <- getOption("OutDec")
|
||||
big.mark <- ifelse(decimal.mark != ",", ",", ".")
|
||||
|
||||
# handle empty microorganisms
|
||||
if (any(all_first$newvar_mo == "UNKNOWN", na.rm = TRUE) & info == TRUE) {
|
||||
message(blue(paste0("NOTE: ", ifelse(include_unknown == TRUE, "Included ", "Excluded "),
|
||||
format(sum(all_first$newvar_mo == "UNKNOWN"),
|
||||
decimal.mark = decimal.mark, big.mark = big.mark),
|
||||
" isolates with a microbial ID 'UNKNOWN' (column `", bold(col_mo), "`)")))
|
||||
}
|
||||
all_first[which(all_first$newvar_mo == "UNKNOWN"), "real_first_isolate"] <- include_unknown
|
||||
|
||||
# exclude all NAs
|
||||
if (any(is.na(all_first$newvar_mo)) & info == TRUE) {
|
||||
message(blue(paste0("NOTE: Excluded ", format(sum(is.na(all_first$newvar_mo)),
|
||||
decimal.mark = decimal.mark, big.mark = big.mark),
|
||||
" isolates with a microbial ID 'NA' (column `", bold(col_mo), "`)")))
|
||||
}
|
||||
all_first[which(is.na(all_first$newvar_mo)), "real_first_isolate"] <- FALSE
|
||||
|
||||
# arrange back according to original sorting again
|
||||
all_first <- all_first %>%
|
||||
arrange(newvar_row_index) %>%
|
||||
pull(real_first_isolate)
|
||||
|
||||
if (info == TRUE) {
|
||||
n_found <- base::sum(all_first, na.rm = TRUE)
|
||||
p_found_total <- percentage(n_found / nrow(x))
|
||||
p_found_scope <- percentage(n_found / scope.size)
|
||||
# mark up number of found
|
||||
n_found <- base::format(n_found, big.mark = big.mark, decimal.mark = decimal.mark)
|
||||
if (p_found_total != p_found_scope) {
|
||||
msg_txt <- paste0("=> Found ",
|
||||
bold(paste0(n_found, " first ", weighted.notice, "isolates")),
|
||||
" (", p_found_scope, " within scope and ", p_found_total, " of total)")
|
||||
} else {
|
||||
msg_txt <- paste0("=> Found ",
|
||||
bold(paste0(n_found, " first ", weighted.notice, "isolates")),
|
||||
" (", p_found_total, " of total)")
|
||||
}
|
||||
base::message(msg_txt)
|
||||
}
|
||||
|
||||
all_first
|
||||
|
||||
}
|
||||
|
||||
#' @rdname first_isolate
|
||||
#' @importFrom dplyr filter
|
||||
#' @export
|
||||
filter_first_isolate <- function(x,
|
||||
col_date = NULL,
|
||||
col_patient_id = NULL,
|
||||
col_mo = NULL,
|
||||
...) {
|
||||
filter(x, first_isolate(x = x,
|
||||
col_date = col_date,
|
||||
col_patient_id = col_patient_id,
|
||||
col_mo = col_mo,
|
||||
...))
|
||||
}
|
||||
|
||||
#' @rdname first_isolate
|
||||
#' @importFrom dplyr %>% mutate filter
|
||||
#' @export
|
||||
filter_first_weighted_isolate <- function(x,
|
||||
col_date = NULL,
|
||||
col_patient_id = NULL,
|
||||
col_mo = NULL,
|
||||
col_keyantibiotics = NULL,
|
||||
...) {
|
||||
tbl_keyab <- x %>%
|
||||
mutate(keyab = suppressMessages(key_antibiotics(.,
|
||||
col_mo = col_mo,
|
||||
...))) %>%
|
||||
mutate(firsts = first_isolate(.,
|
||||
col_date = col_date,
|
||||
col_patient_id = col_patient_id,
|
||||
col_mo = col_mo,
|
||||
col_keyantibiotics = "keyab",
|
||||
...))
|
||||
x[which(tbl_keyab$firsts == TRUE), ]
|
||||
}
|
||||
@@ -1,72 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' @importFrom clean freq
|
||||
#' @export
|
||||
clean::freq
|
||||
|
||||
#' @exportMethod freq.mo
|
||||
#' @importFrom dplyr n_distinct
|
||||
#' @importFrom clean freq.default
|
||||
# @importFrom clean percentage
|
||||
#' @export
|
||||
#' @noRd
|
||||
freq.mo <- function(x, ...) {
|
||||
x_noNA <- as.mo(x[!is.na(x)]) # as.mo() to get the newest mo codes
|
||||
grams <- mo_gramstain(x_noNA, language = NULL)
|
||||
digits <- list(...)$digits
|
||||
if (is.null(digits)) {
|
||||
digits <- 2
|
||||
}
|
||||
freq.default(x = x, ...,
|
||||
.add_header = list(`Gram-negative` = paste0(format(sum(grams == "Gram-negative", na.rm = TRUE),
|
||||
big.mark = ",",
|
||||
decimal.mark = "."),
|
||||
" (", percentage(sum(grams == "Gram-negative", na.rm = TRUE) / length(grams), digits = digits),
|
||||
")"),
|
||||
`Gram-positive` = paste0(format(sum(grams == "Gram-positive", na.rm = TRUE),
|
||||
big.mark = ",",
|
||||
decimal.mark = "."),
|
||||
" (", percentage(sum(grams == "Gram-positive", na.rm = TRUE) / length(grams), digits = digits),
|
||||
")"),
|
||||
`Nr of genera` = n_distinct(mo_genus(x_noNA, language = NULL)),
|
||||
`Nr of species` = n_distinct(paste(mo_genus(x_noNA, language = NULL),
|
||||
mo_species(x_noNA, language = NULL)))))
|
||||
}
|
||||
|
||||
#' @exportMethod freq.rsi
|
||||
#' @importFrom clean freq.default
|
||||
#' @export
|
||||
#' @noRd
|
||||
freq.rsi <- function(x, ...) {
|
||||
x_name <- deparse(substitute(x))
|
||||
x_name <- gsub(".*[$]", "", x_name)
|
||||
ab <- suppressMessages(suppressWarnings(AMR::as.ab(x_name)))
|
||||
if (!is.na(ab)) {
|
||||
freq.default(x = x, ...,
|
||||
.add_header = list(Drug = paste0(ab_name(ab), " (", ab, ", ", ab_atc(ab), ")"),
|
||||
group = ab_group(ab),
|
||||
`%SI` = AMR::portion_SI(x, minimum = 0, as_percent = TRUE)))
|
||||
} else {
|
||||
freq.default(x = x, ...,
|
||||
.add_header = list(`%SI` = AMR::portion_SI(x, minimum = 0, as_percent = TRUE)))
|
||||
}
|
||||
}
|
||||
-203
@@ -1,203 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' \emph{G}-test for Count Data
|
||||
#'
|
||||
#' \code{g.test} performs chi-squared contingency table tests and goodness-of-fit tests, just like \code{\link{chisq.test}} but is more reliable [1]. A \emph{G}-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a \strong{\emph{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 \strong{\emph{G}-test of independence}).
|
||||
#' @inherit stats::chisq.test params return
|
||||
#' @details If \code{x} is a matrix with one row or column, or if \code{x} is a vector and \code{y} is not given, then a \emph{goodness-of-fit test} is performed (\code{x} is treated as a one-dimensional contingency table). The entries of \code{x} must be non-negative integers. In this case, the hypothesis tested is whether the population probabilities equal those in \code{p}, or are all equal if \code{p} is not given.
|
||||
#'
|
||||
#' If \code{x} is a matrix with at least two rows and columns, it is taken as a two-dimensional contingency table: the entries of \code{x} must be non-negative integers. Otherwise, \code{x} and \code{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 (like the \emph{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 \code{p}, each sample being of size \code{n = sum(x)}. This simulation is done in \R and may be slow.
|
||||
#' @section \emph{G}-test of goodness-of-fit (likelihood ratio test):
|
||||
#' Use the \emph{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 \emph{G}-test may give inaccurate results, and you should use an exact test instead (\code{\link{fisher.test}}).
|
||||
#'
|
||||
#' The \emph{G}-test of goodness-of-fit is an alternative to the chi-square test of goodness-of-fit (\code{\link{chisq.test}}); each of these tests has some advantages and some disadvantages, and the results of the two tests are usually very similar.
|
||||
#'
|
||||
#' @section \emph{G}-test of independence:
|
||||
#' Use the \emph{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 \emph{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 (\code{\link{fisher.test}}) is an \strong{exact} test, where the \emph{G}-test is still only an \strong{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 \emph{G}-test of independence is an alternative to the chi-square test of independence (\code{\link{chisq.test}}), and they will give approximately the same results.
|
||||
#' @section How the test works:
|
||||
#' Unlike the exact test of goodness-of-fit (\code{\link{fisher.test}}), the \emph{G}-test does not directly calculate the probability of obtaining the observed results or something more extreme. Instead, like almost all statistical tests, the \emph{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 \emph{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 \emph{G}-statistic is:
|
||||
#'
|
||||
#' \code{G <- 2 * sum(x * log(x / E))}
|
||||
#'
|
||||
#' where \code{E} are the expected values. Since this is chi-square distributed, the p value can be calculated with:
|
||||
#'
|
||||
#' \code{p <- stats::pchisq(G, df, lower.tail = FALSE)}
|
||||
#'
|
||||
#' where \code{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 \emph{G}-tests for each category, of course.
|
||||
#' @keywords chi
|
||||
#' @seealso \code{\link{chisq.test}}
|
||||
#' @references [1] McDonald, J.H. 2014. \strong{Handbook of Biological Statistics (3rd ed.)}. Sparky House Publishing, Baltimore, Maryland. \url{http://www.biostathandbook.com/gtestgof.html}.
|
||||
#' @source This code is almost identical to \code{\link{chisq.test}}, except that:
|
||||
#' \itemize{
|
||||
#' \item{The calculation of the statistic was changed to \code{2 * sum(x * log(x / E))}}
|
||||
#' \item{Yates' continuity correction was removed as it does not apply to a \emph{G}-test}
|
||||
#' \item{The possibility to simulate p values with \code{simulate.p.value} was removed}
|
||||
#' }
|
||||
#' @export
|
||||
#' @importFrom stats pchisq complete.cases
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @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 <- g.test(x, p = c(1, 2, 1) / 4)
|
||||
#' # G$p.value = 0.12574.
|
||||
#'
|
||||
#' # 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)
|
||||
#' # p = 0.01787343
|
||||
#'
|
||||
#' # 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) || anyNA(x))
|
||||
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, parameter = 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")
|
||||
}
|
||||
-424
@@ -1,424 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' AMR plots with \code{ggplot2}
|
||||
#'
|
||||
#' Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal \code{\link[ggplot2]{ggplot}2} functions.
|
||||
#' @param data a \code{data.frame} with column(s) of class \code{"rsi"} (see \code{\link{as.rsi}})
|
||||
#' @param position position adjustment of bars, either \code{"fill"} (default when \code{fun} is \code{\link{count_df}}), \code{"stack"} (default when \code{fun} is \code{\link{portion_df}}) or \code{"dodge"}
|
||||
#' @param x variable to show on x axis, either \code{"antibiotic"} (default) or \code{"interpretation"} or a grouping variable
|
||||
#' @param fill variable to categorise using the plots legend, either \code{"antibiotic"} (default) or \code{"interpretation"} or a grouping variable
|
||||
#' @param breaks numeric vector of positions
|
||||
#' @param limits numeric vector of length two providing limits of the scale, use \code{NA} to refer to the existing minimum or maximum
|
||||
#' @param facet variable to split plots by, either \code{"interpretation"} (default) or \code{"antibiotic"} or a grouping variable
|
||||
#' @inheritParams portion
|
||||
#' @param nrow (when using \code{facet}) number of rows
|
||||
#' @param colours a named vector with colours for the bars. The names must be one or more of: S, SI, I, IR, R or be \code{FALSE} to use default \code{ggplot2} colours.
|
||||
#' @param datalabels show datalabels using \code{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 parameters passed on to \code{geom_rsi}
|
||||
#' @details At default, the names of antibiotics will be shown on the plots using \code{\link{ab_name}}. This can be set with the \code{translate_ab} parameter. See \code{\link{count_df}}.
|
||||
#'
|
||||
#' \strong{The functions}\cr
|
||||
#' \code{geom_rsi} will take any variable from the data that has an \code{rsi} class (created with \code{\link{as.rsi}}) using \code{\link{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.
|
||||
#'
|
||||
#' \code{facet_rsi} creates 2d plots (at default based on S/I/R) using \code{\link[ggplot2]{facet_wrap}}.
|
||||
#'
|
||||
#' \code{scale_y_percent} transforms the y axis to a 0 to 100\% range using \code{\link[ggplot2]{scale_continuous}}.
|
||||
#'
|
||||
#' \code{scale_rsi_colours} sets colours to the bars: pastel blue for S, pastel turquoise for I and pastel red for R, using \code{\link[ggplot2]{scale_brewer}}.
|
||||
#'
|
||||
#' \code{theme_rsi} is a \code{ggplot \link[ggplot2]{theme}} with minimal distraction.
|
||||
#'
|
||||
#' \code{labels_rsi_count} print datalabels on the bars with percentage and amount of isolates using \code{\link[ggplot2]{geom_text}}
|
||||
#'
|
||||
#' \code{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 (\code{\%>\%}). See Examples.
|
||||
#' @rdname ggplot_rsi
|
||||
#' @export
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' library(dplyr)
|
||||
#' library(ggplot2)
|
||||
#'
|
||||
#' # 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 portions and no counts:
|
||||
#' example_isolates %>%
|
||||
#' select(AMX, NIT, FOS, TMP, CIP) %>%
|
||||
#' ggplot_rsi(datalabels = FALSE)
|
||||
#'
|
||||
#' # add other ggplot2 parameters 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)
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' select(AMX) %>%
|
||||
#' ggplot_rsi(colours = c(SI = "yellow"))
|
||||
#'
|
||||
#' # resistance of ciprofloxacine per age group
|
||||
#' example_isolates %>%
|
||||
#' mutate(first_isolate = first_isolate(.)) %>%
|
||||
#' filter(first_isolate == TRUE,
|
||||
#' mo == as.mo("E. coli")) %>%
|
||||
#' # `age_group` is also a function of this package:
|
||||
#' group_by(age_group = age_groups(age)) %>%
|
||||
#' select(age_group,
|
||||
#' CIP) %>%
|
||||
#' ggplot_rsi(x = "age_group")
|
||||
#' \donttest{
|
||||
#'
|
||||
#' # for colourblind mode, use divergent colours from the viridis package:
|
||||
#' example_isolates %>%
|
||||
#' select(AMX, NIT, FOS, TMP, CIP) %>%
|
||||
#' ggplot_rsi() + scale_fill_viridis_d()
|
||||
#' # 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 %>%
|
||||
#' 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)
|
||||
#'
|
||||
#' # genuine analysis: check 3 most prevalent microorganisms
|
||||
#' example_isolates %>%
|
||||
#' # create new bacterial ID's, with all CoNS under the same group (Becker et al.)
|
||||
#' mutate(mo = as.mo(mo, Becker = TRUE)) %>%
|
||||
#' # filter on top three bacterial ID's
|
||||
#' filter(mo %in% top_freq(freq(.$mo), 3)) %>%
|
||||
#' # filter on first isolates
|
||||
#' filter_first_isolate() %>%
|
||||
#' # get short MO names (like "E. coli")
|
||||
#' mutate(bug = mo_shortname(mo, Becker = TRUE)) %>%
|
||||
#' # select this short name and some antiseptic drugs
|
||||
#' select(bug, CXM, GEN, CIP) %>%
|
||||
#' # group by MO
|
||||
#' group_by(bug) %>%
|
||||
#' # plot the thing, putting MOs on the facet
|
||||
#' ggplot_rsi(x = "antibiotic",
|
||||
#' facet = "bug",
|
||||
#' translate_ab = FALSE,
|
||||
#' nrow = 1,
|
||||
#' title = "AMR of Top Three Microorganisms In Blood Culture Isolates",
|
||||
#' subtitle = expression(paste("Only First Isolates, CoNS grouped according to Becker ",
|
||||
#' italic("et al."), " (2014)")),
|
||||
#' x.title = "Antibiotic (EARS-Net code)")
|
||||
#' }
|
||||
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,
|
||||
language = get_locale(),
|
||||
nrow = NULL,
|
||||
colours = c(S = "#61a8ff",
|
||||
SI = "#61a8ff",
|
||||
I = "#61f7ff",
|
||||
IR = "#ff6961",
|
||||
R = "#ff6961"),
|
||||
datalabels = TRUE,
|
||||
datalabels.size = 2.5,
|
||||
datalabels.colour = "gray15",
|
||||
title = NULL,
|
||||
subtitle = NULL,
|
||||
caption = NULL,
|
||||
x.title = "Antimicrobial",
|
||||
y.title = "Proportion",
|
||||
...) {
|
||||
|
||||
stopifnot_installed_package("ggplot2")
|
||||
|
||||
x <- x[1]
|
||||
facet <- facet[1]
|
||||
|
||||
# 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,
|
||||
combine_SI = combine_SI, combine_IR = combine_IR, ...) +
|
||||
theme_rsi()
|
||||
|
||||
if (fill == "interpretation") {
|
||||
# set RSI colours
|
||||
if (isFALSE(colours) & missing(datalabels.colour)) {
|
||||
# set datalabel colour to middle gray
|
||||
datalabels.colour <- "gray50"
|
||||
}
|
||||
p <- p + scale_rsi_colours(colours = colours)
|
||||
}
|
||||
|
||||
if (identical(position, "fill")) {
|
||||
# portions, 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,
|
||||
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",
|
||||
language = get_locale(),
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE,
|
||||
...) {
|
||||
|
||||
stopifnot_installed_package("ggplot2")
|
||||
|
||||
if (is.data.frame(position)) {
|
||||
stop("`position` is invalid. Did you accidentally use '%>%' instead of '+'?", call. = FALSE)
|
||||
}
|
||||
|
||||
y <- "value"
|
||||
if (missing(position) | is.null(position)) {
|
||||
position <- "fill"
|
||||
}
|
||||
|
||||
if (identical(position, "fill")) {
|
||||
position <- ggplot2::position_fill(vjust = 0.5, reverse = TRUE)
|
||||
}
|
||||
|
||||
x <- x[1]
|
||||
|
||||
# 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::layer(geom = "bar", stat = "identity", position = position,
|
||||
mapping = ggplot2::aes_string(x = x, y = y, fill = fill),
|
||||
params = list(...), data = function(x) {
|
||||
AMR::rsi_df(data = x,
|
||||
translate_ab = translate_ab,
|
||||
language = language,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR)
|
||||
})
|
||||
|
||||
}
|
||||
|
||||
#' @rdname ggplot_rsi
|
||||
#' @export
|
||||
facet_rsi <- function(facet = c("interpretation", "antibiotic"), nrow = NULL) {
|
||||
|
||||
stopifnot_installed_package("ggplot2")
|
||||
|
||||
facet <- facet[1]
|
||||
|
||||
# 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
|
||||
# @importFrom clean percentage
|
||||
#' @export
|
||||
scale_y_percent <- function(breaks = seq(0, 1, 0.1), limits = NULL) {
|
||||
stopifnot_installed_package("ggplot2")
|
||||
|
||||
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(colours = c(S = "#61a8ff",
|
||||
SI = "#61a8ff",
|
||||
I = "#61f7ff",
|
||||
IR = "#ff6961",
|
||||
R = "#ff6961")) {
|
||||
stopifnot_installed_package("ggplot2")
|
||||
# previous colour: palette = "RdYlGn"
|
||||
# previous colours: values = c("#b22222", "#ae9c20", "#7cfc00")
|
||||
|
||||
if (!identical(colours, FALSE)) {
|
||||
original_cols <- c(S = "#61a8ff",
|
||||
SI = "#61a8ff",
|
||||
I = "#61f7ff",
|
||||
IR = "#ff6961",
|
||||
R = "#ff6961")
|
||||
colours <- replace(original_cols, names(colours), colours)
|
||||
ggplot2::scale_fill_manual(values = colours)
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname ggplot_rsi
|
||||
#' @export
|
||||
theme_rsi <- function() {
|
||||
stopifnot_installed_package("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
|
||||
#' @importFrom dplyr mutate %>% group_by_at
|
||||
# @importFrom clean percentage
|
||||
#' @export
|
||||
labels_rsi_count <- function(position = NULL,
|
||||
x = "antibiotic",
|
||||
translate_ab = "name",
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE,
|
||||
datalabels.size = 3,
|
||||
datalabels.colour = "gray15") {
|
||||
stopifnot_installed_package("ggplot2")
|
||||
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) {
|
||||
rsi_df(data = x,
|
||||
translate_ab = translate_ab,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR) %>%
|
||||
group_by_at(x_name) %>%
|
||||
mutate(lbl = paste0(percentage(value / sum(value, na.rm = TRUE)),
|
||||
"\n(n=", isolates, ")"))
|
||||
})
|
||||
}
|
||||
-101
@@ -1,101 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
globalVariables(c(".",
|
||||
"..property",
|
||||
"ab",
|
||||
"ab_txt",
|
||||
"abbreviations",
|
||||
"antibiotic",
|
||||
"CNS_CPS",
|
||||
"col_id",
|
||||
"count",
|
||||
"count.x",
|
||||
"date_lab",
|
||||
"diff.percent",
|
||||
"First name",
|
||||
"first_isolate_row_index",
|
||||
"fullname",
|
||||
"fullname_lower",
|
||||
"genus",
|
||||
"gramstain",
|
||||
"group",
|
||||
"index",
|
||||
"input",
|
||||
"interpretation",
|
||||
"isolates",
|
||||
"item",
|
||||
"key_ab",
|
||||
"key_ab_lag",
|
||||
"key_ab_other",
|
||||
"kingdom",
|
||||
"kingdom_index",
|
||||
"lang",
|
||||
"Last name",
|
||||
"lookup",
|
||||
"mdr",
|
||||
"median",
|
||||
"microorganisms",
|
||||
"microorganisms.codes",
|
||||
"missing_names",
|
||||
"mo",
|
||||
"mono_count",
|
||||
"more_than_episode_ago",
|
||||
"name",
|
||||
"new",
|
||||
"newvar_date",
|
||||
"newvar_genus_species",
|
||||
"newvar_mo",
|
||||
"newvar_patient_id",
|
||||
"newvar_row_index",
|
||||
"newvar_row_index_sorted",
|
||||
"observations",
|
||||
"observed",
|
||||
"old",
|
||||
"old_name",
|
||||
"other_pat_or_mo",
|
||||
"package_version",
|
||||
"patient_id",
|
||||
"pattern",
|
||||
"plural",
|
||||
"prevalence",
|
||||
"R",
|
||||
"real_first_isolate",
|
||||
"ref",
|
||||
"rule_group",
|
||||
"rule_name",
|
||||
"S",
|
||||
"se_max",
|
||||
"se_min",
|
||||
"second",
|
||||
"Sex",
|
||||
"species",
|
||||
"species_id",
|
||||
"subspecies",
|
||||
"synonyms",
|
||||
"total",
|
||||
"txt",
|
||||
"uncertainty_level",
|
||||
"value",
|
||||
"x",
|
||||
"xdr",
|
||||
"y",
|
||||
"year"))
|
||||
@@ -1,221 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Guess antibiotic column
|
||||
#'
|
||||
#' This tries to find a column name in a data set based on information from the \code{\link{antibiotics}} data set. Also supports WHONET abbreviations.
|
||||
#' @param x a \code{data.frame}
|
||||
#' @param search_string a text to search \code{x} for, will be checked with \code{\link{as.ab}} if this value is not a column in \code{x}
|
||||
#' @param verbose a logical to indicate whether additional info should be printed
|
||||
#' @details You can look for an antibiotic (trade) name or abbreviation and it will search \code{x} and the \code{\link{antibiotics}} data set for any column containing a name or code of that antibiotic. \strong{Longer columns names take precendence over shorter column names.}
|
||||
#' @importFrom dplyr %>% select filter_all any_vars
|
||||
#' @importFrom crayon blue
|
||||
#' @return A column name of \code{x}, or \code{NULL} when no result is found.
|
||||
#' @export
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @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".
|
||||
#' # [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) {
|
||||
if (is.null(x) & is.null(search_string)) {
|
||||
return(as.name("guess_ab_col"))
|
||||
}
|
||||
if (!is.data.frame(x)) {
|
||||
stop("`x` must be a data.frame")
|
||||
}
|
||||
|
||||
if (length(search_string) > 1) {
|
||||
warning("argument 'search_string' has length > 1 and only the first element will be used")
|
||||
search_string <- search_string[1]
|
||||
}
|
||||
search_string <- as.character(search_string)
|
||||
|
||||
if (search_string %in% colnames(x)) {
|
||||
ab_result <- search_string
|
||||
} else {
|
||||
search_string.ab <- suppressWarnings(as.ab(search_string))
|
||||
if (search_string.ab %in% colnames(x)) {
|
||||
ab_result <- colnames(x)[colnames(x) == search_string.ab][1L]
|
||||
|
||||
} else if (any(tolower(colnames(x)) %in% tolower(unlist(ab_property(search_string.ab, "abbreviations"))))) {
|
||||
ab_result <- colnames(x)[tolower(colnames(x)) %in% tolower(unlist(ab_property(search_string.ab, "abbreviations")))][1L]
|
||||
|
||||
} else {
|
||||
# sort colnames on length - longest first
|
||||
cols <- colnames(x[, x %>% colnames() %>% nchar() %>% order() %>% rev()])
|
||||
df_trans <- data.frame(cols = cols,
|
||||
abs = suppressWarnings(as.ab(cols)),
|
||||
stringsAsFactors = FALSE)
|
||||
ab_result <- df_trans[which(df_trans$abs == search_string.ab), "cols"]
|
||||
ab_result <- ab_result[!is.na(ab_result)][1L]
|
||||
}
|
||||
}
|
||||
|
||||
if (length(ab_result) == 0) {
|
||||
if (verbose == TRUE) {
|
||||
message(paste0("No column found as input for `", search_string,
|
||||
"` (", ab_name(search_string, language = "en", tolower = TRUE), ")."))
|
||||
}
|
||||
return(NULL)
|
||||
} else {
|
||||
if (verbose == TRUE) {
|
||||
message(blue(paste0("NOTE: Using column `", bold(ab_result), "` as input for `", search_string,
|
||||
"` (", ab_name(search_string, language = "en", tolower = TRUE), ").")))
|
||||
}
|
||||
return(ab_result)
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
#' @importFrom crayon blue bold
|
||||
#' @importFrom dplyr %>% mutate arrange pull
|
||||
get_column_abx <- function(x,
|
||||
soft_dependencies = NULL,
|
||||
hard_dependencies = NULL,
|
||||
verbose = FALSE,
|
||||
...) {
|
||||
|
||||
message(blue("NOTE: Auto-guessing columns suitable for analysis..."))
|
||||
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
||||
x_bak <- x
|
||||
# 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 have no more than 50% invalid values
|
||||
vectr_antibiotics <- unique(toupper(unlist(AMR::antibiotics[, c("ab", "atc", "name", "abbreviations", "synonyms")])))
|
||||
vectr_antibiotics <- vectr_antibiotics[!is.na(vectr_antibiotics) & nchar(vectr_antibiotics) >= 3]
|
||||
x_columns <- sapply(colnames(x), function(col, df = x_bak) {
|
||||
if (toupper(col) %in% vectr_antibiotics |
|
||||
is.rsi(as.data.frame(df)[, col]) |
|
||||
is.rsi.eligible(as.data.frame(df)[, col], threshold = 0.5)) {
|
||||
return(col)
|
||||
} else {
|
||||
return(NA_character_)
|
||||
}
|
||||
})
|
||||
x_columns <- x_columns[!is.na(x_columns)]
|
||||
x <- x[, x_columns, drop = FALSE] # without drop = TRUE, x will become a vector when x_columns is length 1
|
||||
|
||||
df_trans <- data.frame(colnames = colnames(x),
|
||||
abcode = suppressWarnings(as.ab(colnames(x))))
|
||||
df_trans <- df_trans[!is.na(df_trans$abcode), ]
|
||||
x <- as.character(df_trans$colnames)
|
||||
names(x) <- df_trans$abcode
|
||||
|
||||
# add from self-defined dots (...):
|
||||
# such as get_column_abx(example_isolates %>% rename(thisone = AMX), amox = "thisone")
|
||||
dots <- list(...)
|
||||
if (length(dots) > 0) {
|
||||
newnames <- suppressWarnings(as.ab(names(dots)))
|
||||
if (any(is.na(newnames))) {
|
||||
warning("Invalid antibiotic reference(s): ", toString(names(dots)[is.na(newnames)]),
|
||||
call. = FALSE, immediate. = TRUE)
|
||||
}
|
||||
# turn all NULLs to NAs
|
||||
dots <- unlist(lapply(dots, function(x) if (is.null(x)) NA else x))
|
||||
names(dots) <- newnames
|
||||
dots <- dots[!is.na(names(dots))]
|
||||
# merge, but overwrite automatically determined ones by 'dots'
|
||||
x <- c(x[!x %in% dots & !names(x) %in% names(dots)], dots)
|
||||
# delete NAs, this will make e.g. eucast_rules(... TMP = NULL) work to prevent TMP from being used
|
||||
x <- x[!is.na(x)]
|
||||
}
|
||||
|
||||
# sort on name
|
||||
x <- x[order(names(x), x)]
|
||||
duplicates <- x[base::duplicated(x)]
|
||||
x <- x[!names(x) %in% names(duplicates)]
|
||||
|
||||
if (verbose == TRUE) {
|
||||
for (i in seq_len(length(x))) {
|
||||
message(blue(paste0("NOTE: Using column `", bold(x[i]), "` as input for `", names(x)[i],
|
||||
"` (", ab_name(names(x)[i], tolower = TRUE), ").")))
|
||||
}
|
||||
} else if (length(duplicates) > 0) {
|
||||
for (i in seq_len(length(duplicates))) {
|
||||
warning(red(paste0("Using column `", bold(duplicates[i]), "` as input for `", names(x[which(x == duplicates[i])]),
|
||||
"` (", ab_name(names(x[names(which(x == duplicates))[i]]), tolower = TRUE),
|
||||
"), although it was matched for multiple antibiotics or columns.")), call. = FALSE)
|
||||
}
|
||||
}
|
||||
|
||||
if (!is.null(hard_dependencies)) {
|
||||
if (!all(hard_dependencies %in% names(x))) {
|
||||
# missing a hard dependency will return NA and consequently the data will not be analysed
|
||||
missing <- hard_dependencies[!hard_dependencies %in% names(x)]
|
||||
generate_warning_abs_missing(missing, any = FALSE)
|
||||
return(NA)
|
||||
}
|
||||
}
|
||||
if (!is.null(soft_dependencies)) {
|
||||
if (!all(soft_dependencies %in% names(x))) {
|
||||
# missing a soft dependency may lower the reliability
|
||||
missing <- soft_dependencies[!soft_dependencies %in% names(x)]
|
||||
missing_txt <- data.frame(missing = missing,
|
||||
missing_names = AMR::ab_name(missing, tolower = TRUE),
|
||||
stringsAsFactors = FALSE) %>%
|
||||
mutate(txt = paste0(bold(missing), " (", missing_names, ")")) %>%
|
||||
arrange(missing_names) %>%
|
||||
pull(txt)
|
||||
message(blue("NOTE: Reliability might be improved if these antimicrobial results would be available too:",
|
||||
paste(missing_txt, collapse = ", ")))
|
||||
}
|
||||
}
|
||||
x
|
||||
}
|
||||
|
||||
generate_warning_abs_missing <- function(missing, any = FALSE) {
|
||||
missing <- paste0(missing, " (", ab_name(missing, tolower = TRUE), ")")
|
||||
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: ",
|
||||
paste(missing, collapse = ", ")),
|
||||
immediate. = TRUE,
|
||||
call. = FALSE)
|
||||
}
|
||||
@@ -1,158 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Join a table with \code{microorganisms}
|
||||
#'
|
||||
#' Join the dataset \code{\link{microorganisms}} easily to an existing table or character vector.
|
||||
#' @rdname join
|
||||
#' @name join
|
||||
#' @aliases join inner_join
|
||||
#' @param x existing table to join, or character vector
|
||||
#' @param by a variable to join by - if left empty will search for a column with class \code{mo} (created with \code{\link{as.mo}}) or will be \code{"mo"} if that column name exists in \code{x}, could otherwise be a column name of \code{x} with values that exist in \code{microorganisms$mo} (like \code{by = "bacteria_id"}), or another column in \code{\link{microorganisms}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})
|
||||
#' @param suffix if there are non-joined duplicate variables in \code{x} and \code{y}, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.
|
||||
#' @param ... other parameters to pass on to \code{dplyr::\link[dplyr]{join}}.
|
||||
#' @details \strong{Note:} As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, characters vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @export
|
||||
#' @examples
|
||||
#' left_join_microorganisms(as.mo("K. pneumoniae"))
|
||||
#' left_join_microorganisms("B_KLBSL_PNE")
|
||||
#'
|
||||
#' library(dplyr)
|
||||
#' example_isolates %>% left_join_microorganisms()
|
||||
#'
|
||||
#' 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", ""), ...) {
|
||||
checked <- joins_check_df(x, by)
|
||||
x <- checked$x
|
||||
by <- checked$by
|
||||
join <- suppressWarnings(
|
||||
dplyr::inner_join(x = x, y = AMR::microorganisms, by = by, suffix = suffix, ...)
|
||||
)
|
||||
if (nrow(join) > nrow(x)) {
|
||||
warning("The newly joined tbl contains ", nrow(join) - nrow(x), " rows more that its original.")
|
||||
}
|
||||
join
|
||||
}
|
||||
|
||||
#' @rdname join
|
||||
#' @export
|
||||
left_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
|
||||
checked <- joins_check_df(x, by)
|
||||
x <- checked$x
|
||||
by <- checked$by
|
||||
join <- suppressWarnings(
|
||||
dplyr::left_join(x = x, y = AMR::microorganisms, by = by, suffix = suffix, ...)
|
||||
)
|
||||
if (nrow(join) > nrow(x)) {
|
||||
warning("The newly joined tbl contains ", nrow(join) - nrow(x), " rows more that its original.")
|
||||
}
|
||||
join
|
||||
}
|
||||
|
||||
#' @rdname join
|
||||
#' @export
|
||||
right_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
|
||||
checked <- joins_check_df(x, by)
|
||||
x <- checked$x
|
||||
by <- checked$by
|
||||
join <- suppressWarnings(
|
||||
dplyr::right_join(x = x, y = AMR::microorganisms, by = by, suffix = suffix, ...)
|
||||
)
|
||||
if (nrow(join) > nrow(x)) {
|
||||
warning("The newly joined tbl contains ", nrow(join) - nrow(x), " rows more that its original.")
|
||||
}
|
||||
join
|
||||
}
|
||||
|
||||
#' @rdname join
|
||||
#' @export
|
||||
full_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
|
||||
checked <- joins_check_df(x, by)
|
||||
x <- checked$x
|
||||
by <- checked$by
|
||||
join <- suppressWarnings(
|
||||
dplyr::full_join(x = x, y = AMR::microorganisms, by = by, suffix = suffix, ...)
|
||||
)
|
||||
if (nrow(join) > nrow(x)) {
|
||||
warning("The newly joined tbl contains ", nrow(join) - nrow(x), " rows more that its original.")
|
||||
}
|
||||
join
|
||||
}
|
||||
|
||||
#' @rdname join
|
||||
#' @export
|
||||
semi_join_microorganisms <- function(x, by = NULL, ...) {
|
||||
checked <- joins_check_df(x, by)
|
||||
x <- checked$x
|
||||
by <- checked$by
|
||||
suppressWarnings(
|
||||
dplyr::semi_join(x = x, y = AMR::microorganisms, by = by, ...)
|
||||
)
|
||||
}
|
||||
|
||||
#' @rdname join
|
||||
#' @export
|
||||
anti_join_microorganisms <- function(x, by = NULL, ...) {
|
||||
checked <- joins_check_df(x, by)
|
||||
x <- checked$x
|
||||
by <- checked$by
|
||||
suppressWarnings(
|
||||
dplyr::anti_join(x = x, y = AMR::microorganisms, by = by, ...)
|
||||
)
|
||||
}
|
||||
|
||||
joins_check_df <- function(x, by) {
|
||||
if (!any(class(x) %in% c("data.frame", "matrix"))) {
|
||||
x <- data.frame(mo = as.character(x), stringsAsFactors = FALSE)
|
||||
if (is.null(by)) {
|
||||
by <- "mo"
|
||||
}
|
||||
}
|
||||
if (is.null(by)) {
|
||||
# search for column with class `mo` and return first one found
|
||||
by <- colnames(x)[lapply(x, is.mo) == TRUE][1]
|
||||
if (is.na(by)) {
|
||||
if ("mo" %in% colnames(x)) {
|
||||
by <- "mo"
|
||||
} else {
|
||||
stop("Cannot join - no column found with name or class `mo`.", call. = FALSE)
|
||||
}
|
||||
}
|
||||
message('Joining, by = "', by, '"') # message same as dplyr::join functions
|
||||
}
|
||||
if (is.null(names(by))) {
|
||||
joinby <- colnames(AMR::microorganisms)[1]
|
||||
names(joinby) <- by
|
||||
} else {
|
||||
joinby <- by
|
||||
}
|
||||
list(x = x,
|
||||
by = joinby)
|
||||
}
|
||||
@@ -1,314 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Key antibiotics for first \emph{weighted} isolates
|
||||
#'
|
||||
#' These function can be used to determine first isolates (see \code{\link{first_isolate}}). Using key antibiotics to determine first isolates is more reliable than without key antibiotics. These selected isolates will then be called first \emph{weighted} isolates.
|
||||
#' @param x table with antibiotics coloms, like \code{AMX} or \code{amox}
|
||||
#' @param y,z characters to compare
|
||||
#' @inheritParams first_isolate
|
||||
#' @param universal_1,universal_2,universal_3,universal_4,universal_5,universal_6 column names of \strong{broad-spectrum} antibiotics, case-insensitive. At default, the columns containing these antibiotics will be guessed with \code{\link{guess_ab_col}}.
|
||||
#' @param GramPos_1,GramPos_2,GramPos_3,GramPos_4,GramPos_5,GramPos_6 column names of antibiotics for \strong{Gram-positives}, case-insensitive. At default, the columns containing these antibiotics will be guessed with \code{\link{guess_ab_col}}.
|
||||
#' @param GramNeg_1,GramNeg_2,GramNeg_3,GramNeg_4,GramNeg_5,GramNeg_6 column names of antibiotics for \strong{Gram-negatives}, case-insensitive. At default, the columns containing these antibiotics will be guessed with \code{\link{guess_ab_col}}.
|
||||
#' @param warnings give warning about missing antibiotic columns, they will anyway be ignored
|
||||
#' @param ... other parameters passed on to function
|
||||
#' @details The function \code{key_antibiotics} returns a character vector with 12 antibiotic results for every isolate. These isolates can then be compared using \code{key_antibiotics_equal}, to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (\code{"."}). The \code{\link{first_isolate}} function only uses this function on the same microbial species from the same patient. Using this, an MRSA will be included after a susceptible \emph{S. aureus} (MSSA) found within the same episode (see \code{episode} parameter of \code{\link{first_isolate}}). Without key antibiotic comparison it would not.
|
||||
#'
|
||||
#' At default, the antibiotics that are used for \strong{Gram-positive bacteria} are: \cr
|
||||
#' amoxicillin, amoxicillin/clavulanic acid, cefuroxime, piperacillin/tazobactam, ciprofloxacin, trimethoprim/sulfamethoxazole (until here is universal), vancomycin, teicoplanin, tetracycline, erythromycin, oxacillin, rifampin.
|
||||
#'
|
||||
#' At default, the antibiotics that are used for \strong{Gram-negative bacteria} are: \cr
|
||||
#' amoxicillin, amoxicillin/clavulanic acid, cefuroxime, piperacillin/tazobactam, ciprofloxacin, trimethoprim/sulfamethoxazole (until here is universal), gentamicin, tobramycin, colistin, cefotaxime, ceftazidime, meropenem.
|
||||
#'
|
||||
#'
|
||||
#' The function \code{key_antibiotics_equal} checks the characters returned by \code{key_antibiotics} for equality, and returns a logical vector.
|
||||
#' @inheritSection first_isolate Key antibiotics
|
||||
#' @rdname key_antibiotics
|
||||
#' @export
|
||||
#' @importFrom dplyr %>% mutate if_else pull
|
||||
#' @importFrom crayon blue bold
|
||||
#' @seealso \code{\link{first_isolate}}
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' # `example_isolates` is a dataset available in the AMR package.
|
||||
#' # See ?example_isolates.
|
||||
#'
|
||||
#' library(dplyr)
|
||||
#' # set key antibiotics to a new variable
|
||||
#' my_patients <- example_isolates %>%
|
||||
#' mutate(keyab = key_antibiotics(.)) %>%
|
||||
#' mutate(
|
||||
#' # now calculate first isolates
|
||||
#' first_regular = first_isolate(., col_keyantibiotics = FALSE),
|
||||
#' # and first WEIGHTED isolates
|
||||
#' first_weighted = first_isolate(., col_keyantibiotics = "keyab")
|
||||
#' )
|
||||
#'
|
||||
#' # Check the difference, in this data set it results in 7% more isolates:
|
||||
#' sum(my_patients$first_regular, na.rm = TRUE)
|
||||
#' sum(my_patients$first_weighted, na.rm = TRUE)
|
||||
#'
|
||||
#'
|
||||
#' # output of the `key_antibiotics` function could be like this:
|
||||
#' strainA <- "SSSRR.S.R..S"
|
||||
#' strainB <- "SSSIRSSSRSSS"
|
||||
#'
|
||||
#' key_antibiotics_equal(strainA, strainB)
|
||||
#' # TRUE, because I is ignored (as well as missing values)
|
||||
#'
|
||||
#' key_antibiotics_equal(strainA, strainB, ignore_I = FALSE)
|
||||
#' # FALSE, because I is not ignored and so the 4th value differs
|
||||
key_antibiotics <- function(x,
|
||||
col_mo = NULL,
|
||||
universal_1 = guess_ab_col(x, "amoxicillin"),
|
||||
universal_2 = guess_ab_col(x, "amoxicillin/clavulanic acid"),
|
||||
universal_3 = guess_ab_col(x, "cefuroxime"),
|
||||
universal_4 = guess_ab_col(x, "piperacillin/tazobactam"),
|
||||
universal_5 = guess_ab_col(x, "ciprofloxacin"),
|
||||
universal_6 = guess_ab_col(x, "trimethoprim/sulfamethoxazole"),
|
||||
GramPos_1 = guess_ab_col(x, "vancomycin"),
|
||||
GramPos_2 = guess_ab_col(x, "teicoplanin"),
|
||||
GramPos_3 = guess_ab_col(x, "tetracycline"),
|
||||
GramPos_4 = guess_ab_col(x, "erythromycin"),
|
||||
GramPos_5 = guess_ab_col(x, "oxacillin"),
|
||||
GramPos_6 = guess_ab_col(x, "rifampin"),
|
||||
GramNeg_1 = guess_ab_col(x, "gentamicin"),
|
||||
GramNeg_2 = guess_ab_col(x, "tobramycin"),
|
||||
GramNeg_3 = guess_ab_col(x, "colistin"),
|
||||
GramNeg_4 = guess_ab_col(x, "cefotaxime"),
|
||||
GramNeg_5 = guess_ab_col(x, "ceftazidime"),
|
||||
GramNeg_6 = guess_ab_col(x, "meropenem"),
|
||||
warnings = TRUE,
|
||||
...) {
|
||||
|
||||
# try to find columns based on type
|
||||
# -- mo
|
||||
if (is.null(col_mo)) {
|
||||
col_mo <- search_type_in_df(x = x, type = "mo")
|
||||
}
|
||||
if (is.null(col_mo)) {
|
||||
stop("`col_mo` must be set.", call. = FALSE)
|
||||
}
|
||||
|
||||
# check columns
|
||||
col.list <- c(universal_1, universal_2, universal_3, universal_4, universal_5, universal_6,
|
||||
GramPos_1, GramPos_2, GramPos_3, GramPos_4, GramPos_5, GramPos_6,
|
||||
GramNeg_1, GramNeg_2, GramNeg_3, GramNeg_4, GramNeg_5, GramNeg_6)
|
||||
check_available_columns <- function(x, col.list, info = TRUE) {
|
||||
# check columns
|
||||
col.list <- col.list[!is.na(col.list) & !is.null(col.list)]
|
||||
names(col.list) <- col.list
|
||||
col.list.bak <- col.list
|
||||
# are they available as upper case or lower case then?
|
||||
for (i in seq_len(length(col.list))) {
|
||||
if (is.null(col.list[i]) | isTRUE(is.na(col.list[i]))) {
|
||||
col.list[i] <- NA
|
||||
} else if (toupper(col.list[i]) %in% colnames(x)) {
|
||||
col.list[i] <- toupper(col.list[i])
|
||||
} else if (tolower(col.list[i]) %in% colnames(x)) {
|
||||
col.list[i] <- tolower(col.list[i])
|
||||
} else if (!col.list[i] %in% colnames(x)) {
|
||||
col.list[i] <- NA
|
||||
}
|
||||
}
|
||||
if (!all(col.list %in% colnames(x))) {
|
||||
if (info == TRUE) {
|
||||
warning("Some columns do not exist and will be ignored: ",
|
||||
col.list.bak[!(col.list %in% colnames(x))] %>% toString(),
|
||||
".\nTHIS MAY STRONGLY INFLUENCE THE OUTCOME.",
|
||||
immediate. = TRUE,
|
||||
call. = FALSE)
|
||||
}
|
||||
}
|
||||
col.list
|
||||
}
|
||||
|
||||
col.list <- check_available_columns(x = x, col.list = col.list, info = warnings)
|
||||
universal_1 <- col.list[universal_1]
|
||||
universal_2 <- col.list[universal_2]
|
||||
universal_3 <- col.list[universal_3]
|
||||
universal_4 <- col.list[universal_4]
|
||||
universal_5 <- col.list[universal_5]
|
||||
universal_6 <- col.list[universal_6]
|
||||
GramPos_1 <- col.list[GramPos_1]
|
||||
GramPos_2 <- col.list[GramPos_2]
|
||||
GramPos_3 <- col.list[GramPos_3]
|
||||
GramPos_4 <- col.list[GramPos_4]
|
||||
GramPos_5 <- col.list[GramPos_5]
|
||||
GramPos_6 <- col.list[GramPos_6]
|
||||
GramNeg_1 <- col.list[GramNeg_1]
|
||||
GramNeg_2 <- col.list[GramNeg_2]
|
||||
GramNeg_3 <- col.list[GramNeg_3]
|
||||
GramNeg_4 <- col.list[GramNeg_4]
|
||||
GramNeg_5 <- col.list[GramNeg_5]
|
||||
GramNeg_6 <- col.list[GramNeg_6]
|
||||
|
||||
universal <- c(universal_1, universal_2, universal_3,
|
||||
universal_4, universal_5, universal_6)
|
||||
|
||||
gram_positive <- c(universal,
|
||||
GramPos_1, GramPos_2, GramPos_3,
|
||||
GramPos_4, GramPos_5, GramPos_6)
|
||||
gram_positive <- gram_positive[!is.null(gram_positive)]
|
||||
gram_positive <- gram_positive[!is.na(gram_positive)]
|
||||
if (length(gram_positive) < 12) {
|
||||
warning("only using ", length(gram_positive), " different antibiotics as key antibiotics for Gram-positives. See ?key_antibiotics.", call. = FALSE)
|
||||
}
|
||||
|
||||
gram_negative <- c(universal,
|
||||
GramNeg_1, GramNeg_2, GramNeg_3,
|
||||
GramNeg_4, GramNeg_5, GramNeg_6)
|
||||
gram_negative <- gram_negative[!is.null(gram_negative)]
|
||||
gram_negative <- gram_negative[!is.na(gram_negative)]
|
||||
if (length(gram_negative) < 12) {
|
||||
warning("only using ", length(gram_negative), " different antibiotics as key antibiotics for Gram-negatives. See ?key_antibiotics.", call. = FALSE)
|
||||
}
|
||||
|
||||
# join to microorganisms data set
|
||||
x <- x %>%
|
||||
as.data.frame(stringsAsFactors = FALSE) %>%
|
||||
mutate_at(vars(col_mo), as.mo) %>%
|
||||
left_join_microorganisms(by = col_mo) %>%
|
||||
mutate(key_ab = NA_character_,
|
||||
gramstain = mo_gramstain(pull(., col_mo), language = NULL))
|
||||
|
||||
# Gram +
|
||||
x <- x %>% mutate(key_ab =
|
||||
if_else(gramstain == "Gram-positive",
|
||||
tryCatch(apply(X = x[, gram_positive],
|
||||
MARGIN = 1,
|
||||
FUN = function(x) paste(x, collapse = "")),
|
||||
error = function(e) paste0(rep(".", 12), collapse = "")),
|
||||
key_ab))
|
||||
|
||||
# Gram -
|
||||
x <- x %>% mutate(key_ab =
|
||||
if_else(gramstain == "Gram-negative",
|
||||
tryCatch(apply(X = x[, gram_negative],
|
||||
MARGIN = 1,
|
||||
FUN = function(x) paste(x, collapse = "")),
|
||||
error = function(e) paste0(rep(".", 12), collapse = "")),
|
||||
key_ab))
|
||||
|
||||
# format
|
||||
key_abs <- x %>%
|
||||
pull(key_ab) %>%
|
||||
gsub("(NA|NULL)", ".", .) %>%
|
||||
gsub("[^SIR]", ".", ., ignore.case = TRUE) %>%
|
||||
toupper()
|
||||
|
||||
if (n_distinct(key_abs) == 1) {
|
||||
warning("No distinct key antibiotics determined.", call. = FALSE)
|
||||
}
|
||||
|
||||
key_abs
|
||||
|
||||
}
|
||||
|
||||
#' @importFrom dplyr progress_estimated %>%
|
||||
#' @rdname key_antibiotics
|
||||
#' @export
|
||||
key_antibiotics_equal <- function(y,
|
||||
z,
|
||||
type = c("keyantibiotics", "points"),
|
||||
ignore_I = TRUE,
|
||||
points_threshold = 2,
|
||||
info = FALSE) {
|
||||
# y is active row, z is lag
|
||||
x <- y
|
||||
y <- z
|
||||
|
||||
type <- type[1]
|
||||
|
||||
if (length(x) != length(y)) {
|
||||
stop("Length of `x` and `y` must be equal.")
|
||||
}
|
||||
|
||||
# only show progress bar on points or when at least 5000 isolates
|
||||
info_needed <- info == TRUE & (type == "points" | length(x) > 5000)
|
||||
|
||||
result <- logical(length(x))
|
||||
|
||||
if (info_needed == TRUE) {
|
||||
p <- dplyr::progress_estimated(length(x))
|
||||
}
|
||||
|
||||
for (i in seq_len(length(x))) {
|
||||
|
||||
if (info_needed == TRUE) {
|
||||
p$tick()$print()
|
||||
}
|
||||
|
||||
if (is.na(x[i])) {
|
||||
x[i] <- ""
|
||||
}
|
||||
if (is.na(y[i])) {
|
||||
y[i] <- ""
|
||||
}
|
||||
|
||||
if (x[i] == y[i]) {
|
||||
|
||||
result[i] <- TRUE
|
||||
|
||||
} else if (nchar(x[i]) != nchar(y[i])) {
|
||||
|
||||
result[i] <- FALSE
|
||||
|
||||
} else {
|
||||
|
||||
x_split <- strsplit(x[i], "")[[1]]
|
||||
y_split <- strsplit(y[i], "")[[1]]
|
||||
|
||||
if (type == "keyantibiotics") {
|
||||
|
||||
if (ignore_I == TRUE) {
|
||||
x_split[x_split == "I"] <- "."
|
||||
y_split[y_split == "I"] <- "."
|
||||
}
|
||||
|
||||
y_split[x_split == "."] <- "."
|
||||
x_split[y_split == "."] <- "."
|
||||
|
||||
result[i] <- all(x_split == y_split)
|
||||
|
||||
} else 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)
|
||||
|
||||
suppressWarnings(x_split <- x_split %>% as.rsi() %>% as.double())
|
||||
suppressWarnings(y_split <- y_split %>% as.rsi() %>% as.double())
|
||||
|
||||
points <- (x_split - y_split) %>% abs() %>% sum(na.rm = TRUE) / 2
|
||||
result[i] <- points >= points_threshold
|
||||
|
||||
} else {
|
||||
stop("`", type, '` is not a valid value for type, must be "points" or "keyantibiotics". See ?key_antibiotics')
|
||||
}
|
||||
}
|
||||
}
|
||||
if (info_needed == TRUE) {
|
||||
cat("\n")
|
||||
}
|
||||
result
|
||||
}
|
||||
@@ -1,62 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Kurtosis of the sample
|
||||
#'
|
||||
#' @description Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable.
|
||||
#'
|
||||
#' @param x a vector of values, a \code{matrix} or a \code{data frame}
|
||||
#' @param na.rm a logical value indicating whether \code{NA} values should be stripped before the computation proceeds.
|
||||
#' @exportMethod kurtosis
|
||||
#' @seealso \code{\link{skewness}}
|
||||
#' @rdname kurtosis
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @export
|
||||
kurtosis <- function(x, na.rm = FALSE) {
|
||||
UseMethod("kurtosis")
|
||||
}
|
||||
|
||||
#' @exportMethod kurtosis.default
|
||||
#' @rdname kurtosis
|
||||
#' @export
|
||||
kurtosis.default <- function(x, na.rm = FALSE) {
|
||||
x <- as.vector(x)
|
||||
if (na.rm == TRUE) {
|
||||
x <- x[!is.na(x)]
|
||||
}
|
||||
n <- length(x)
|
||||
n * base::sum((x - base::mean(x, na.rm = na.rm))^4, na.rm = na.rm) /
|
||||
(base::sum((x - base::mean(x, na.rm = na.rm))^2, na.rm = na.rm)^2)
|
||||
}
|
||||
|
||||
#' @exportMethod kurtosis.matrix
|
||||
#' @rdname kurtosis
|
||||
#' @export
|
||||
kurtosis.matrix <- function(x, na.rm = FALSE) {
|
||||
base::apply(x, 2, kurtosis.default, na.rm = na.rm)
|
||||
}
|
||||
|
||||
#' @exportMethod kurtosis.data.frame
|
||||
#' @rdname kurtosis
|
||||
#' @export
|
||||
kurtosis.data.frame <- function(x, na.rm = FALSE) {
|
||||
base::sapply(x, kurtosis.default, na.rm = na.rm)
|
||||
}
|
||||
@@ -1,105 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Pattern Matching
|
||||
#'
|
||||
#' Convenient wrapper around \code{\link[base]{grep}} to match a pattern: \code{a \%like\% b}. It always returns a \code{logical} vector and is always case-insensitive (use \code{a \%like_case\% b} for case-sensitive matching). Also, \code{pattern} (\code{b}) can be as long as \code{x} (\code{a}) to compare items of each index in both vectors, or can both have the same length to iterate over all cases.
|
||||
#' @inheritParams base::grepl
|
||||
#' @return A \code{logical} vector
|
||||
#' @name like
|
||||
#' @rdname like
|
||||
#' @export
|
||||
#' @details Using RStudio? This function can also be inserted from the Addins menu and can have its own Keyboard Shortcut like Ctrl+Shift+L or Cmd+Shift+L (see Tools > Modify Keyboard Shortcuts...).
|
||||
#' @source Idea from the \href{https://github.com/Rdatatable/data.table/blob/master/R/like.R}{\code{like} function from the \code{data.table} package}, but made it case insensitive at default and let it support multiple patterns. Also, if the regex fails the first time, it tries again with \code{perl = TRUE}.
|
||||
#' @seealso \code{\link[base]{grep}}
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' # simple test
|
||||
#' a <- "This is a test"
|
||||
#' b <- "TEST"
|
||||
#' a %like% b
|
||||
#' #> TRUE
|
||||
#' b %like% a
|
||||
#' #> FALSE
|
||||
#'
|
||||
#' # also supports multiple patterns, length must be equal to x
|
||||
#' a <- c("Test case", "Something different", "Yet another thing")
|
||||
#' b <- c("case", "diff", "yet")
|
||||
#' a %like% b
|
||||
#' #> TRUE TRUE TRUE
|
||||
#'
|
||||
#' # get frequencies of bacteria whose name start with 'Ent' or 'ent'
|
||||
#' library(dplyr)
|
||||
#' library(clean)
|
||||
#' example_isolates %>%
|
||||
#' left_join_microorganisms() %>%
|
||||
#' filter(genus %like% '^ent') %>%
|
||||
#' freq(genus, species)
|
||||
like <- function(x, pattern, ignore.case = TRUE) {
|
||||
if (length(pattern) > 1) {
|
||||
if (length(x) != length(pattern)) {
|
||||
if (length(x) == 1) {
|
||||
x <- rep(x, length(pattern))
|
||||
}
|
||||
# return TRUE for every 'x' that matches any 'pattern', FALSE otherwise
|
||||
res <- sapply(pattern, function(pttrn) base::grepl(pttrn, x, ignore.case = ignore.case))
|
||||
res2 <- as.logical(rowSums(res))
|
||||
# get only first item of every hit in pattern
|
||||
res2[duplicated(res)] <- FALSE
|
||||
res2[rowSums(res) == 0] <- NA
|
||||
return(res2)
|
||||
} else {
|
||||
# x and pattern are of same length, so items with each other
|
||||
res <- vector(length = length(pattern))
|
||||
for (i in seq_len(length(res))) {
|
||||
if (is.factor(x[i])) {
|
||||
res[i] <- as.integer(x[i]) %in% base::grep(pattern[i], levels(x[i]), ignore.case = ignore.case)
|
||||
} else {
|
||||
res[i] <- base::grepl(pattern[i], x[i], ignore.case = ignore.case)
|
||||
}
|
||||
}
|
||||
return(res)
|
||||
}
|
||||
}
|
||||
|
||||
# the regular way how grepl works; just one pattern against one or more x
|
||||
if (is.factor(x)) {
|
||||
as.integer(x) %in% base::grep(pattern, levels(x), ignore.case = ignore.case)
|
||||
} else {
|
||||
tryCatch(base::grepl(pattern, x, ignore.case = ignore.case),
|
||||
error = function(e) ifelse(test = grepl("Invalid regexp", e$message),
|
||||
# try with perl = TRUE:
|
||||
yes = return(base::grepl(pattern, x, ignore.case = ignore.case, perl = TRUE)),
|
||||
no = stop(e$message)))
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname like
|
||||
#' @export
|
||||
"%like%" <- function(x, pattern) {
|
||||
like(x, pattern, ignore.case = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname like
|
||||
#' @export
|
||||
"%like_case%" <- function(x, pattern) {
|
||||
like(x, pattern, ignore.case = FALSE)
|
||||
}
|
||||
@@ -1,587 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Determine multidrug-resistant organisms (MDRO)
|
||||
#'
|
||||
#' Determine which isolates are multidrug-resistant organisms (MDRO) according to (country-specific) guidelines.
|
||||
#' @param x table with antibiotic columns, like e.g. \code{AMX} and \code{AMC}
|
||||
#' @param guideline a specific guideline to mention, see Details. EUCAST guidelines will be used when left empty, see Details.
|
||||
#' @param info print progress
|
||||
#' @inheritParams eucast_rules
|
||||
#' @param verbose print additional info: missing antibiotic columns per parameter
|
||||
#' @inheritSection eucast_rules Antibiotics
|
||||
#' @details Currently supported guidelines are (case-insensitive):
|
||||
#' \itemize{
|
||||
#' \item{\code{guideline = "EUCAST"}: The European international guideline - EUCAST Expert Rules Version 3.1 "Intrinsic Resistance and Exceptional Phenotypes Tables" (\href{http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf}{link})}
|
||||
#' \item{\code{guideline = "TB"}: The international guideline for multi-drug resistant tuberculosis - World Health Organization "Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis" (\href{https://www.who.int/tb/publications/pmdt_companionhandbook/en/}{link})}
|
||||
#' \item{\code{guideline = "MRGN"}: The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7. DOI: 10.1186/s13756-015-0047-6}
|
||||
#' \item{\code{guideline = "BRMO"}: The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) [ZKH]" (\href{https://www.rivm.nl/Documenten_en_publicaties/Professioneel_Praktisch/Richtlijnen/Infectieziekten/WIP_Richtlijnen/WIP_Richtlijnen/Ziekenhuizen/WIP_richtlijn_BRMO_Bijzonder_Resistente_Micro_Organismen_ZKH}{link})}
|
||||
#' }
|
||||
#'
|
||||
#' Please suggest your own (country-specific) guidelines by letting us know: \url{https://gitlab.com/msberends/AMR/issues/new}.
|
||||
#' @return \itemize{
|
||||
#' \item{TB guideline - function \code{mdr_tb()} or \code{mdro(..., guideline = "TB")}:\cr Ordered factor with levels \code{Negative < Mono-resistant < Poly-resistant < Multi-drug-resistant < Extensive drug-resistant}}
|
||||
#' \item{German guideline - function \code{mrgn()} or \code{mdro(..., guideline = "MRGN")}:\cr Ordered factor with levels \code{Negative < 3MRGN < 4MRGN}}
|
||||
#' \item{Everything else:\cr Ordered factor with levels \code{Negative < Positive, unconfirmed < Positive}. The value \code{"Positive, unconfirmed"} means that, according to the guideline, it is not entirely sure if the isolate is multi-drug resistant and this should be confirmed with additional (e.g. molecular) tests}
|
||||
#' }
|
||||
#' @rdname mdro
|
||||
#' @importFrom dplyr %>%
|
||||
#' @importFrom crayon red blue bold
|
||||
#' @export
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @source
|
||||
#' EUCAST Expert Rules Version 3.1 "Intrinsic Resistance and Exceptional Phenotypes Tables" (\href{http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf}{link})
|
||||
#'
|
||||
#' World Health Organization "Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis" (\href{https://www.who.int/tb/publications/pmdt_companionhandbook/en/}{link})
|
||||
#'
|
||||
#' Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) [ZKH]" (\href{https://www.rivm.nl/Documenten_en_publicaties/Professioneel_Praktisch/Richtlijnen/Infectieziekten/WIP_Richtlijnen/WIP_Richtlijnen/Ziekenhuizen/WIP_richtlijn_BRMO_Bijzonder_Resistente_Micro_Organismen_ZKH}{link})
|
||||
#' @examples
|
||||
#' library(dplyr)
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' mutate(EUCAST = mdro(.),
|
||||
#' BRMO = brmo(.),
|
||||
#' MRGN = mrgn(.))
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' rename(PIP = TZP) %>% # no piperacillin, so take piperacillin/tazobactam
|
||||
#' mrgn() %>% # check German guideline
|
||||
#' freq() # check frequencies
|
||||
mdro <- function(x,
|
||||
guideline = NULL,
|
||||
col_mo = NULL,
|
||||
info = TRUE,
|
||||
verbose = FALSE,
|
||||
...) {
|
||||
|
||||
if (!is.data.frame(x)) {
|
||||
stop("`x` must be a data frame.", call. = FALSE)
|
||||
}
|
||||
|
||||
|
||||
if (!is.null(list(...)$country)) {
|
||||
warning("Using `country` is deprecated, use `guideline` instead. Please see ?mdro.", call. = FALSE)
|
||||
guideline <- list(...)$country
|
||||
}
|
||||
if (length(guideline) > 1) {
|
||||
stop("`guideline` must be a length one character string.", call. = FALSE)
|
||||
}
|
||||
|
||||
if (is.null(guideline)) {
|
||||
guideline <- "eucast"
|
||||
}
|
||||
if (tolower(guideline) == "nl") {
|
||||
guideline <- "BRMO"
|
||||
}
|
||||
if (tolower(guideline) == "de") {
|
||||
guideline <- "MRGN"
|
||||
}
|
||||
if (!tolower(guideline) %in% c("brmo", "mrgn", "eucast", "tb")) {
|
||||
stop("invalid guideline: ", guideline, call. = FALSE)
|
||||
}
|
||||
guideline <- list(code = tolower(guideline))
|
||||
|
||||
# try to find columns based on type
|
||||
# -- mo
|
||||
if (is.null(col_mo)) {
|
||||
col_mo <- search_type_in_df(x = x, type = "mo")
|
||||
}
|
||||
if (is.null(col_mo) & guideline$code == "tb") {
|
||||
message(blue("NOTE: No column found as input for `col_mo`,",
|
||||
bold("assuming all records contain", italic("Mycobacterium tuberculosis.\n"))))
|
||||
x$mo <- AMR::as.mo("Mycobacterium tuberculosis")
|
||||
col_mo <- "mo"
|
||||
}
|
||||
if (is.null(col_mo)) {
|
||||
stop("`col_mo` must be set.", call. = FALSE)
|
||||
}
|
||||
|
||||
if (guideline$code == "eucast") {
|
||||
guideline$name <- "EUCAST Expert Rules, \"Intrinsic Resistance and Exceptional Phenotypes Tables\""
|
||||
guideline$author <- "EUCAST (European Committee on Antimicrobial Susceptibility Testing)"
|
||||
guideline$version <- "3.1"
|
||||
guideline$source <- "http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf"
|
||||
|
||||
} else if (guideline$code == "tb") {
|
||||
guideline$name <- "Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis"
|
||||
guideline$author <- "WHO (World Health Organization)"
|
||||
guideline$version <- "WHO/HTM/TB/2014.11"
|
||||
guideline$source <- "https://www.who.int/tb/publications/pmdt_companionhandbook/en/"
|
||||
|
||||
# support per country:
|
||||
} else if (guideline$code == "mrgn") {
|
||||
guideline$name <- "Cross-border comparison of the Dutch and German guidelines on multidrug-resistant Gram-negative microorganisms"
|
||||
guideline$author <- "J. M\u00fcller, A. Voss, R. K\u00f6ck, ..., W.V. Kern, C. Wendt, A.W. Friedrich"
|
||||
guideline$version <- "N/A"
|
||||
guideline$source <- "M\u00fcller et al. (2015) Antimicrobial Resistance and Infection Control 4:7. DOI: 10.1186/s13756-015-0047-6"
|
||||
} else if (guideline$code == "brmo") {
|
||||
guideline$name <- "WIP-Richtlijn Bijzonder Resistente Micro-organismen (BRMO)"
|
||||
guideline$author <- "RIVM (Rijksinstituut voor de Volksgezondheid)"
|
||||
guideline$version <- "Revision as of December 2017"
|
||||
guideline$source <- "https://www.rivm.nl/Documenten_en_publicaties/Professioneel_Praktisch/Richtlijnen/Infectieziekten/WIP_Richtlijnen/WIP_Richtlijnen/Ziekenhuizen/WIP_richtlijn_BRMO_Bijzonder_Resistente_Micro_Organismen_ZKH"
|
||||
} else {
|
||||
stop("This guideline is currently unsupported: ", guideline$code, call. = FALSE)
|
||||
}
|
||||
|
||||
if (info == TRUE) {
|
||||
cat("Determining multidrug-resistant organisms (MDRO), according to:\n",
|
||||
"Guideline: ", red(guideline$name), "\n",
|
||||
"Version: ", red(guideline$version), "\n",
|
||||
"Author: ", red(guideline$author), "\n",
|
||||
"Source: ", blue(guideline$source), "\n",
|
||||
"\n", sep = "")
|
||||
}
|
||||
|
||||
if (guideline$code == "tb") {
|
||||
cols_ab <- get_column_abx(x = x,
|
||||
soft_dependencies = c("CAP",
|
||||
"ETH",
|
||||
"GAT",
|
||||
"INH",
|
||||
"PZA",
|
||||
"RIF",
|
||||
"RIB",
|
||||
"RFP"),
|
||||
verbose = verbose, ...)
|
||||
} else if (guideline$code == "mrgn") {
|
||||
cols_ab <- get_column_abx(x = x,
|
||||
soft_dependencies = c("PIP",
|
||||
"CTX",
|
||||
"CAZ",
|
||||
"IPM",
|
||||
"MEM",
|
||||
"CIP"),
|
||||
verbose = verbose, ...)
|
||||
} else {
|
||||
cols_ab <- get_column_abx(x = x, verbose = verbose, ...)
|
||||
}
|
||||
|
||||
AMC <- cols_ab["AMC"]
|
||||
AMK <- cols_ab["AMK"]
|
||||
AMP <- cols_ab["AMP"]
|
||||
AMX <- cols_ab["AMX"]
|
||||
ATM <- cols_ab["ATM"]
|
||||
AZL <- cols_ab["AZL"]
|
||||
AZM <- cols_ab["AZM"]
|
||||
CAZ <- cols_ab["CAZ"]
|
||||
CED <- cols_ab["CED"]
|
||||
CHL <- cols_ab["CHL"]
|
||||
CIP <- cols_ab["CIP"]
|
||||
CLI <- cols_ab["CLI"]
|
||||
CLR <- cols_ab["CLR"]
|
||||
COL <- cols_ab["COL"]
|
||||
CRO <- cols_ab["CRO"]
|
||||
CTX <- cols_ab["CTX"]
|
||||
CXM <- cols_ab["CXM"]
|
||||
CZO <- cols_ab["CZO"]
|
||||
DAP <- cols_ab["DAP"]
|
||||
DOX <- cols_ab["DOX"]
|
||||
ERY <- cols_ab["ERY"]
|
||||
ETP <- cols_ab["ETP"]
|
||||
FEP <- cols_ab["FEP"]
|
||||
FLC <- cols_ab["FLC"]
|
||||
FOS <- cols_ab["FOS"]
|
||||
FOX <- cols_ab["FOX"]
|
||||
FUS <- cols_ab["FUS"]
|
||||
GEN <- cols_ab["GEN"]
|
||||
IPM <- cols_ab["IPM"]
|
||||
KAN <- cols_ab["KAN"]
|
||||
LIN <- cols_ab["LIN"]
|
||||
LNZ <- cols_ab["LNZ"]
|
||||
LVX <- cols_ab["LVX"]
|
||||
MEM <- cols_ab["MEM"]
|
||||
MEZ <- cols_ab["MEZ"]
|
||||
MTR <- cols_ab["MTR"]
|
||||
MFX <- cols_ab["MFX"]
|
||||
MNO <- cols_ab["MNO"]
|
||||
NAL <- cols_ab["NAL"]
|
||||
NEO <- cols_ab["NEO"]
|
||||
NET <- cols_ab["NET"]
|
||||
NIT <- cols_ab["NIT"]
|
||||
NOR <- cols_ab["NOR"]
|
||||
NOV <- cols_ab["NOV"]
|
||||
OFX <- cols_ab["OFX"]
|
||||
PEN <- cols_ab["PEN"]
|
||||
PIP <- cols_ab["PIP"]
|
||||
PLB <- cols_ab["PLB"]
|
||||
PRI <- cols_ab["PRI"]
|
||||
QDA <- cols_ab["QDA"]
|
||||
RID <- cols_ab["RID"]
|
||||
RIF <- cols_ab["RIF"]
|
||||
RXT <- cols_ab["RXT"]
|
||||
SIS <- cols_ab["SIS"]
|
||||
SXT <- cols_ab["SXT"]
|
||||
TCY <- cols_ab["TCY"]
|
||||
TEC <- cols_ab["TEC"]
|
||||
TGC <- cols_ab["TGC"]
|
||||
TIC <- cols_ab["TIC"]
|
||||
TMP <- cols_ab["TMP"]
|
||||
TOB <- cols_ab["TOB"]
|
||||
TZP <- cols_ab["TZP"]
|
||||
VAN <- cols_ab["VAN"]
|
||||
# additional for TB
|
||||
CAP <- cols_ab["CAP"]
|
||||
ETH <- cols_ab["ETH"]
|
||||
GAT <- cols_ab["GAT"]
|
||||
INH <- cols_ab["INH"]
|
||||
PZA <- cols_ab["PZA"]
|
||||
RIF <- cols_ab["RIF"]
|
||||
RIB <- cols_ab["RIB"]
|
||||
RFP <- cols_ab["RFP"]
|
||||
abx_tb <- c(CAP, ETH, GAT, INH, PZA, RIF, RIB, RFP)
|
||||
abx_tb <- abx_tb[!is.na(abx_tb)]
|
||||
if (guideline$code == "tb" & length(abx_tb) == 0) {
|
||||
stop("No antimycobacterials found in data set.", call. = FALSE)
|
||||
}
|
||||
|
||||
ab_missing <- function(ab) {
|
||||
isTRUE(ab %in% c(NULL, NA)) | length(ab) == 0
|
||||
}
|
||||
|
||||
# antibiotic classes
|
||||
aminoglycosides <- c(TOB, GEN)
|
||||
cephalosporins <- c(FEP, CTX, FOX, CED, CAZ, CRO, CXM, CZO)
|
||||
cephalosporins_3rd <- c(CTX, CRO, CAZ)
|
||||
carbapenems <- c(ETP, IPM, MEM)
|
||||
fluoroquinolones <- c(OFX, CIP, LVX, MFX)
|
||||
|
||||
# helper function for editing the table
|
||||
trans_tbl <- function(to, rows, cols, any_all) {
|
||||
cols <- cols[!ab_missing(cols)]
|
||||
cols <- cols[!is.na(cols)]
|
||||
if (length(rows) > 0 & length(cols) > 0) {
|
||||
if (any_all == "any") {
|
||||
row_filter <- which(x[, cols] == "R")
|
||||
} else if (any_all == "all") {
|
||||
row_filter <- x %>%
|
||||
mutate(index = seq_len(nrow(.))) %>%
|
||||
filter_at(vars(cols), all_vars(. == "R")) %>%
|
||||
pull((index))
|
||||
}
|
||||
rows <- rows[rows %in% row_filter]
|
||||
x[rows, "MDRO"] <<- to
|
||||
}
|
||||
}
|
||||
|
||||
x <- x %>%
|
||||
mutate_at(vars(col_mo), as.mo) %>%
|
||||
# join to microorganisms data set
|
||||
left_join_microorganisms(by = col_mo) %>%
|
||||
# add unconfirmed to where genus is available
|
||||
mutate(MDRO = ifelse(!is.na(genus), 1, NA_integer_)) %>%
|
||||
# transform to data.frame so subsetting is possible with x[y, z] (might not be the case with tibble/data.table/...)
|
||||
as.data.frame(stringsAsFactors = FALSE)
|
||||
|
||||
if (guideline$code == "eucast") {
|
||||
# EUCAST ------------------------------------------------------------------
|
||||
# Table 5
|
||||
trans_tbl(3,
|
||||
which(x$family == "Enterobacteriaceae"
|
||||
| x$fullname %like% "^Pseudomonas aeruginosa"
|
||||
| x$genus == "Acinetobacter"),
|
||||
COL,
|
||||
"all")
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "^Salmonella Typhi"),
|
||||
c(carbapenems, fluoroquinolones),
|
||||
"any")
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "^Haemophilus influenzae"),
|
||||
c(cephalosporins_3rd, carbapenems, fluoroquinolones),
|
||||
"any")
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "^Moraxella catarrhalis"),
|
||||
c(cephalosporins_3rd, fluoroquinolones),
|
||||
"any")
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "^Neisseria meningitidis"),
|
||||
c(cephalosporins_3rd, fluoroquinolones),
|
||||
"any")
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "^Neisseria gonorrhoeae"),
|
||||
AZM,
|
||||
"any")
|
||||
# Table 6
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "^(Coagulase-negative|Staphylococcus (aureus|epidermidis|hominis|haemolyticus|intermedius|pseudointermedius))"),
|
||||
c(VAN, TEC, DAP, LNZ, QDA, TGC),
|
||||
"any")
|
||||
trans_tbl(3,
|
||||
which(x$genus == "Corynebacterium"),
|
||||
c(VAN, TEC, DAP, LNZ, QDA, TGC),
|
||||
"any")
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "^Streptococcus pneumoniae"),
|
||||
c(carbapenems, VAN, TEC, DAP, LNZ, QDA, TGC, RIF),
|
||||
"any")
|
||||
trans_tbl(3, # Sr. groups A/B/C/G
|
||||
which(x$fullname %like% "^Streptococcus (group (A|B|C|G)|pyogenes|agalactiae|equisimilis|equi|zooepidemicus|dysgalactiae|anginosus)"),
|
||||
c(PEN, cephalosporins, VAN, TEC, DAP, LNZ, QDA, TGC),
|
||||
"any")
|
||||
trans_tbl(3,
|
||||
which(x$genus == "Enterococcus"),
|
||||
c(DAP, LNZ, TGC, TEC),
|
||||
"any")
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "^Enterococcus faecalis"),
|
||||
c(AMP, AMX),
|
||||
"any")
|
||||
# Table 7
|
||||
trans_tbl(3,
|
||||
which(x$genus == "Bacteroides"),
|
||||
MTR,
|
||||
"any")
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "^Clostridium difficile"),
|
||||
c(MTR, VAN),
|
||||
"any")
|
||||
}
|
||||
|
||||
if (guideline$code == "mrgn") {
|
||||
# Germany -----------------------------------------------------------------
|
||||
CTX_or_CAZ <- CTX %or% CAZ
|
||||
IPM_or_MEM <- IPM %or% MEM
|
||||
x$missing <- NA_character_
|
||||
if (is.na(PIP)) PIP <- "missing"
|
||||
if (is.na(CTX_or_CAZ)) CTX_or_CAZ <- "missing"
|
||||
if (is.na(IPM_or_MEM)) IPM_or_MEM <- "missing"
|
||||
if (is.na(IPM)) IPM <- "missing"
|
||||
if (is.na(MEM)) MEM <- "missing"
|
||||
if (is.na(CIP)) CIP <- "missing"
|
||||
|
||||
# Table 1
|
||||
x[which((x$family == "Enterobacteriaceae" |
|
||||
x$fullname %like% "^Acinetobacter baumannii") &
|
||||
x[, PIP] == "R" &
|
||||
x[, CTX_or_CAZ] == "R" &
|
||||
x[, IPM_or_MEM] == "S" &
|
||||
x[, CIP] == "R"),
|
||||
"MDRO"] <- 2 # 2 = 3MRGN
|
||||
|
||||
x[which((x$family == "Enterobacteriaceae" |
|
||||
x$fullname %like% "^Acinetobacter baumannii") &
|
||||
x[, PIP] == "R" &
|
||||
x[, CTX_or_CAZ] == "R" &
|
||||
x[, IPM_or_MEM] == "R" &
|
||||
x[, CIP] == "R"),
|
||||
"MDRO"] <- 3 # 3 = 4MRGN, overwrites 3MRGN if applicable
|
||||
|
||||
x[which((x$family == "Enterobacteriaceae" |
|
||||
x$fullname %like% "^Acinetobacter baumannii") &
|
||||
x[, IPM] == "R" | x[, MEM] == "R"),
|
||||
"MDRO"] <- 3 # 3 = 4MRGN, always when imipenem or meropenem is R
|
||||
|
||||
x[which(x$fullname %like% "^Pseudomonas aeruginosa" &
|
||||
(x[, PIP] == "S") +
|
||||
(x[, CTX_or_CAZ] == "S") +
|
||||
(x[, IPM_or_MEM] == "S") +
|
||||
(x[, CIP] == "S") == 1),
|
||||
"MDRO"] <- 2 # 2 = 3MRGN, if only 1 group is S
|
||||
|
||||
x[which((x$fullname %like% "^Pseudomonas aeruginosa") &
|
||||
x[, PIP] == "R" &
|
||||
x[, CTX_or_CAZ] == "R" &
|
||||
x[, IPM_or_MEM] == "R" &
|
||||
x[, CIP] == "R"),
|
||||
"MDRO"] <- 3 # 3 = 4MRGN
|
||||
}
|
||||
|
||||
if (guideline$code == "brmo") {
|
||||
# Netherlands -------------------------------------------------------------
|
||||
aminoglycosides <- aminoglycosides[!is.na(aminoglycosides)]
|
||||
fluoroquinolones <- fluoroquinolones[!is.na(fluoroquinolones)]
|
||||
carbapenems <- carbapenems[!is.na(carbapenems)]
|
||||
amino <- AMX %or% AMP
|
||||
third <- CAZ %or% CTX
|
||||
ESBLs <- c(amino, third)
|
||||
ESBLs <- ESBLs[!is.na(ESBLs)]
|
||||
if (length(ESBLs) != 2) {
|
||||
ESBLs <- character(0)
|
||||
}
|
||||
|
||||
# Table 1
|
||||
trans_tbl(3,
|
||||
which(x$family == "Enterobacteriaceae"),
|
||||
c(aminoglycosides, fluoroquinolones),
|
||||
"all")
|
||||
|
||||
trans_tbl(2,
|
||||
which(x$family == "Enterobacteriaceae"),
|
||||
carbapenems,
|
||||
"any")
|
||||
|
||||
trans_tbl(2,
|
||||
which(x$family == "Enterobacteriaceae"),
|
||||
ESBLs,
|
||||
"all")
|
||||
|
||||
# Table 2
|
||||
trans_tbl(2,
|
||||
which(x$genus == "Acinetobacter"),
|
||||
c(carbapenems),
|
||||
"any")
|
||||
trans_tbl(3,
|
||||
which(x$genus == "Acinetobacter"),
|
||||
c(aminoglycosides, fluoroquinolones),
|
||||
"all")
|
||||
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "^Stenotrophomonas maltophilia"),
|
||||
SXT,
|
||||
"all")
|
||||
|
||||
if (!ab_missing(MEM) & !ab_missing(IPM)
|
||||
& !ab_missing(GEN) & !ab_missing(TOB)
|
||||
& !ab_missing(CIP)
|
||||
& !ab_missing(CAZ)
|
||||
& !ab_missing(TZP)) {
|
||||
x$psae <- 0
|
||||
x[which(x[, MEM] == "R" | x[, IPM] == "R"), "psae"] <- 1 + x[which(x[, MEM] == "R" | x[, IPM] == "R"), "psae"]
|
||||
x[which(x[, GEN] == "R" & x[, TOB] == "R"), "psae"] <- 1 + x[which(x[, GEN] == "R" & x[, TOB] == "R"), "psae"]
|
||||
x[which(x[, CIP] == "R"), "psae"] <- 1 + x[which(x[, CIP] == "R"), "psae"]
|
||||
x[which(x[, CAZ] == "R"), "psae"] <- 1 + x[which(x[, CAZ] == "R"), "psae"]
|
||||
x[which(x[, TZP] == "R"), "psae"] <- 1 + x[which(x[, TZP] == "R"), "psae"]
|
||||
} else {
|
||||
x$psae <- 0
|
||||
}
|
||||
x[which(
|
||||
x$fullname %like% "Pseudomonas aeruginosa"
|
||||
& x$psae >= 3
|
||||
), "MDRO"] <- 3
|
||||
|
||||
# Table 3
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "Streptococcus pneumoniae"),
|
||||
PEN,
|
||||
"all")
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "Streptococcus pneumoniae"),
|
||||
VAN,
|
||||
"all")
|
||||
trans_tbl(3,
|
||||
which(x$fullname %like% "Enterococcus faecium"),
|
||||
c(PEN, VAN),
|
||||
"all")
|
||||
}
|
||||
|
||||
prepare_drug <- function(ab) {
|
||||
# returns vector values of drug
|
||||
# if `ab` is a column name, looks up the values in `x`
|
||||
if (length(ab) == 1 & is.character(ab)) {
|
||||
if (ab %in% colnames(x)) {
|
||||
ab <- as.data.frame(x)[, ab]
|
||||
}
|
||||
}
|
||||
ab <- as.character(as.rsi(ab))
|
||||
ab[is.na(ab)] <- ""
|
||||
ab
|
||||
}
|
||||
drug_is_R <- function(ab) {
|
||||
# returns logical vector
|
||||
ab <- prepare_drug(ab)
|
||||
if (length(ab) == 1) {
|
||||
rep(ab, NROW(x)) == "R"
|
||||
} else {
|
||||
ab == "R"
|
||||
}
|
||||
}
|
||||
drug_is_not_R <- function(ab) {
|
||||
# returns logical vector
|
||||
ab <- prepare_drug(ab)
|
||||
if (length(ab) == 1) {
|
||||
rep(ab, NROW(x)) != "R"
|
||||
} else {
|
||||
ab != "R"
|
||||
}
|
||||
}
|
||||
|
||||
if (guideline$code == "tb") {
|
||||
# Tuberculosis ------------------------------------------------------------
|
||||
x <- x %>%
|
||||
mutate(mono_count = 0,
|
||||
mono_count = ifelse(drug_is_R(INH), mono_count + 1, mono_count),
|
||||
mono_count = ifelse(drug_is_R(RIF), mono_count + 1, mono_count),
|
||||
mono_count = ifelse(drug_is_R(ETH), mono_count + 1, mono_count),
|
||||
mono_count = ifelse(drug_is_R(PZA), mono_count + 1, mono_count),
|
||||
mono_count = ifelse(drug_is_R(RIB), mono_count + 1, mono_count),
|
||||
mono_count = ifelse(drug_is_R(RFP), mono_count + 1, mono_count),
|
||||
# from here on logicals
|
||||
mono = mono_count > 0,
|
||||
poly = ifelse(mono_count > 1 & drug_is_not_R(RIF) & drug_is_not_R(INH),
|
||||
TRUE, FALSE),
|
||||
mdr = ifelse(drug_is_R(RIF) & drug_is_R(INH),
|
||||
TRUE, FALSE),
|
||||
xdr = ifelse(drug_is_R(LVX) | drug_is_R(MFX) | drug_is_R(GAT),
|
||||
TRUE, FALSE),
|
||||
second = ifelse(drug_is_R(CAP) | drug_is_R(KAN) | drug_is_R(AMK),
|
||||
TRUE, FALSE),
|
||||
xdr = ifelse(mdr & xdr & second, TRUE, FALSE)) %>%
|
||||
mutate(mdr_tb = case_when(xdr ~ 5,
|
||||
mdr ~ 4,
|
||||
poly ~ 3,
|
||||
mono ~ 2,
|
||||
TRUE ~ 1),
|
||||
# keep all real TB, make other species NA
|
||||
mdr_tb = ifelse(x$fullname == "Mycobacterium tuberculosis", mdr_tb, NA_real_))
|
||||
}
|
||||
|
||||
# return results
|
||||
if (guideline$code == "tb") {
|
||||
factor(x = x$mdr_tb,
|
||||
levels = 1:5,
|
||||
labels = c("Negative", "Mono-resistant", "Poly-resistant", "Multi-drug-resistant", "Extensive drug-resistant"),
|
||||
ordered = TRUE)
|
||||
} else if (guideline$code == "mrgn") {
|
||||
factor(x = x$MDRO,
|
||||
levels = 1:3,
|
||||
labels = c("Negative", "3MRGN", "4MRGN"),
|
||||
ordered = TRUE)
|
||||
} else {
|
||||
factor(x = x$MDRO,
|
||||
levels = 1:3,
|
||||
labels = c("Negative", "Positive, unconfirmed", "Positive"),
|
||||
ordered = TRUE)
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname mdro
|
||||
#' @export
|
||||
brmo <- function(x, guideline = "BRMO", ...) {
|
||||
mdro(x, guideline = "BRMO", ...)
|
||||
}
|
||||
|
||||
#' @rdname mdro
|
||||
#' @export
|
||||
mrgn <- function(x, guideline = "MRGN", ...) {
|
||||
mdro(x = x, guideline = "MRGN", ...)
|
||||
}
|
||||
|
||||
#' @rdname mdro
|
||||
#' @export
|
||||
mdr_tb <- function(x, guideline = "TB", ...) {
|
||||
mdro(x = x, guideline = "TB", ...)
|
||||
}
|
||||
|
||||
#' @rdname mdro
|
||||
#' @export
|
||||
eucast_exceptional_phenotypes <- function(x, guideline = "EUCAST", ...) {
|
||||
mdro(x = x, guideline = "EUCAST", ...)
|
||||
}
|
||||
@@ -1,326 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Class 'mic'
|
||||
#'
|
||||
#' This transforms a vector to a new class \code{mic}, which is an ordered factor with valid MIC values as levels. Invalid MIC values will be translated as \code{NA} with a warning.
|
||||
#' @rdname as.mic
|
||||
#' @param x vector
|
||||
#' @param na.rm a logical indicating whether missing values should be removed
|
||||
#' @details Interpret MIC values as RSI values with \code{\link{as.rsi}}. It supports guidelines from EUCAST and CLSI.
|
||||
#' @return Ordered factor with new class \code{mic}
|
||||
#' @keywords mic
|
||||
#' @export
|
||||
#' @importFrom dplyr %>%
|
||||
#' @seealso \code{\link{as.rsi}}
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
|
||||
#' is.mic(mic_data)
|
||||
#'
|
||||
#' # this can also coerce combined MIC/RSI values:
|
||||
#' as.mic("<=0.002; S") # will return <=0.002
|
||||
#'
|
||||
#' # interpret MIC values
|
||||
#' as.rsi(x = as.mic(2),
|
||||
#' mo = as.mo("S. pneumoniae"),
|
||||
#' ab = "AMX",
|
||||
#' guideline = "EUCAST")
|
||||
#' as.rsi(x = as.mic(4),
|
||||
#' mo = as.mo("S. pneumoniae"),
|
||||
#' ab = "AMX",
|
||||
#' guideline = "EUCAST")
|
||||
#'
|
||||
#' plot(mic_data)
|
||||
#' barplot(mic_data)
|
||||
#'
|
||||
#' library(clean)
|
||||
#' freq(mic_data)
|
||||
as.mic <- function(x, na.rm = FALSE) {
|
||||
if (is.mic(x)) {
|
||||
x
|
||||
} else {
|
||||
x <- x %>% unlist()
|
||||
if (na.rm == TRUE) {
|
||||
x <- x[!is.na(x)]
|
||||
}
|
||||
x.bak <- x
|
||||
|
||||
# comma to period
|
||||
x <- gsub(",", ".", x, fixed = TRUE)
|
||||
# remove space between operator and number ("<= 0.002" -> "<=0.002")
|
||||
x <- gsub("(<|=|>) +", "\\1", x)
|
||||
# transform => to >= and =< to <=
|
||||
x <- gsub("=>", ">=", x, fixed = TRUE)
|
||||
x <- gsub("=<", "<=", x, fixed = TRUE)
|
||||
# starting dots must start with 0
|
||||
x <- gsub("^[.]+", "0.", x)
|
||||
# <=0.2560.512 should be 0.512
|
||||
x <- gsub(".*[.].*[.]", "0.", x)
|
||||
# remove ending .0
|
||||
x <- gsub("[.]+0$", "", x)
|
||||
# remove all after last digit
|
||||
x <- gsub("[^0-9]+$", "", x)
|
||||
# keep only one zero before dot
|
||||
x <- gsub("0+[.]", "0.", x)
|
||||
# starting 00 is probably 0.0 if there's no dot yet
|
||||
x[!x %like% "[.]"] <- gsub("^00", "0.0", x[!x %like% "[.]"])
|
||||
# remove last zeroes
|
||||
x <- gsub("([.].?)0+$", "\\1", x)
|
||||
x <- gsub("(.*[.])0+$", "\\10", x)
|
||||
# remove ending .0 again
|
||||
x[x %like% "[.]"] <- gsub("0+$", "", x[x %like% "[.]"])
|
||||
# force to be character
|
||||
x <- as.character(x)
|
||||
# trim it
|
||||
x <- trimws(x)
|
||||
|
||||
## previously unempty values now empty - should return a warning later on
|
||||
x[x.bak != "" & x == ""] <- "invalid"
|
||||
|
||||
# these are allowed MIC values and will become factor levels
|
||||
lvls <- c("<0.001", "<=0.001", "0.001", ">=0.001", ">0.001",
|
||||
"<0.002", "<=0.002", "0.002", ">=0.002", ">0.002",
|
||||
"<0.003", "<=0.003", "0.003", ">=0.003", ">0.003",
|
||||
"<0.004", "<=0.004", "0.004", ">=0.004", ">0.004",
|
||||
"<0.005", "<=0.005", "0.005", ">=0.005", ">0.005",
|
||||
"<0.006", "<=0.006", "0.006", ">=0.006", ">0.006",
|
||||
"<0.007", "<=0.007", "0.007", ">=0.007", ">0.007",
|
||||
"<0.008", "<=0.008", "0.008", ">=0.008", ">0.008",
|
||||
"<0.009", "<=0.009", "0.009", ">=0.009", ">0.009",
|
||||
"<0.01", "<=0.01", "0.01", ">=0.01", ">0.01",
|
||||
"<0.012", "<=0.012", "0.012", ">=0.012", ">0.012",
|
||||
"<0.0125", "<=0.0125", "0.0125", ">=0.0125", ">0.0125",
|
||||
"<0.016", "<=0.016", "0.016", ">=0.016", ">0.016",
|
||||
"<0.019", "<=0.019", "0.019", ">=0.019", ">0.019",
|
||||
"<0.02", "<=0.02", "0.02", ">=0.02", ">0.02",
|
||||
"<0.023", "<=0.023", "0.023", ">=0.023", ">0.023",
|
||||
"<0.025", "<=0.025", "0.025", ">=0.025", ">0.025",
|
||||
"<0.028", "<=0.028", "0.028", ">=0.028", ">0.028",
|
||||
"<0.03", "<=0.03", "0.03", ">=0.03", ">0.03",
|
||||
"<0.031", "<=0.031", "0.031", ">=0.031", ">0.031",
|
||||
"<0.032", "<=0.032", "0.032", ">=0.032", ">0.032",
|
||||
"<0.038", "<=0.038", "0.038", ">=0.038", ">0.038",
|
||||
"<0.04", "<=0.04", "0.04", ">=0.04", ">0.04",
|
||||
"<0.047", "<=0.047", "0.047", ">=0.047", ">0.047",
|
||||
"<0.05", "<=0.05", "0.05", ">=0.05", ">0.05",
|
||||
"<0.054", "<=0.054", "0.054", ">=0.054", ">0.054",
|
||||
"<0.06", "<=0.06", "0.06", ">=0.06", ">0.06",
|
||||
"<0.0625", "<=0.0625", "0.0625", ">=0.0625", ">0.0625",
|
||||
"<0.063", "<=0.063", "0.063", ">=0.063", ">0.063",
|
||||
"<0.064", "<=0.064", "0.064", ">=0.064", ">0.064",
|
||||
"<0.075", "<=0.075", "0.075", ">=0.075", ">0.075",
|
||||
"<0.08", "<=0.08", "0.08", ">=0.08", ">0.08",
|
||||
"<0.09", "<=0.09", "0.09", ">=0.09", ">0.09",
|
||||
"<0.094", "<=0.094", "0.094", ">=0.094", ">0.094",
|
||||
"<0.095", "<=0.095", "0.095", ">=0.095", ">0.095",
|
||||
"<0.1", "<=0.1", "0.1", ">=0.1", ">0.1",
|
||||
"<0.12", "<=0.12", "0.12", ">=0.12", ">0.12",
|
||||
"<0.125", "<=0.125", "0.125", ">=0.125", ">0.125",
|
||||
"<0.128", "<=0.128", "0.128", ">=0.128", ">0.128",
|
||||
"<0.15", "<=0.15", "0.15", ">=0.15", ">0.15",
|
||||
"<0.16", "<=0.16", "0.16", ">=0.16", ">0.16",
|
||||
"<0.17", "<=0.17", "0.17", ">=0.17", ">0.17",
|
||||
"<0.18", "<=0.18", "0.18", ">=0.18", ">0.18",
|
||||
"<0.19", "<=0.19", "0.19", ">=0.19", ">0.19",
|
||||
"<0.2", "<=0.2", "0.2", ">=0.2", ">0.2",
|
||||
"<0.23", "<=0.23", "0.23", ">=0.23", ">0.23",
|
||||
"<0.25", "<=0.25", "0.25", ">=0.25", ">0.25",
|
||||
"<0.256", "<=0.256", "0.256", ">=0.256", ">0.256",
|
||||
"<0.28", "<=0.28", "0.28", ">=0.28", ">0.28",
|
||||
"<0.3", "<=0.3", "0.3", ">=0.3", ">0.3",
|
||||
"<0.32", "<=0.32", "0.32", ">=0.32", ">0.32",
|
||||
"<0.35", "<=0.35", "0.35", ">=0.35", ">0.35",
|
||||
"<0.36", "<=0.36", "0.36", ">=0.36", ">0.36",
|
||||
"<0.38", "<=0.38", "0.38", ">=0.38", ">0.38",
|
||||
"<0.47", "<=0.47", "0.47", ">=0.47", ">0.47",
|
||||
"<0.5", "<=0.5", "0.5", ">=0.5", ">0.5",
|
||||
"<0.512", "<=0.512", "0.512", ">=0.512", ">0.512",
|
||||
"<0.64", "<=0.64", "0.64", ">=0.64", ">0.64",
|
||||
"<0.73", "<=0.73", "0.73", ">=0.73", ">0.73",
|
||||
"<0.75", "<=0.75", "0.75", ">=0.75", ">0.75",
|
||||
"<0.8", "<=0.8", "0.8", ">=0.8", ">0.8",
|
||||
"<0.94", "<=0.94", "0.94", ">=0.94", ">0.94",
|
||||
"<1", "<=1", "1", ">=1", ">1",
|
||||
"<1.5", "<=1.5", "1.5", ">=1.5", ">1.5",
|
||||
"<2", "<=2", "2", ">=2", ">2",
|
||||
"<3", "<=3", "3", ">=3", ">3",
|
||||
"<4", "<=4", "4", ">=4", ">4",
|
||||
"<5", "<=5", "5", ">=5", ">5",
|
||||
"<6", "<=6", "6", ">=6", ">6",
|
||||
"<7", "<=7", "7", ">=7", ">7",
|
||||
"<8", "<=8", "8", ">=8", ">8",
|
||||
"<10", "<=10", "10", ">=10", ">10",
|
||||
"<12", "<=12", "12", ">=12", ">12",
|
||||
"<16", "<=16", "16", ">=16", ">16",
|
||||
"<20", "<=20", "20", ">=20", ">20",
|
||||
"<24", "<=24", "24", ">=24", ">24",
|
||||
"<32", "<=32", "32", ">=32", ">32",
|
||||
"<40", "<=40", "40", ">=40", ">40",
|
||||
"<48", "<=48", "48", ">=48", ">48",
|
||||
"<64", "<=64", "64", ">=64", ">64",
|
||||
"<80", "<=80", "80", ">=80", ">80",
|
||||
"<96", "<=96", "96", ">=96", ">96",
|
||||
"<128", "<=128", "128", ">=128", ">128",
|
||||
"129",
|
||||
"<160", "<=160", "160", ">=160", ">160",
|
||||
"<256", "<=256", "256", ">=256", ">256",
|
||||
"257",
|
||||
"<320", "<=320", "320", ">=320", ">320",
|
||||
"<512", "<=512", "512", ">=512", ">512",
|
||||
"513",
|
||||
"<1024", "<=1024", "1024", ">=1024", ">1024",
|
||||
"1025")
|
||||
|
||||
na_before <- x[is.na(x) | x == ""] %>% length()
|
||||
x[!x %in% lvls] <- NA
|
||||
na_after <- x[is.na(x) | x == ""] %>% length()
|
||||
|
||||
if (na_before != na_after) {
|
||||
list_missing <- x.bak[is.na(x) & !is.na(x.bak) & x.bak != ""] %>%
|
||||
unique() %>%
|
||||
sort()
|
||||
list_missing <- paste0('"', list_missing, '"', collapse = ", ")
|
||||
warning(na_after - na_before, " results truncated (",
|
||||
round(((na_after - na_before) / length(x)) * 100),
|
||||
"%) that were invalid MICs: ",
|
||||
list_missing, call. = FALSE)
|
||||
}
|
||||
|
||||
structure(.Data = factor(x, levels = lvls, ordered = TRUE),
|
||||
class = c("mic", "ordered", "factor"))
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname as.mic
|
||||
#' @export
|
||||
#' @importFrom dplyr %>%
|
||||
is.mic <- function(x) {
|
||||
class(x) %>% identical(c("mic", "ordered", "factor"))
|
||||
}
|
||||
|
||||
#' @exportMethod as.double.mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
as.double.mic <- function(x, ...) {
|
||||
as.double(gsub("(<|=|>)+", "", as.character(x)))
|
||||
}
|
||||
|
||||
#' @exportMethod as.integer.mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
as.integer.mic <- function(x, ...) {
|
||||
as.integer(gsub("(<|=|>)+", "", as.character(x)))
|
||||
}
|
||||
|
||||
#' @exportMethod as.numeric.mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
as.numeric.mic <- function(x, ...) {
|
||||
as.numeric(gsub("(<|=|>)+", "", as.character(x)))
|
||||
}
|
||||
|
||||
#' @exportMethod droplevels.mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
droplevels.mic <- function(x, exclude = ifelse(anyNA(levels(x)), NULL, NA), ...) {
|
||||
x <- droplevels.factor(x, exclude = exclude, ...)
|
||||
class(x) <- c("mic", "ordered", "factor")
|
||||
x
|
||||
}
|
||||
|
||||
#' @exportMethod print.mic
|
||||
#' @export
|
||||
#' @importFrom dplyr %>% tibble group_by summarise pull
|
||||
#' @noRd
|
||||
print.mic <- function(x, ...) {
|
||||
cat("Class 'mic'\n")
|
||||
print(as.character(x), quote = FALSE)
|
||||
}
|
||||
|
||||
#' @exportMethod summary.mic
|
||||
#' @export
|
||||
#' @importFrom dplyr %>%
|
||||
#' @noRd
|
||||
summary.mic <- function(object, ...) {
|
||||
x <- object
|
||||
n_total <- x %>% length()
|
||||
x <- x[!is.na(x)]
|
||||
n <- x %>% length()
|
||||
c(
|
||||
"Class" = "mic",
|
||||
"<NA>" = n_total - n,
|
||||
"Min." = sort(x)[1] %>% as.character(),
|
||||
"Max." = sort(x)[n] %>% as.character()
|
||||
)
|
||||
}
|
||||
|
||||
#' @exportMethod plot.mic
|
||||
#' @export
|
||||
#' @importFrom graphics barplot axis par
|
||||
#' @noRd
|
||||
plot.mic <- function(x,
|
||||
main = paste("MIC values of", deparse(substitute(x))),
|
||||
ylab = "Frequency",
|
||||
xlab = "MIC value",
|
||||
axes = FALSE,
|
||||
...) {
|
||||
barplot(table(droplevels.factor(x)),
|
||||
ylab = ylab,
|
||||
xlab = xlab,
|
||||
axes = axes,
|
||||
main = main,
|
||||
...)
|
||||
axis(2, seq(0, max(table(droplevels.factor(x)))))
|
||||
}
|
||||
|
||||
#' @exportMethod barplot.mic
|
||||
#' @export
|
||||
#' @importFrom graphics barplot axis
|
||||
#' @noRd
|
||||
barplot.mic <- function(height,
|
||||
main = paste("MIC values of", deparse(substitute(height))),
|
||||
ylab = "Frequency",
|
||||
xlab = "MIC value",
|
||||
axes = FALSE,
|
||||
...) {
|
||||
barplot(table(droplevels.factor(height)),
|
||||
ylab = ylab,
|
||||
xlab = xlab,
|
||||
axes = axes,
|
||||
main = main,
|
||||
...)
|
||||
axis(2, seq(0, max(table(droplevels.factor(height)))))
|
||||
}
|
||||
|
||||
#' @importFrom pillar type_sum
|
||||
#' @export
|
||||
type_sum.mic <- function(x) {
|
||||
"mic"
|
||||
}
|
||||
|
||||
#' @importFrom pillar pillar_shaft
|
||||
#' @export
|
||||
pillar_shaft.mic <- function(x, ...) {
|
||||
out <- trimws(format(x))
|
||||
out[is.na(x)] <- pillar::style_na(NA)
|
||||
pillar::new_pillar_shaft_simple(out, align = "right", min_width = 4)
|
||||
}
|
||||
@@ -1,171 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
# No export, no Rd
|
||||
addin_insert_in <- function() {
|
||||
rstudioapi::insertText(" %in% ")
|
||||
}
|
||||
|
||||
# No export, no Rd
|
||||
addin_insert_like <- function() {
|
||||
rstudioapi::insertText(" %like% ")
|
||||
}
|
||||
|
||||
#' @importFrom crayon blue bold red
|
||||
#' @importFrom dplyr %>% pull
|
||||
search_type_in_df <- function(x, type) {
|
||||
# try to find columns based on type
|
||||
found <- NULL
|
||||
|
||||
colnames(x) <- trimws(colnames(x))
|
||||
|
||||
# -- mo
|
||||
if (type == "mo") {
|
||||
if ("mo" %in% lapply(x, class)) {
|
||||
found <- colnames(x)[lapply(x, class) == "mo"][1]
|
||||
} else if (any(colnames(x) %like% "^(mo|microorganism|organism|bacteria|bacterie)s?$")) {
|
||||
found <- colnames(x)[colnames(x) %like% "^(mo|microorganism|organism|bacteria|bacterie)s?$"][1]
|
||||
} else if (any(colnames(x) %like% "^(microorganism|organism|bacteria|bacterie)")) {
|
||||
found <- colnames(x)[colnames(x) %like% "^(microorganism|organism|bacteria|bacterie)"][1]
|
||||
} else if (any(colnames(x) %like% "species")) {
|
||||
found <- colnames(x)[colnames(x) %like% "species"][1]
|
||||
}
|
||||
|
||||
}
|
||||
# -- key antibiotics
|
||||
if (type == "keyantibiotics") {
|
||||
if (any(colnames(x) %like% "^key.*(ab|antibiotics)")) {
|
||||
found <- colnames(x)[colnames(x) %like% "^key.*(ab|antibiotics)"][1]
|
||||
}
|
||||
}
|
||||
# -- date
|
||||
if (type == "date") {
|
||||
if (any(colnames(x) %like% "^(specimen date|specimen_date|spec_date)")) {
|
||||
# WHONET support
|
||||
found <- colnames(x)[colnames(x) %like% "^(specimen date|specimen_date|spec_date)"][1]
|
||||
if (!any(class(x %>% pull(found)) %in% c("Date", "POSIXct"))) {
|
||||
stop(red(paste0("ERROR: Found column `", bold(found), "` to be used as input for `col_", type,
|
||||
"`, but this column contains no valid dates. Transform its values to valid dates first.")),
|
||||
call. = FALSE)
|
||||
}
|
||||
} else {
|
||||
for (i in seq_len(ncol(x))) {
|
||||
if (any(class(x %>% pull(i)) %in% c("Date", "POSIXct"))) {
|
||||
found <- colnames(x)[i]
|
||||
break
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
# -- patient id
|
||||
if (type == "patient_id") {
|
||||
if (any(colnames(x) %like% "^(identification |patient|patid)")) {
|
||||
found <- colnames(x)[colnames(x) %like% "^(identification |patient|patid)"][1]
|
||||
}
|
||||
}
|
||||
# -- specimen
|
||||
if (type == "specimen") {
|
||||
if (any(colnames(x) %like% "(specimen type|spec_type)")) {
|
||||
found <- colnames(x)[colnames(x) %like% "(specimen type|spec_type)"][1]
|
||||
} else if (any(colnames(x) %like% "^(specimen)")) {
|
||||
found <- colnames(x)[colnames(x) %like% "^(specimen)"][1]
|
||||
}
|
||||
}
|
||||
|
||||
if (!is.null(found)) {
|
||||
msg <- paste0("NOTE: Using column `", bold(found), "` as input for `col_", type, "`.")
|
||||
if (type %in% c("keyantibiotics", "specimen")) {
|
||||
msg <- paste(msg, "Use", bold(paste0("col_", type), "= FALSE"), "to prevent this.")
|
||||
}
|
||||
message(blue(msg))
|
||||
}
|
||||
found
|
||||
}
|
||||
|
||||
stopifnot_installed_package <- function(package) {
|
||||
# no "utils::installed.packages()" since it requires non-staged install since R 3.6.0
|
||||
# https://developer.r-project.org/Blog/public/2019/02/14/staged-install/index.html
|
||||
get(".packageName", envir = asNamespace(package))
|
||||
return(invisible())
|
||||
}
|
||||
|
||||
"%or%" <- function(x, y) {
|
||||
if (is.null(x) | is.null(y)) {
|
||||
if (is.null(x)) {
|
||||
return(y)
|
||||
} else {
|
||||
return(x)
|
||||
}
|
||||
}
|
||||
ifelse(!is.na(x),
|
||||
x,
|
||||
ifelse(!is.na(y), y, NA))
|
||||
}
|
||||
|
||||
class_integrity_check <- function(value, type, check_vector) {
|
||||
if (!all(value[!is.na(value)] %in% check_vector)) {
|
||||
warning(paste0("invalid ", type, ", NA generated"), call. = FALSE)
|
||||
value[!value %in% check_vector] <- NA
|
||||
}
|
||||
value
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
# Percentages -------------------------------------------------------------
|
||||
# Can all be removed when clean 1.2.0 is on CRAN
|
||||
|
||||
getdecimalplaces <- function(x, minimum = 0, maximum = 3) {
|
||||
if (maximum < minimum) {
|
||||
maximum <- minimum
|
||||
}
|
||||
if (minimum > maximum) {
|
||||
minimum <- maximum
|
||||
}
|
||||
max_places <- max(unlist(lapply(strsplit(sub("0+$", "",
|
||||
as.character(x * 100)), ".", fixed = TRUE),
|
||||
function(y) ifelse(length(y) == 2, nchar(y[2]), 0))), na.rm = TRUE)
|
||||
max(min(max_places,
|
||||
maximum, na.rm = TRUE),
|
||||
minimum, na.rm = TRUE)
|
||||
}
|
||||
|
||||
round2 <- function(x, digits = 0, force_zero = TRUE) {
|
||||
# https://stackoverflow.com/a/12688836/4575331
|
||||
val <- (trunc((abs(x) * 10 ^ digits) + 0.5) / 10 ^ digits) * sign(x)
|
||||
if (digits > 0 & force_zero == TRUE) {
|
||||
val[val != as.integer(val) & !is.na(val)] <- paste0(val[val != as.integer(val) & !is.na(val)],
|
||||
strrep("0", max(0, digits - nchar(gsub(".*[.](.*)$", "\\1", val[val != as.integer(val) & !is.na(val)])))))
|
||||
}
|
||||
val
|
||||
}
|
||||
|
||||
percentage <- function(x, digits = NULL, ...) {
|
||||
if (is.null(digits)) {
|
||||
digits <- getdecimalplaces(x, minimum = 0, maximum = 1)
|
||||
}
|
||||
# round right: percentage(0.4455) should return "44.6%", not "44.5%"
|
||||
x <- as.numeric(round2(x, digits = digits + 2))
|
||||
x_formatted <- format(as.double(x) * 100, scientific = FALSE, digits = digits, nsmall = digits, ...)
|
||||
x_formatted[!is.na(x)] <- paste0(x_formatted[!is.na(x)], "%")
|
||||
x_formatted
|
||||
}
|
||||
-217
@@ -1,217 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
# print successful as.mo coercions to a options entry
|
||||
#' @importFrom dplyr %>% distinct filter
|
||||
#' @importFrom utils write.csv
|
||||
set_mo_history <- function(x, mo, uncertainty_level, force = FALSE, disable = FALSE) {
|
||||
if (isTRUE(disable)) {
|
||||
return(base::invisible())
|
||||
}
|
||||
|
||||
# don't save codes that are in a code data set already
|
||||
mo <- mo[!x %in% microorganisms.codes$code & !x %in% microorganisms.translation$mo_old]
|
||||
x <- x[!x %in% microorganisms.codes$code & !x %in% microorganisms.translation$mo_old]
|
||||
|
||||
warning_new_write <- FALSE
|
||||
|
||||
if (base::interactive() | force == TRUE) {
|
||||
mo_hist <- read_mo_history(uncertainty_level = uncertainty_level, force = force)
|
||||
df <- data.frame(x, mo, stringsAsFactors = FALSE) %>%
|
||||
distinct(x, .keep_all = TRUE) %>%
|
||||
filter(!is.na(x) & !is.na(mo))
|
||||
if (nrow(df) == 0) {
|
||||
return(base::invisible())
|
||||
}
|
||||
x <- toupper(df$x)
|
||||
mo <- df$mo
|
||||
for (i in seq_len(length(x))) {
|
||||
# save package version too, as both the as.mo() algorithm and the reference data set may change
|
||||
if (NROW(mo_hist[base::which(mo_hist$x == x[i] &
|
||||
mo_hist$uncertainty_level >= uncertainty_level &
|
||||
mo_hist$package_version == utils::packageVersion("AMR")), ]) == 0) {
|
||||
# # Not using the file system:
|
||||
# tryCatch(options(mo_remembered_results = rbind(mo_hist,
|
||||
# data.frame(
|
||||
# x = x[i],
|
||||
# mo = mo[i],
|
||||
# uncertainty_level = uncertainty_level,
|
||||
# package_version = base::as.character(utils::packageVersion("AMR")),
|
||||
# stringsAsFactors = FALSE))),
|
||||
# error = function(e) base::invisible())
|
||||
# # don't remember more than 1,000 different input values
|
||||
# if (tryCatch(nrow(getOption("mo_remembered_results")), error = function(e) 1001) > 1000) {
|
||||
# return(base::invisible())
|
||||
# }
|
||||
if (is.null(mo_hist) & interactive()) {
|
||||
warning_new_write <- TRUE
|
||||
}
|
||||
tryCatch(write.csv(rbind(mo_hist,
|
||||
data.frame(
|
||||
x = x[i],
|
||||
mo = mo[i],
|
||||
uncertainty_level = uncertainty_level,
|
||||
package_version = base::as.character(utils::packageVersion("AMR")),
|
||||
stringsAsFactors = FALSE)),
|
||||
row.names = FALSE,
|
||||
file = mo_history_file()),
|
||||
error = function(e) {
|
||||
warning_new_write <- FALSE; base::invisible()
|
||||
})
|
||||
}
|
||||
}
|
||||
}
|
||||
if (warning_new_write == TRUE) {
|
||||
message(blue(paste0("NOTE: results are saved to ", mo_history_file(), ".")))
|
||||
}
|
||||
return(base::invisible())
|
||||
}
|
||||
|
||||
get_mo_history <- function(x, uncertainty_level, force = FALSE, disable = FALSE) {
|
||||
if (isTRUE(disable)) {
|
||||
return(to_class_mo(NA))
|
||||
}
|
||||
|
||||
history <- read_mo_history(uncertainty_level = uncertainty_level, force = force)
|
||||
if (base::is.null(history)) {
|
||||
result <- NA
|
||||
} else {
|
||||
result <- data.frame(x = as.character(toupper(x)), stringsAsFactors = FALSE) %>%
|
||||
left_join(history, by = "x") %>%
|
||||
pull(mo)
|
||||
}
|
||||
to_class_mo(result)
|
||||
}
|
||||
|
||||
#' @importFrom dplyr %>% filter distinct
|
||||
#' @importFrom utils read.csv
|
||||
read_mo_history <- function(uncertainty_level = 2, force = FALSE, unfiltered = FALSE, disable = FALSE) {
|
||||
if (isTRUE(disable)) {
|
||||
return(NULL)
|
||||
}
|
||||
|
||||
if ((!base::interactive() & force == FALSE)) {
|
||||
return(NULL)
|
||||
}
|
||||
uncertainty_level_param <- uncertainty_level
|
||||
|
||||
# # Not using the file system:
|
||||
# history <- tryCatch(getOption("mo_remembered_results"),
|
||||
# error = function(e) NULL)
|
||||
history <- tryCatch(read.csv(mo_history_file(), stringsAsFactors = FALSE),
|
||||
warning = function(w) invisible(),
|
||||
error = function(e) NULL)
|
||||
if (is.null(history)) {
|
||||
return(NULL)
|
||||
}
|
||||
# Below: filter on current package version.
|
||||
# Even current fullnames may be replaced by new taxonomic names, so new versions of
|
||||
# the Catalogue of Life must not lead to data corruption.
|
||||
|
||||
if (unfiltered == FALSE) {
|
||||
history <- history %>%
|
||||
filter(package_version == as.character(utils::packageVersion("AMR")),
|
||||
# only take unknowns if uncertainty_level_param is higher
|
||||
((mo == "UNKNOWN" & uncertainty_level_param == uncertainty_level) |
|
||||
(mo != "UNKNOWN" & uncertainty_level_param >= uncertainty_level))) %>%
|
||||
arrange(desc(uncertainty_level)) %>%
|
||||
distinct(x, mo, .keep_all = TRUE)
|
||||
}
|
||||
|
||||
if (nrow(history) == 0) {
|
||||
NULL
|
||||
} else {
|
||||
history
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname as.mo
|
||||
#' @importFrom crayon red
|
||||
#' @importFrom utils menu
|
||||
#' @export
|
||||
clear_mo_history <- function(...) {
|
||||
if (!is.null(read_mo_history())) {
|
||||
if (interactive() & !isTRUE(list(...)$force)) {
|
||||
q <- menu(title = paste("This will clear all",
|
||||
format(nrow(read_mo_history(999, unfiltered = TRUE)), big.mark = ","),
|
||||
"previously determined microbial IDs. Are you sure?"),
|
||||
choices = c("Yes", "No"),
|
||||
graphics = FALSE)
|
||||
if (q != 1) {
|
||||
return(invisible())
|
||||
}
|
||||
}
|
||||
# # Not using the file system:
|
||||
# success <- tryCatch(options(mo_remembered_results = NULL),
|
||||
# error = function(e) FALSE)
|
||||
success <- create_blank_mo_history()
|
||||
if (!isFALSE(success)) {
|
||||
cat(red(paste("File", mo_history_file(), "cleared.")))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#' @importFrom utils write.csv
|
||||
create_blank_mo_history <- function() {
|
||||
tryCatch(
|
||||
write.csv(x = data.frame(x = character(0),
|
||||
mo = character(0),
|
||||
uncertainty_level = integer(0),
|
||||
package_version = character(0),
|
||||
stringsAsFactors = FALSE),
|
||||
row.names = FALSE,
|
||||
file = mo_history_file()),
|
||||
warning = function(w) invisible(),
|
||||
error = function(e) TRUE)
|
||||
}
|
||||
|
||||
|
||||
# Borrowed all below code from the extrafont package,
|
||||
# https://github.com/wch/extrafont/blob/254c3f99b02f11adb59affbda699a92aec8624f5/R/utils.r
|
||||
inst_path <- function() {
|
||||
envname <- environmentName(parent.env(environment()))
|
||||
|
||||
# If installed in package, envname == "AMR"
|
||||
# If loaded with load_all, envname == "package:AMR"
|
||||
# (This is kind of strange)
|
||||
if (envname == "AMR") {
|
||||
system.file(package = "AMR")
|
||||
} else {
|
||||
srcfile <- attr(attr(inst_path, "srcref"), "srcfile")
|
||||
file.path(dirname(dirname(srcfile$filename)), "inst")
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
# Get the path where extrafontdb is installed
|
||||
db_path <- function() {
|
||||
system.file(package = "AMR")
|
||||
}
|
||||
|
||||
# fonttable file
|
||||
mo_history_file <- function() {
|
||||
file.path(mo_history_path(), "mo_history.csv")
|
||||
}
|
||||
|
||||
# Path of fontmap directory
|
||||
mo_history_path <- function() {
|
||||
file.path(db_path(), "mo_history")
|
||||
}
|
||||
-439
@@ -1,439 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Property of a microorganism
|
||||
#'
|
||||
#' Use these functions to return a specific property of a microorganism. All input values will be evaluated internally with \code{\link{as.mo}}, which makes it possible for input of these functions to use microbial abbreviations, codes and names. See Examples.
|
||||
#' @param x any (vector of) text that can be coerced to a valid microorganism code with \code{\link{as.mo}}
|
||||
#' @param property one of the column names of the \code{\link{microorganisms}} data set or \code{"shortname"}
|
||||
#' @param language language of the returned text, defaults to system language (see \code{\link{get_locale}}) and can also be set with \code{\link{getOption}("AMR_locale")}. Use \code{language = NULL} or \code{language = ""} to prevent translation.
|
||||
#' @param ... other parameters passed on to \code{\link{as.mo}}
|
||||
#' @param open browse the URL using \code{\link[utils]{browseURL}()}
|
||||
#' @details All functions will return the most recently known taxonomic property according to the Catalogue of Life, except for \code{mo_ref}, \code{mo_authors} and \code{mo_year}. This leads to the following results:
|
||||
#' \itemize{
|
||||
#' \item{\code{mo_name("Chlamydia psittaci")} will return \code{"Chlamydophila psittaci"} (with a warning about the renaming)}
|
||||
#' \item{\code{mo_ref("Chlamydia psittaci")} will return \code{"Page, 1968"} (with a warning about the renaming)}
|
||||
#' \item{\code{mo_ref("Chlamydophila psittaci")} will return \code{"Everett et al., 1999"} (without a warning)}
|
||||
#' }
|
||||
#'
|
||||
#' The Gram stain - \code{mo_gramstain()} - will be determined on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002) who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram positive - all other bacteria are considered Gram negative. Species outside the kingdom of Bacteria will return a value \code{NA}.
|
||||
#'
|
||||
#' All output will be \link{translate}d where possible.
|
||||
#'
|
||||
#' The function \code{mo_url()} will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.
|
||||
#' @inheritSection catalogue_of_life Catalogue of Life
|
||||
#' @inheritSection as.mo Source
|
||||
#' @rdname mo_property
|
||||
#' @name mo_property
|
||||
#' @return \itemize{
|
||||
#' \item{An \code{integer} in case of \code{mo_year}}
|
||||
#' \item{A \code{list} in case of \code{mo_taxonomy}}
|
||||
#' \item{A named \code{character} in case of \code{mo_url}}
|
||||
#' \item{A \code{character} in all other cases}
|
||||
#' }
|
||||
#' @export
|
||||
#' @seealso \code{\link{microorganisms}}
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' # taxonomic tree -----------------------------------------------------------
|
||||
#' mo_kingdom("E. coli") # "Bacteria"
|
||||
#' mo_phylum("E. coli") # "Proteobacteria"
|
||||
#' mo_class("E. coli") # "Gammaproteobacteria"
|
||||
#' mo_order("E. coli") # "Enterobacteriales"
|
||||
#' mo_family("E. coli") # "Enterobacteriaceae"
|
||||
#' mo_genus("E. coli") # "Escherichia"
|
||||
#' mo_species("E. coli") # "coli"
|
||||
#' mo_subspecies("E. coli") # ""
|
||||
#'
|
||||
#' # colloquial properties ----------------------------------------------------
|
||||
#' mo_name("E. coli") # "Escherichia coli"
|
||||
#' mo_fullname("E. coli") # "Escherichia coli", same as mo_name()
|
||||
#' mo_shortname("E. coli") # "E. coli"
|
||||
#'
|
||||
#' # other properties ---------------------------------------------------------
|
||||
#' mo_gramstain("E. coli") # "Gram-negative"
|
||||
#' mo_type("E. coli") # "Bacteria" (equal to kingdom, but may be translated)
|
||||
#' mo_rank("E. coli") # "species"
|
||||
#' mo_url("E. coli") # get the direct url to the online database entry
|
||||
#' mo_synonyms("E. coli") # get previously accepted taxonomic names
|
||||
#'
|
||||
#' # scientific reference -----------------------------------------------------
|
||||
#' mo_ref("E. coli") # "Castellani et al., 1919"
|
||||
#' mo_authors("E. coli") # "Castellani et al."
|
||||
#' mo_year("E. coli") # 1919
|
||||
#'
|
||||
#' # abbreviations known in the field -----------------------------------------
|
||||
#' mo_genus("MRSA") # "Staphylococcus"
|
||||
#' mo_species("MRSA") # "aureus"
|
||||
#' mo_shortname("VISA") # "S. aureus"
|
||||
#' mo_gramstain("VISA") # "Gram-positive"
|
||||
#'
|
||||
#' mo_genus("EHEC") # "Escherichia"
|
||||
#' mo_species("EHEC") # "coli"
|
||||
#'
|
||||
#' # known subspecies ---------------------------------------------------------
|
||||
#' mo_name("doylei") # "Campylobacter jejuni doylei"
|
||||
#' mo_genus("doylei") # "Campylobacter"
|
||||
#' mo_species("doylei") # "jejuni"
|
||||
#' mo_subspecies("doylei") # "doylei"
|
||||
#'
|
||||
#' mo_fullname("K. pneu rh") # "Klebsiella pneumoniae rhinoscleromatis"
|
||||
#' mo_shortname("K. pneu rh") # "K. pneumoniae"
|
||||
#'
|
||||
#' \donttest{
|
||||
#' # Becker classification, see ?as.mo ----------------------------------------
|
||||
#' mo_fullname("S. epi") # "Staphylococcus epidermidis"
|
||||
#' mo_fullname("S. epi", Becker = TRUE) # "Coagulase-negative Staphylococcus (CoNS)"
|
||||
#' mo_shortname("S. epi") # "S. epidermidis"
|
||||
#' mo_shortname("S. epi", Becker = TRUE) # "CoNS"
|
||||
#'
|
||||
#' # Lancefield classification, see ?as.mo ------------------------------------
|
||||
#' mo_fullname("S. pyo") # "Streptococcus pyogenes"
|
||||
#' mo_fullname("S. pyo", Lancefield = TRUE) # "Streptococcus group A"
|
||||
#' mo_shortname("S. pyo") # "S. pyogenes"
|
||||
#' mo_shortname("S. pyo", Lancefield = TRUE) # "GAS" (='Group A Streptococci')
|
||||
#'
|
||||
#'
|
||||
#' # language support for German, Dutch, Spanish, Portuguese, Italian and French
|
||||
#' mo_gramstain("E. coli", language = "de") # "Gramnegativ"
|
||||
#' mo_gramstain("E. coli", language = "nl") # "Gram-negatief"
|
||||
#' mo_gramstain("E. coli", language = "es") # "Gram negativo"
|
||||
#'
|
||||
#' # mo_type is equal to mo_kingdom, but mo_kingdom will remain official
|
||||
#' mo_kingdom("E. coli") # "Bacteria" on a German system
|
||||
#' mo_type("E. coli") # "Bakterien" on a German system
|
||||
#' mo_type("E. coli") # "Bacteria" on an English system
|
||||
#'
|
||||
#' mo_fullname("S. pyogenes",
|
||||
#' Lancefield = TRUE,
|
||||
#' language = "de") # "Streptococcus Gruppe A"
|
||||
#' mo_fullname("S. pyogenes",
|
||||
#' Lancefield = TRUE,
|
||||
#' language = "nl") # "Streptococcus groep A"
|
||||
#'
|
||||
#'
|
||||
#' # get a list with the complete taxonomy (from kingdom to subspecies)
|
||||
#' mo_taxonomy("E. coli")
|
||||
#' # get a list with the taxonomy, the authors and the URL to the online database
|
||||
#' mo_info("E. coli")
|
||||
#' }
|
||||
mo_name <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(mo_validate(x = x, property = "fullname", ...), language = language, only_unknown = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_fullname <- mo_name
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_shortname <- function(x, language = get_locale(), ...) {
|
||||
x.mo <- AMR::as.mo(x, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
replace_empty <- function(x) {
|
||||
x[x == ""] <- "spp."
|
||||
x
|
||||
}
|
||||
|
||||
# get first char of genus and complete species in English
|
||||
shortnames <- paste0(substr(mo_genus(x.mo, language = NULL), 1, 1), ". ", replace_empty(mo_species(x.mo, language = NULL)))
|
||||
|
||||
# exceptions for Staphylococci
|
||||
shortnames[shortnames == "S. coagulase-negative"] <- "CoNS"
|
||||
shortnames[shortnames == "S. coagulase-positive"] <- "CoPS"
|
||||
# exceptions for Streptococci: Streptococcus Group A -> GAS
|
||||
shortnames[shortnames %like% "S. group [ABCDFGHK]"] <- paste0("G", gsub("S. group ([ABCDFGHK])", "\\1", shortnames[shortnames %like% "S. group [ABCDFGHK]"]), "S")
|
||||
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
translate_AMR(shortnames, language = language, only_unknown = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_subspecies <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(mo_validate(x = x, property = "subspecies", ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_species <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(mo_validate(x = x, property = "species", ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_genus <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(mo_validate(x = x, property = "genus", ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_family <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(mo_validate(x = x, property = "family", ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_order <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(mo_validate(x = x, property = "order", ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_class <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(mo_validate(x = x, property = "class", ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_phylum <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(mo_validate(x = x, property = "phylum", ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_kingdom <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(mo_validate(x = x, property = "kingdom", ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_type <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(mo_validate(x = x, property = "kingdom", ...), language = language, only_unknown = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_gramstain <- function(x, language = get_locale(), ...) {
|
||||
x.mo <- AMR::as.mo(x, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
x.phylum <- mo_phylum(x.mo)
|
||||
# DETERMINE GRAM STAIN FOR BACTERIA
|
||||
# Source: https://itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=956097
|
||||
# It says this:
|
||||
# Kingdom Bacteria (Cavalier-Smith, 2002)
|
||||
# Subkingdom Posibacteria (Cavalier-Smith, 2002)
|
||||
# Direct Children:
|
||||
# Phylum Actinobacteria (Cavalier-Smith, 2002)
|
||||
# Phylum Chloroflexi (Garrity and Holt, 2002)
|
||||
# Phylum Firmicutes (corrig. Gibbons and Murray, 1978)
|
||||
# Phylum Tenericutes (Murray, 1984)
|
||||
x <- NA_character_
|
||||
# make all bacteria Gram negative
|
||||
x[mo_kingdom(x.mo) == "Bacteria"] <- "Gram-negative"
|
||||
# overwrite these phyla with Gram positive
|
||||
x[x.phylum %in% c("Actinobacteria",
|
||||
"Chloroflexi",
|
||||
"Firmicutes",
|
||||
"Tenericutes")
|
||||
| x.mo == "B_GRAMP"] <- "Gram-positive"
|
||||
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
translate_AMR(x, language = language, only_unknown = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_ref <- function(x, ...) {
|
||||
mo_validate(x = x, property = "ref", ...)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_authors <- function(x, ...) {
|
||||
x <- mo_validate(x = x, property = "ref", ...)
|
||||
# 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)])
|
||||
suppressWarnings(x)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_year <- function(x, ...) {
|
||||
x <- mo_validate(x = x, property = "ref", ...)
|
||||
# get last 4 digits
|
||||
x[!is.na(x)] <- gsub(".*([0-9]{4})$", "\\1", x[!is.na(x)])
|
||||
suppressWarnings(as.integer(x))
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_rank <- function(x, ...) {
|
||||
mo_validate(x = x, property = "rank", ...)
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_taxonomy <- function(x, language = get_locale(), ...) {
|
||||
x <- AMR::as.mo(x, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
result <- base::list(kingdom = AMR::mo_kingdom(x, language = language),
|
||||
phylum = AMR::mo_phylum(x, language = language),
|
||||
class = AMR::mo_class(x, language = language),
|
||||
order = AMR::mo_order(x, language = language),
|
||||
family = AMR::mo_family(x, language = language),
|
||||
genus = AMR::mo_genus(x, language = language),
|
||||
species = AMR::mo_species(x, language = language),
|
||||
subspecies = AMR::mo_subspecies(x, language = language))
|
||||
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
result
|
||||
}
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_synonyms <- function(x, ...) {
|
||||
x <- AMR::as.mo(x, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
IDs <- AMR::mo_property(x = x, property = "col_id", language = NULL)
|
||||
syns <- lapply(IDs, function(col_id) {
|
||||
res <- sort(AMR::microorganisms.old[which(AMR::microorganisms.old$col_id_new == col_id), "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_locale(), ...) {
|
||||
x <- AMR::as.mo(x, ...)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
info <- lapply(x, function(y)
|
||||
c(mo_taxonomy(y, language = language),
|
||||
list(synonyms = mo_synonyms(y),
|
||||
url = unname(mo_url(y, open = FALSE)),
|
||||
ref = mo_ref(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
|
||||
#' @importFrom utils browseURL
|
||||
#' @importFrom dplyr %>% left_join select mutate case_when
|
||||
#' @export
|
||||
mo_url <- function(x, open = FALSE, ...) {
|
||||
mo <- AMR::as.mo(x = x, ... = ...)
|
||||
mo_names <- AMR::mo_name(mo)
|
||||
metadata <- get_mo_failures_uncertainties_renamed()
|
||||
|
||||
df <- data.frame(mo, stringsAsFactors = FALSE) %>%
|
||||
left_join(select(AMR::microorganisms, mo, source, species_id), by = "mo") %>%
|
||||
mutate(url = case_when(source == "CoL" ~
|
||||
paste0(gsub("{year}", catalogue_of_life$year, catalogue_of_life$url_CoL, fixed = TRUE), "details/species/id/", species_id),
|
||||
source == "DSMZ" ~
|
||||
paste0(catalogue_of_life$url_DSMZ, "/", unlist(lapply(strsplit(mo_names, ""), function(x) x[1]))),
|
||||
TRUE ~
|
||||
NA_character_))
|
||||
|
||||
u <- df$url
|
||||
names(u) <- mo_names
|
||||
if (open == TRUE) {
|
||||
if (length(u) > 1) {
|
||||
warning("only the first URL will be opened, as `browseURL()` only suports one string.")
|
||||
}
|
||||
browseURL(u[1L])
|
||||
}
|
||||
|
||||
load_mo_failures_uncertainties_renamed(metadata)
|
||||
u
|
||||
}
|
||||
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @importFrom data.table data.table as.data.table setkey
|
||||
#' @export
|
||||
mo_property <- function(x, property = "fullname", language = get_locale(), ...) {
|
||||
if (length(property) != 1L) {
|
||||
stop("'property' must be of length 1.")
|
||||
}
|
||||
if (!property %in% colnames(AMR::microorganisms)) {
|
||||
stop("invalid property: '", property, "' - use a column name of the `microorganisms` data set")
|
||||
}
|
||||
|
||||
translate_AMR(mo_validate(x = x, property = property, ...), language = language, only_unknown = TRUE)
|
||||
}
|
||||
|
||||
mo_validate <- function(x, property, ...) {
|
||||
|
||||
dots <- list(...)
|
||||
Becker <- dots$Becker
|
||||
if (is.null(Becker)) {
|
||||
Becker <- FALSE
|
||||
}
|
||||
Lancefield <- dots$Lancefield
|
||||
if (is.null(Lancefield)) {
|
||||
Lancefield <- FALSE
|
||||
}
|
||||
|
||||
if (!"AMR" %in% base::.packages()) {
|
||||
require("AMR")
|
||||
# check .onLoad() in R/zzz.R: data tables are created there.
|
||||
}
|
||||
|
||||
# try to catch an error when inputting an invalid parameter
|
||||
# so the 'call.' can be set to FALSE
|
||||
tryCatch(x[1L] %in% AMR::microorganisms[1, property],
|
||||
error = function(e) stop(e$message, call. = FALSE))
|
||||
|
||||
if (is.mo(x)
|
||||
& !Becker %in% c(TRUE, "all")
|
||||
& !Lancefield %in% c(TRUE, "all")) {
|
||||
# this will not reset mo_uncertainties and mo_failures
|
||||
# because it's already a valid MO
|
||||
x <- exec_as.mo(x, property = property, initial_search = FALSE, ...)
|
||||
} else if (!all(x %in% pull(AMR::microorganisms, property))
|
||||
| Becker %in% c(TRUE, "all")
|
||||
| Lancefield %in% c(TRUE, "all")) {
|
||||
x <- exec_as.mo(x, property = property, ...)
|
||||
}
|
||||
|
||||
if (property == "mo") {
|
||||
return(to_class_mo(x))
|
||||
} else if (property == "col_id") {
|
||||
return(as.integer(x))
|
||||
} else {
|
||||
return(x)
|
||||
}
|
||||
}
|
||||
-221
@@ -1,221 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Use predefined reference data set
|
||||
#'
|
||||
#' @description These functions can be used to predefine your own reference to be used in \code{\link{as.mo}} and consequently all \code{mo_*} functions like \code{\link{mo_genus}} and \code{\link{mo_gramstain}}.
|
||||
#'
|
||||
#' This is \strong{the fastest way} to have your organisation (or analysis) specific codes picked up and translated by this package.
|
||||
#' @param path location of your reference file, see Details
|
||||
#' @rdname mo_source
|
||||
#' @name mo_source
|
||||
#' @aliases set_mo_source get_mo_source
|
||||
#' @details The reference file can be a text file seperated 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 need to have the \code{readxl} package installed.
|
||||
#'
|
||||
#' \code{set_mo_source} will check the file for validity: it must be a \code{data.frame}, must have a column named \code{"mo"} which contains values from \code{microorganisms$mo} and must have a reference column with your own defined values. If all tests pass, \code{set_mo_source} will read the file into R and export it to \code{"~/.mo_source.rds"}. This compressed data file will then be used at default for MO determination (function \code{\link{as.mo}} and consequently all \code{mo_*} functions like \code{\link{mo_genus}} and \code{\link{mo_gramstain}}). The location of the original file will be saved as option with \code{\link{options}(mo_source = path)}. Its timestamp will be saved with \code{\link{options}(mo_source_datetime = ...)}.
|
||||
#'
|
||||
#' \code{get_mo_source} will return the data set by reading \code{"~/.mo_source.rds"} with \code{\link{readRDS}}. If the original file has changed (the file defined with \code{path}), it will call \code{set_mo_source} to update the data file automatically.
|
||||
#'
|
||||
#' Reading an Excel file (\code{.xlsx}) with only one row has a size of 8-9 kB. The compressed file used by this package will have a size of 0.1 kB and can be read by \code{get_mo_source} in only a couple of microseconds (a millionth of a second).
|
||||
#' @section How it works:
|
||||
#' Imagine this data on a sheet of an Excel file (mo codes were looked up in the `microorganisms` data set). The first column contains the organisation specific codes, the second column contains an MO code from this package:
|
||||
#' \preformatted{
|
||||
#' | A | B |
|
||||
#' --|--------------------|-------------|
|
||||
#' 1 | Organisation XYZ | mo |
|
||||
#' 2 | lab_mo_ecoli | B_ESCHR_COL |
|
||||
#' 3 | lab_mo_kpneumoniae | B_KLBSL_PNE |
|
||||
#' 4 | | |
|
||||
#' }
|
||||
#'
|
||||
#' We save it as \code{'home/me/ourcodes.xlsx'}. Now we have to set it as a source:
|
||||
#' \preformatted{
|
||||
#' set_mo_source("home/me/ourcodes.xlsx")
|
||||
#' # Created mo_source file '~/.mo_source.rds' from 'home/me/ourcodes.xlsx'.
|
||||
#' }
|
||||
#'
|
||||
#' It has now created a file "~/.mo_source.rds" with the contents of our Excel file, but only the first column with foreign values and the 'mo' column will be kept.
|
||||
#'
|
||||
#' And now we can use it in our functions:
|
||||
#' \preformatted{
|
||||
#' as.mo("lab_mo_ecoli")
|
||||
#' [1] B_ESCHR_COL
|
||||
#'
|
||||
#' mo_genus("lab_mo_kpneumoniae")
|
||||
#' [1] "Klebsiella"
|
||||
#'
|
||||
#' # other input values still work too
|
||||
#' as.mo(c("Escherichia coli", "E. coli", "lab_mo_ecoli"))
|
||||
#' [1] B_ESCHR_COL B_ESCHR_COL B_ESCHR_COL
|
||||
#' }
|
||||
#'
|
||||
#' If we edit the Excel file to, let's say, this:
|
||||
#' \preformatted{
|
||||
#' | A | B |
|
||||
#' --|--------------------|-------------|
|
||||
#' 1 | Organisation XYZ | mo |
|
||||
#' 2 | lab_mo_ecoli | B_ESCHR_COL |
|
||||
#' 3 | lab_mo_kpneumoniae | B_KLBSL_PNE |
|
||||
#' 4 | lab_Staph_aureus | B_STPHY_AUR |
|
||||
#' 5 | | |
|
||||
#' }
|
||||
#'
|
||||
#' ...any new usage of an MO function in this package will update your data:
|
||||
#' \preformatted{
|
||||
#' as.mo("lab_mo_ecoli")
|
||||
#' # Updated mo_source file '~/.mo_source.rds' from 'home/me/ourcodes.xlsx'.
|
||||
#' [1] B_ESCHR_COL
|
||||
#'
|
||||
#' mo_genus("lab_Staph_aureus")
|
||||
#' [1] "Staphylococcus"
|
||||
#' }
|
||||
#'
|
||||
#' To remove the reference completely, just use any of these:
|
||||
#' \preformatted{
|
||||
#' set_mo_source("")
|
||||
#' set_mo_source(NULL)
|
||||
#' # Removed mo_source file '~/.mo_source.rds'.
|
||||
#' }
|
||||
#' @importFrom dplyr select everything
|
||||
#' @export
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
set_mo_source <- function(path) {
|
||||
|
||||
file_location <- path.expand("~/mo_source.rds")
|
||||
|
||||
if (!is.character(path) | length(path) > 1) {
|
||||
stop("`path` must be a character of length 1.")
|
||||
}
|
||||
|
||||
if (path %in% c(NULL, "")) {
|
||||
options(mo_source = NULL)
|
||||
options(mo_source_timestamp = NULL)
|
||||
if (file.exists(file_location)) {
|
||||
unlink(file_location)
|
||||
message("Removed mo_source file '", file_location, "'.")
|
||||
}
|
||||
return(invisible())
|
||||
}
|
||||
|
||||
if (!file.exists(path)) {
|
||||
stop("File not found: ", path)
|
||||
}
|
||||
|
||||
if (path %like% "[.]rds$") {
|
||||
df <- readRDS(path)
|
||||
|
||||
} else if (path %like% "[.]xlsx?$") {
|
||||
# is Excel file (old or new)
|
||||
if (!"readxl" %in% utils::installed.packages()) {
|
||||
stop("Install the 'readxl' package first.")
|
||||
}
|
||||
df <- readxl::read_excel(path)
|
||||
|
||||
} else if (path %like% "[.]tsv$") {
|
||||
df <- utils::read.table(header = TRUE, sep = "\t", stringsAsFactors = FALSE)
|
||||
|
||||
} else {
|
||||
# try comma first
|
||||
try(
|
||||
df <- utils::read.table(header = TRUE, sep = ",", stringsAsFactors = FALSE),
|
||||
silent = TRUE)
|
||||
if (!mo_source_isvalid(df)) {
|
||||
# try tab
|
||||
try(
|
||||
df <- utils::read.table(header = TRUE, sep = "\t", stringsAsFactors = FALSE),
|
||||
silent = TRUE)
|
||||
}
|
||||
if (!mo_source_isvalid(df)) {
|
||||
# try pipe
|
||||
try(
|
||||
df <- utils::read.table(header = TRUE, sep = "|", stringsAsFactors = FALSE),
|
||||
silent = TRUE)
|
||||
}
|
||||
}
|
||||
|
||||
if (!mo_source_isvalid(df)) {
|
||||
stop("File must contain a column with self-defined values and a reference column `mo` with valid values from the `microorganisms` data set.")
|
||||
}
|
||||
|
||||
df <- df %>% filter(!is.na(mo))
|
||||
|
||||
# keep only first two columns, second must be mo
|
||||
if (colnames(df)[1] == "mo") {
|
||||
df <- df[, c(2, 1)]
|
||||
} else {
|
||||
df <- df[, c(1, 2)]
|
||||
}
|
||||
|
||||
df <- as.data.frame(df, stringAsFactors = FALSE)
|
||||
|
||||
# success
|
||||
if (file.exists(file_location)) {
|
||||
action <- "Updated"
|
||||
} else {
|
||||
action <- "Created"
|
||||
}
|
||||
saveRDS(df, file_location)
|
||||
options(mo_source = path)
|
||||
options(mo_source_timestamp = as.character(file.info(path)$mtime))
|
||||
message(action, " mo_source file '", file_location, "' from '", path, "'.")
|
||||
}
|
||||
|
||||
#' @rdname mo_source
|
||||
#' @export
|
||||
get_mo_source <- function() {
|
||||
if (is.null(getOption("mo_source", NULL))) {
|
||||
NULL
|
||||
} else {
|
||||
old_time <- as.POSIXct(getOption("mo_source_timestamp"))
|
||||
new_time <- as.POSIXct(as.character(file.info(getOption("mo_source", ""))$mtime))
|
||||
|
||||
if (is.na(new_time)) {
|
||||
# source file was deleted, remove reference too
|
||||
set_mo_source("")
|
||||
return(NULL)
|
||||
}
|
||||
if (new_time != old_time) {
|
||||
# set updated source
|
||||
set_mo_source(getOption("mo_source"))
|
||||
}
|
||||
file_location <- path.expand("~/mo_source.rds")
|
||||
readRDS(file_location)
|
||||
}
|
||||
}
|
||||
|
||||
mo_source_isvalid <- function(x) {
|
||||
if (deparse(substitute(x)) == "get_mo_source()") {
|
||||
return(TRUE)
|
||||
}
|
||||
if (identical(x, get_mo_source())) {
|
||||
return(TRUE)
|
||||
}
|
||||
if (is.null(x)) {
|
||||
return(TRUE)
|
||||
}
|
||||
if (!is.data.frame(x)) {
|
||||
return(FALSE)
|
||||
}
|
||||
if (!"mo" %in% colnames(x)) {
|
||||
return(FALSE)
|
||||
}
|
||||
all(x$mo %in% c("", AMR::microorganisms$mo))
|
||||
}
|
||||
@@ -1,42 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Symbol of a p value
|
||||
#'
|
||||
#' Return the symbol related to the p value: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1. Values above \code{p = 1} will return \code{NA}.
|
||||
#' @param p p value
|
||||
#' @param emptychar text to show when \code{p > 0.1}
|
||||
#' @return Text
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @export
|
||||
p_symbol <- function(p, emptychar = " ") {
|
||||
|
||||
p <- as.double(p)
|
||||
s <- rep(NA_character_, length(p))
|
||||
|
||||
s[p <= 1] <- emptychar
|
||||
s[p <= 0.100] <- "."
|
||||
s[p <= 0.050] <- "*"
|
||||
s[p <= 0.010] <- "**"
|
||||
s[p <= 0.001] <- "***"
|
||||
|
||||
s
|
||||
}
|
||||
-267
@@ -1,267 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Calculate resistance of isolates
|
||||
#'
|
||||
#' @description These functions can be used to calculate the (co-)resistance of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in \code{dplyr}s \code{\link[dplyr]{summarise}} and support grouped variables, see \emph{Examples}.
|
||||
#'
|
||||
#' \code{portion_R} and \code{portion_IR} can be used to calculate resistance, \code{portion_S} and \code{portion_SI} can be used to calculate susceptibility.\cr
|
||||
#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with \code{\link{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 \code{minimum} will return \code{NA} with a warning. The default number of \code{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 \code{0.123456} will then be returned as \code{"12.3\%"}.
|
||||
#' @param only_all_tested (for combination therapies, i.e. using more than one variable for \code{...}) a logical to indicate that isolates must be tested for all antibiotics, see section \emph{Combination therapy} below
|
||||
#' @param data a \code{data.frame} containing columns with class \code{rsi} (see \code{\link{as.rsi}})
|
||||
#' @param translate_ab a column name of the \code{\link{antibiotics}} data set to translate the antibiotic abbreviations to, using \code{\link{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 parameter \code{combine_IR}, but this now follows the redefinition by EUCAST about the interpretion of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is \code{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 parameter \code{combine_SI}.
|
||||
#' @inheritSection as.rsi Interpretation of S, I and R
|
||||
#' @details \strong{Remember that you should filter your table to let it contain only first isolates!} This is needed to exclude duplicates and to reduce selection bias. Use \code{\link{first_isolate}} to determine them in your data set.
|
||||
#'
|
||||
#' These functions are not meant to count isolates, but to calculate the portion of resistance/susceptibility. Use the \code{\link[AMR]{count}} functions to count isolates. The function \code{portion_SI()} is essentially equal to \code{count_SI() / count_all()}. \emph{Low counts can infuence the outcome - the \code{portion} functions may camouflage this, since they only return the portion (albeit being dependent on the \code{minimum} parameter).}
|
||||
#'
|
||||
#' The function \code{portion_df} takes any variable from \code{data} that has an \code{"rsi"} class (created with \code{\link{as.rsi}}) and calculates the portions R, I and S. The resulting \emph{tidy data} (see Source) \code{data.frame} will have three rows (S/I/R) and a column for each group and each variable with class \code{"rsi"}.
|
||||
#'
|
||||
#' The function \code{rsi_df} works exactly like \code{portion_df}, but adds the number of isolates.
|
||||
#' @section Combination therapy:
|
||||
#' When using more than one variable for \code{...} (= combination therapy)), use \code{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, Antibiotic A and Antibiotic B, about how \code{portion_SI} works to calculate the \%SI:
|
||||
#'
|
||||
#' \preformatted{
|
||||
#' --------------------------------------------------------------------
|
||||
#' 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 \code{only_all_tested = TRUE} applies that:
|
||||
#' \preformatted{
|
||||
#' count_S() + count_I() + count_R() == count_all()
|
||||
#' portion_S() + portion_I() + portion_R() == 1
|
||||
#' }
|
||||
#' and that, in combination therapies, for \code{only_all_tested = FALSE} applies that:
|
||||
#' \preformatted{
|
||||
#' count_S() + count_I() + count_R() >= count_all()
|
||||
#' portion_S() + portion_I() + portion_R() >= 1
|
||||
#' }
|
||||
#'
|
||||
#' Using \code{only_all_tested} has no impact when only using one antibiotic as input.
|
||||
#' @source \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
|
||||
#'
|
||||
#' Wickham H. \strong{Tidy Data.} The Journal of Statistical Software, vol. 59, 2014. \url{http://vita.had.co.nz/papers/tidy-data.html}
|
||||
#' @seealso \code{\link[AMR]{count}_*} to count resistant and susceptible isolates.
|
||||
#' @keywords resistance susceptibility rsi_df rsi antibiotics isolate isolates
|
||||
#' @return Double or, when \code{as_percent = TRUE}, a character.
|
||||
#' @rdname portion
|
||||
#' @name portion
|
||||
#' @export
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' # example_isolates is a data set available in the AMR package.
|
||||
#' ?example_isolates
|
||||
#'
|
||||
#' # Calculate resistance
|
||||
#' portion_R(example_isolates$AMX)
|
||||
#' portion_IR(example_isolates$AMX)
|
||||
#'
|
||||
#' # Or susceptibility
|
||||
#' portion_S(example_isolates$AMX)
|
||||
#' portion_SI(example_isolates$AMX)
|
||||
#'
|
||||
|
||||
#' # Do the above with pipes:
|
||||
#' library(dplyr)
|
||||
#' example_isolates %>% portion_R(AMX)
|
||||
#' example_isolates %>% portion_IR(AMX)
|
||||
#' example_isolates %>% portion_S(AMX)
|
||||
#' example_isolates %>% portion_SI(AMX)
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(p = portion_SI(CIP),
|
||||
#' n = n_rsi(CIP)) # n_rsi works like n_distinct in dplyr
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(R = portion_R(CIP, as_percent = TRUE),
|
||||
#' I = portion_I(CIP, as_percent = TRUE),
|
||||
#' S = portion_S(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 %>% portion_SI(AMC) # %SI = 76.3%
|
||||
#' example_isolates %>% count_all(AMC) # n = 1879
|
||||
#'
|
||||
#' example_isolates %>% portion_SI(GEN) # %SI = 75.4%
|
||||
#' example_isolates %>% count_all(GEN) # n = 1855
|
||||
#'
|
||||
#' example_isolates %>% portion_SI(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_SI(AMC, GEN),
|
||||
#' denominator = count_all(AMC, GEN),
|
||||
#' portion = portion_SI(AMC, GEN))
|
||||
#' # numerator denominator portion
|
||||
#' # 1764 1936 0.9408
|
||||
#' example_isolates %>%
|
||||
#' summarise(numerator = count_SI(AMC, GEN, only_all_tested = TRUE),
|
||||
#' denominator = count_all(AMC, GEN, only_all_tested = TRUE),
|
||||
#' portion = portion_SI(AMC, GEN, only_all_tested = TRUE))
|
||||
#' # numerator denominator portion
|
||||
#' # 1687 1798 0.9383
|
||||
#'
|
||||
#'
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(cipro_p = portion_SI(CIP, as_percent = TRUE),
|
||||
#' cipro_n = count_all(CIP),
|
||||
#' genta_p = portion_SI(GEN, as_percent = TRUE),
|
||||
#' genta_n = count_all(GEN),
|
||||
#' combination_p = portion_SI(CIP, GEN, as_percent = TRUE),
|
||||
#' combination_n = count_all(CIP, GEN))
|
||||
#'
|
||||
#' # Get portions S/I/R immediately of all rsi columns
|
||||
#' example_isolates %>%
|
||||
#' select(AMX, CIP) %>%
|
||||
#' portion_df(translate = FALSE)
|
||||
#'
|
||||
#' # It also supports grouping variables
|
||||
#' example_isolates %>%
|
||||
#' select(hospital_id, AMX, CIP) %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' portion_df(translate = FALSE)
|
||||
#'
|
||||
#'
|
||||
#' \dontrun{
|
||||
#'
|
||||
#' # calculate current empiric combination therapy of Helicobacter gastritis:
|
||||
#' my_table %>%
|
||||
#' filter(first_isolate == TRUE,
|
||||
#' genus == "Helicobacter") %>%
|
||||
#' summarise(p = portion_S(AMX, MTR), # amoxicillin with metronidazole
|
||||
#' n = count_all(AMX, MTR))
|
||||
#' }
|
||||
portion_R <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname portion
|
||||
#' @export
|
||||
portion_IR <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = c("I", "R"),
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname portion
|
||||
#' @export
|
||||
portion_I <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = "I",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname portion
|
||||
#' @export
|
||||
portion_SI <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname portion
|
||||
#' @export
|
||||
portion_S <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = "S",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE)
|
||||
}
|
||||
|
||||
#' @rdname portion
|
||||
#' @importFrom dplyr %>% select_if bind_rows summarise_if mutate group_vars select everything
|
||||
#' @export
|
||||
portion_df <- function(data,
|
||||
translate_ab = "name",
|
||||
language = get_locale(),
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE) {
|
||||
|
||||
rsi_calc_df(type = "portion",
|
||||
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))
|
||||
}
|
||||
-175
@@ -1,175 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Read data from 4D database
|
||||
#'
|
||||
#' This function is only useful for the MMB department of the UMCG. Use this function to \strong{import data by just defining the \code{file} parameter}. It will automatically transform birth dates and calculate patients age, translate the column names to English, transform the MO codes with \code{\link{as.mo}} and transform all antimicrobial columns with \code{\link{as.rsi}}.
|
||||
#' @inheritParams utils::read.table
|
||||
#' @param info a logical to indicate whether info about the import should be printed, defaults to \code{TRUE} in interactive sessions
|
||||
#' @details Column names will be transformed, but the original column names are set as a "label" attribute and can be seen in e.g. RStudio Viewer.
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @export
|
||||
read.4D <- function(file,
|
||||
info = interactive(),
|
||||
header = TRUE,
|
||||
row.names = NULL,
|
||||
sep = "\t",
|
||||
quote = "\"'",
|
||||
dec = ",",
|
||||
na.strings = c("NA", "", "."),
|
||||
skip = 2,
|
||||
check.names = TRUE,
|
||||
strip.white = TRUE,
|
||||
fill = TRUE,
|
||||
blank.lines.skip = TRUE,
|
||||
stringsAsFactors = FALSE,
|
||||
fileEncoding = "UTF-8",
|
||||
encoding = "UTF-8") {
|
||||
|
||||
if (info == TRUE) {
|
||||
message("Importing ", file, "... ", appendLF = FALSE)
|
||||
}
|
||||
data_4D <- utils::read.table(file = file,
|
||||
row.names = row.names,
|
||||
header = header,
|
||||
sep = sep,
|
||||
quote = quote,
|
||||
dec = dec,
|
||||
na.strings = na.strings,
|
||||
skip = skip,
|
||||
check.names = check.names,
|
||||
strip.white = strip.white,
|
||||
fill = fill,
|
||||
blank.lines.skip = blank.lines.skip,
|
||||
stringsAsFactors = stringsAsFactors,
|
||||
fileEncoding = fileEncoding,
|
||||
encoding = encoding)
|
||||
|
||||
# helper function for dates
|
||||
to_date_4D <- function(x) {
|
||||
date_regular <- as.Date(x, format = "%d-%m-%y")
|
||||
posixlt <- as.POSIXlt(date_regular)
|
||||
# born after today will be born 100 years ago
|
||||
# based on https://stackoverflow.com/a/3312971/4575331
|
||||
posixlt[date_regular > Sys.Date() & !is.na(posixlt)]$year <- posixlt[date_regular > Sys.Date() & !is.na(posixlt)]$year - 100
|
||||
as.Date(posixlt)
|
||||
}
|
||||
|
||||
if (info == TRUE) {
|
||||
message("OK\nTransforming column names... ", appendLF = FALSE)
|
||||
}
|
||||
if ("row.names" %in% colnames(data_4D) & all(is.na(data_4D[, ncol(data_4D)]))) {
|
||||
# remove first column name "row.names" and remove last empty column
|
||||
colnames(data_4D) <- c(colnames(data_4D)[2:ncol(data_4D)], "_skip_last")
|
||||
data_4D <- data_4D[, -ncol(data_4D)]
|
||||
}
|
||||
|
||||
colnames(data_4D) <- tolower(colnames(data_4D))
|
||||
if (all(c("afnamedat", "gebdatum") %in% colnames(data_4D))) {
|
||||
# add age
|
||||
data_4D$age <- NA_integer_
|
||||
}
|
||||
cols_wanted <- c("patientnr", "gebdatum", "age", "mv", "monsternr", "afnamedat", "bepaling",
|
||||
"afd.", "spec", "mat", "matbijz.", "mocode",
|
||||
"amfo", "amox", "anid", "azit", "casp", "cecl", "cefe", "cfcl",
|
||||
"cfot", "cfox", "cfta", "cftr", "cfur", "chlo", "cipr", "clin",
|
||||
"cocl", "ctta", "dapt", "doxy", "eryt", "fluo", "fluz", "fosf",
|
||||
"fusi", "gehi", "gent", "imip", "kana", "levo", "line", "mero",
|
||||
"metr", "mico", "mino", "moxi", "mupi", "nali", "nitr", "norf",
|
||||
"oxac", "peni", "pipe", "pita", "poly", "posa", "quda", "rifa",
|
||||
"spat", "teic", "tige", "tobr", "trim", "trsu", "vana", "vanb",
|
||||
"vanc", "vori")
|
||||
# this ones actually exist
|
||||
cols_wanted <- cols_wanted[cols_wanted %in% colnames(data_4D)]
|
||||
# order of columns
|
||||
data_4D <- data_4D[, cols_wanted]
|
||||
|
||||
# backup original column names
|
||||
colnames.bak <- toupper(colnames(data_4D))
|
||||
colnames.bak[colnames.bak == "AGE"] <- NA_character_
|
||||
|
||||
# rename of columns
|
||||
colnames(data_4D) <- gsub("patientnr", "patient_id", colnames(data_4D), fixed = TRUE)
|
||||
colnames(data_4D) <- gsub("gebdatum", "date_birth", colnames(data_4D), fixed = TRUE)
|
||||
colnames(data_4D) <- gsub("mv", "gender", colnames(data_4D), fixed = TRUE)
|
||||
colnames(data_4D) <- gsub("monsternr", "sample_id", colnames(data_4D), fixed = TRUE)
|
||||
colnames(data_4D) <- gsub("afnamedat", "date_received", colnames(data_4D), fixed = TRUE)
|
||||
colnames(data_4D) <- gsub("bepaling", "sample_test", colnames(data_4D), fixed = TRUE)
|
||||
colnames(data_4D) <- gsub("afd.", "department", colnames(data_4D), fixed = TRUE)
|
||||
colnames(data_4D) <- gsub("spec", "specialty", colnames(data_4D), fixed = TRUE)
|
||||
colnames(data_4D) <- gsub("matbijz.", "specimen_type", colnames(data_4D), fixed = TRUE)
|
||||
colnames(data_4D) <- gsub("mat", "specimen_group", colnames(data_4D), fixed = TRUE)
|
||||
colnames(data_4D) <- gsub("mocode", "mo", colnames(data_4D), fixed = TRUE)
|
||||
|
||||
if (info == TRUE) {
|
||||
message("OK\nTransforming dates and age... ", appendLF = FALSE)
|
||||
}
|
||||
if ("date_birth" %in% colnames(data_4D)) {
|
||||
data_4D$date_birth <- to_date_4D(data_4D$date_birth)
|
||||
}
|
||||
if ("date_received" %in% colnames(data_4D)) {
|
||||
data_4D$date_received <- to_date_4D(data_4D$date_received)
|
||||
}
|
||||
if ("age" %in% colnames(data_4D)) {
|
||||
data_4D$age <- age(data_4D$date_birth, data_4D$date_received)
|
||||
}
|
||||
if ("gender" %in% colnames(data_4D)) {
|
||||
data_4D$gender[data_4D$gender == "V"] <- "F"
|
||||
}
|
||||
|
||||
if (info == TRUE) {
|
||||
message("OK\nTransforming MO codes... ", appendLF = FALSE)
|
||||
}
|
||||
if ("mo" %in% colnames(data_4D)) {
|
||||
data_4D$mo <- as.mo(data_4D$mo)
|
||||
# column right of mo is:
|
||||
drug1 <- colnames(data_4D)[grep("^mo$", colnames(data_4D)) + 1]
|
||||
if (!is.na(drug1)) {
|
||||
# and last is:
|
||||
drug_last <- colnames(data_4D)[length(data_4D)]
|
||||
# transform those to rsi:
|
||||
data_4D <- suppressWarnings(mutate_at(data_4D, vars(drug1:drug_last), as.rsi))
|
||||
}
|
||||
}
|
||||
|
||||
# set original column names as label (can be seen in RStudio Viewer)
|
||||
if (info == TRUE) {
|
||||
message("OK\nSetting original column names as label... ", appendLF = FALSE)
|
||||
}
|
||||
for (i in seq_len(ncol(data_4D))) {
|
||||
if (!is.na(colnames.bak[i])) {
|
||||
attr(data_4D[, i], "label") <- colnames.bak[i]
|
||||
}
|
||||
}
|
||||
|
||||
if (info == TRUE) {
|
||||
message("OK\nSetting query as label to data.frame... ", appendLF = FALSE)
|
||||
}
|
||||
qry <- readLines(con <- file(file, open = "r"))[1]
|
||||
close(con)
|
||||
attr(data_4D, "label") <- qry
|
||||
|
||||
if (info == TRUE) {
|
||||
message("OK")
|
||||
}
|
||||
|
||||
data_4D
|
||||
}
|
||||
@@ -1,406 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.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 \code{se_min} and \code{se_max}. See Examples for a real live example.
|
||||
#' @param col_ab column name of \code{x} with antimicrobial interpretations (\code{R}, \code{I} and \code{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 \code{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 \code{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 \code{\link{glm}(..., family = \link{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 \code{I} should be treated as \code{S} (will otherwise be treated as \code{R})
|
||||
#' @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 \code{NA}.
|
||||
#' @param info a logical to indicate whether textual analysis should be printed with the name and \code{\link{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 ... parameters passed on to functions
|
||||
#' @inheritParams first_isolate
|
||||
#' @inheritParams graphics::plot
|
||||
#' @details Valid options for the statistical model are:
|
||||
#' \itemize{
|
||||
#' \item{\code{"binomial"} or \code{"binom"} or \code{"logit"}: a generalised linear regression model with binomial distribution}
|
||||
#' \item{\code{"loglin"} or \code{"poisson"}: a generalised log-linear regression model with poisson distribution}
|
||||
#' \item{\code{"lin"} or \code{"linear"}: a linear regression model}
|
||||
#' }
|
||||
#' @return \code{data.frame} with extra class \code{"resistance_predict"} with columns:
|
||||
#' \itemize{
|
||||
#' \item{\code{year}}
|
||||
#' \item{\code{value}, the same as \code{estimated} when \code{preserve_measurements = FALSE}, and a combination of \code{observed} and \code{estimated} otherwise}
|
||||
#' \item{\code{se_min}, the lower bound of the standard error with a minimum of \code{0} (so the standard error will never go below 0\%)}
|
||||
#' \item{\code{se_max} the upper bound of the standard error with a maximum of \code{1} (so the standard error will never go above 100\%)}
|
||||
#' \item{\code{observations}, the total number of available observations in that year, i.e. S + I + R}
|
||||
#' \item{\code{observed}, the original observed resistant percentages}
|
||||
#' \item{\code{estimated}, the estimated resistant percentages, calculated by the model}
|
||||
#' }
|
||||
#' Furthermore, the model itself is available as an attribute: \code{attributes(x)$model}, see Examples.
|
||||
#' @seealso The \code{\link{portion}} function to calculate resistance, \cr \code{\link{lm}} \code{\link{glm}}
|
||||
#' @rdname resistance_predict
|
||||
#' @export
|
||||
#' @importFrom stats predict glm lm
|
||||
#' @importFrom dplyr %>% pull mutate mutate_at n group_by_at summarise filter filter_at all_vars n_distinct arrange case_when n_groups transmute ungroup
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' x <- resistance_predict(example_isolates, col_ab = "AMX", year_min = 2010, model = "binomial")
|
||||
#' plot(x)
|
||||
#' ggplot_rsi_predict(x)
|
||||
#'
|
||||
#' # use dplyr so you can actually read it:
|
||||
#' library(dplyr)
|
||||
#' x <- example_isolates %>%
|
||||
#' filter_first_isolate() %>%
|
||||
#' filter(mo_genus(mo) == "Staphylococcus") %>%
|
||||
#' resistance_predict("PEN", model = "binomial")
|
||||
#' plot(x)
|
||||
#'
|
||||
#'
|
||||
#' # get the model from the object
|
||||
#' mymodel <- attributes(x)$model
|
||||
#' summary(mymodel)
|
||||
#'
|
||||
#'
|
||||
#' # create nice plots with ggplot2 yourself
|
||||
#' if (!require(ggplot2)) {
|
||||
#'
|
||||
#' data <- example_isolates %>%
|
||||
#' filter(mo == as.mo("E. coli")) %>%
|
||||
#' resistance_predict(col_ab = "AMX",
|
||||
#' col_date = "date",
|
||||
#' model = "binomial",
|
||||
#' info = FALSE,
|
||||
#' minimum = 15)
|
||||
#'
|
||||
#' ggplot(data,
|
||||
#' aes(x = year)) +
|
||||
#' geom_col(aes(y = value),
|
||||
#' fill = "grey75") +
|
||||
#' geom_errorbar(aes(ymin = se_min,
|
||||
#' ymax = se_max),
|
||||
#' colour = "grey50") +
|
||||
#' scale_y_continuous(limits = c(0, 1),
|
||||
#' breaks = seq(0, 1, 0.1),
|
||||
#' labels = paste0(seq(0, 100, 10), "%")) +
|
||||
#' labs(title = expression(paste("Forecast of amoxicillin resistance in ",
|
||||
#' italic("E. coli"))),
|
||||
#' y = "%IR",
|
||||
#' x = "Year") +
|
||||
#' theme_minimal(base_size = 13)
|
||||
#' }
|
||||
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 = TRUE,
|
||||
...) {
|
||||
|
||||
if (nrow(x) == 0) {
|
||||
stop("This table does not contain any observations.")
|
||||
}
|
||||
|
||||
if (is.null(model)) {
|
||||
stop('Choose a regression model with the `model` parameter, e.g. resistance_predict(..., model = "binomial").')
|
||||
}
|
||||
|
||||
if (!col_ab %in% colnames(x)) {
|
||||
stop("Column ", col_ab, " not found.")
|
||||
}
|
||||
|
||||
dots <- unlist(list(...))
|
||||
if (length(dots) != 0) {
|
||||
# backwards compatibility with old parameters
|
||||
dots.names <- dots %>% names()
|
||||
if ("tbl" %in% dots.names) {
|
||||
x <- dots[which(dots.names == "tbl")]
|
||||
}
|
||||
if ("I_as_R" %in% dots.names) {
|
||||
warning("`I_as_R is deprecated - use I_as_S instead.", call. = FALSE)
|
||||
}
|
||||
}
|
||||
|
||||
# -- date
|
||||
if (is.null(col_date)) {
|
||||
col_date <- search_type_in_df(x = x, type = "date")
|
||||
}
|
||||
if (is.null(col_date)) {
|
||||
stop("`col_date` must be set.", call. = FALSE)
|
||||
}
|
||||
|
||||
if (!col_date %in% colnames(x)) {
|
||||
stop("Column ", col_date, " not found.")
|
||||
}
|
||||
|
||||
if (n_groups(x) > 1) {
|
||||
# no grouped tibbles please, mutate will throw errors
|
||||
x <- base::as.data.frame(x, stringsAsFactors = FALSE)
|
||||
}
|
||||
|
||||
year <- function(x) {
|
||||
if (all(grepl("^[0-9]{4}$", x))) {
|
||||
x
|
||||
} else {
|
||||
as.integer(format(as.Date(x), "%Y"))
|
||||
}
|
||||
}
|
||||
|
||||
df <- x %>%
|
||||
mutate_at(col_ab, as.rsi) %>%
|
||||
mutate_at(col_ab, droplevels)
|
||||
if (I_as_S == TRUE) {
|
||||
df <- df %>%
|
||||
mutate_at(col_ab, ~gsub("I", "S", .))
|
||||
} else {
|
||||
# then I as R
|
||||
df <- df %>%
|
||||
mutate_at(col_ab, ~gsub("I", "R", .))
|
||||
}
|
||||
df <- df %>%
|
||||
filter_at(col_ab, all_vars(!is.na(.))) %>%
|
||||
mutate(year = year(pull(., col_date))) %>%
|
||||
group_by_at(c("year", col_ab)) %>%
|
||||
summarise(n())
|
||||
|
||||
if (df %>% pull(col_ab) %>% n_distinct(na.rm = TRUE) < 2) {
|
||||
stop("No variety in antimicrobial interpretations - all isolates are '",
|
||||
df %>% pull(col_ab) %>% unique(), "'.",
|
||||
call. = FALSE)
|
||||
}
|
||||
|
||||
colnames(df) <- c("year", "antibiotic", "observations")
|
||||
df <- df %>%
|
||||
filter(!is.na(antibiotic)) %>%
|
||||
tidyr::spread(antibiotic, observations, fill = 0) %>%
|
||||
filter((R + S) >= minimum)
|
||||
df_matrix <- df %>%
|
||||
ungroup() %>%
|
||||
select(R, S) %>%
|
||||
as.matrix()
|
||||
|
||||
if (NROW(df) == 0) {
|
||||
stop("There are no observations.")
|
||||
}
|
||||
|
||||
year_lowest <- min(df$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,
|
||||
stringsAsFactors = FALSE) %>%
|
||||
|
||||
mutate(se_min = value - se,
|
||||
se_max = value + se)
|
||||
|
||||
if (model == "poisson") {
|
||||
df_prediction <- df_prediction %>%
|
||||
mutate(value = value %>%
|
||||
format(scientific = FALSE) %>%
|
||||
as.integer(),
|
||||
se_min = as.integer(se_min),
|
||||
se_max = as.integer(se_max))
|
||||
} else {
|
||||
df_prediction <- df_prediction %>%
|
||||
# se_max not above 1
|
||||
mutate(se_max = ifelse(se_max > 1, 1, se_max))
|
||||
}
|
||||
df_prediction <- df_prediction %>%
|
||||
# se_min not below 0
|
||||
mutate(se_min = ifelse(se_min < 0, 0, se_min))
|
||||
|
||||
df_observations <- df %>%
|
||||
ungroup() %>%
|
||||
transmute(year,
|
||||
observations = R + S,
|
||||
observed = R / (R + S))
|
||||
df_prediction <- df_prediction %>%
|
||||
left_join(df_observations, by = "year") %>%
|
||||
mutate(estimated = value)
|
||||
|
||||
if (preserve_measurements == TRUE) {
|
||||
# replace estimated data by observed data
|
||||
df_prediction <- df_prediction %>%
|
||||
mutate(value = ifelse(!is.na(observed), observed, value),
|
||||
se_min = ifelse(!is.na(observed), NA, se_min),
|
||||
se_max = ifelse(!is.na(observed), NA, se_max))
|
||||
}
|
||||
|
||||
df_prediction <- df_prediction %>%
|
||||
mutate(value = case_when(value > 1 ~ 1,
|
||||
value < 0 ~ 0,
|
||||
TRUE ~ value)) %>%
|
||||
arrange(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
|
||||
|
||||
#' @exportMethod plot.mic
|
||||
#' @export
|
||||
#' @importFrom dplyr filter
|
||||
#' @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, ")")
|
||||
|
||||
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$se_max,
|
||||
length = 0.05, angle = 90, code = 3, lwd = 1.5)
|
||||
|
||||
# overlay grey points for prediction
|
||||
points(x = filter(x, is.na(observations))$year,
|
||||
y = filter(x, is.na(observations))$value,
|
||||
pch = 19,
|
||||
col = "grey40")
|
||||
}
|
||||
|
||||
#' @rdname resistance_predict
|
||||
#' @importFrom dplyr filter
|
||||
#' @export
|
||||
ggplot_rsi_predict <- function(x,
|
||||
main = paste("Resistance Prediction of", x_name),
|
||||
ribbon = TRUE,
|
||||
...) {
|
||||
if (!"resistance_predict" %in% class(x)) {
|
||||
stop("`x` must be a resistance prediction model created with resistance_predict().")
|
||||
}
|
||||
|
||||
x_name <- paste0(ab_name(attributes(x)$ab), " (", attributes(x)$ab, ")")
|
||||
|
||||
if (attributes(x)$I_as_S == TRUE) {
|
||||
ylab <- "%R"
|
||||
} else {
|
||||
ylab <- "%IR"
|
||||
}
|
||||
|
||||
p <- ggplot2::ggplot(x, ggplot2::aes(x = year, y = value)) +
|
||||
ggplot2::geom_point(data = filter(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 = filter(x, is.na(observations)),
|
||||
size = 2,
|
||||
colour = "grey40")
|
||||
p
|
||||
}
|
||||
@@ -1,491 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Class 'rsi'
|
||||
#'
|
||||
#' Interpret MIC values according to EUCAST or CLSI, or clean up existing RSI values. This transforms the input to a new class \code{rsi}, which is an ordered factor with levels \code{S < I < R}. Invalid antimicrobial interpretations will be translated as \code{NA} with a warning.
|
||||
#' @rdname as.rsi
|
||||
#' @param x vector of values (for class \code{mic}: an MIC value in mg/L, for class \code{disk}: a disk diffusion radius in millimeters)
|
||||
#' @param mo a microorganism code, generated with \code{\link{as.mo}}
|
||||
#' @param ab an antimicrobial code, generated with \code{\link{as.ab}}
|
||||
#' @inheritParams first_isolate
|
||||
#' @param guideline defaults to the latest included EUCAST guideline, run \code{unique(AMR::rsi_translation$guideline)} for all options
|
||||
#' @param threshold maximum fraction of invalid antimicrobial interpretations of \code{x}, see Examples
|
||||
#' @param ... parameters passed on to methods
|
||||
#' @details Run \code{unique(AMR::rsi_translation$guideline)} for a list of all supported guidelines.
|
||||
#'
|
||||
#' After using \code{as.rsi}, you can use \code{\link{eucast_rules}} to (1) apply inferred susceptibility and resistance based on results of other antimicrobials and (2) apply intrinsic resistance based on taxonomic properties of a microorganism.
|
||||
#'
|
||||
#' The function \code{is.rsi.eligible} returns \code{TRUE} when a columns contains at most 5\% invalid antimicrobial interpretations (not S and/or I and/or R), and \code{FALSE} otherwise. The threshold of 5\% can be set with the \code{threshold} parameter.
|
||||
#' @section Interpretation of S, I and R:
|
||||
#' In 2019, EUCAST has decided to change the definitions of susceptibility testing categories S, I and R as shown below (\url{http://www.eucast.org/newsiandr/}). Results of several consultations on the new definitions are available on the EUCAST website under "Consultations".
|
||||
#'
|
||||
#' \itemize{
|
||||
#' \item{\strong{S} - }{Susceptible, standard dosing regimen: A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.}
|
||||
#' \item{\strong{I} - }{Susceptible, increased exposure: A microorganism is categorised as "Susceptible, Increased exposure" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.}
|
||||
#' \item{\strong{R} - }{Resistant: A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.}
|
||||
#' }
|
||||
#'
|
||||
#' Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
|
||||
#'
|
||||
#' This AMR package honours this new insight. Use \code{\link{portion_SI}} to determine antimicrobial susceptibility and \code{\link{count_SI}} to count susceptible isolates.
|
||||
#' @return Ordered factor with new class \code{rsi}
|
||||
#' @keywords rsi
|
||||
#' @export
|
||||
#' @importFrom dplyr %>% desc arrange filter
|
||||
#' @seealso \code{\link{as.mic}}
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @examples
|
||||
#' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370)))
|
||||
#' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370), "A", "B", "C"))
|
||||
#' is.rsi(rsi_data)
|
||||
#'
|
||||
#' # this can also coerce combined MIC/RSI values:
|
||||
#' as.rsi("<= 0.002; S") # will return S
|
||||
#'
|
||||
#' # interpret MIC values
|
||||
#' as.rsi(x = as.mic(2),
|
||||
#' mo = as.mo("S. pneumoniae"),
|
||||
#' ab = "AMX",
|
||||
#' guideline = "EUCAST")
|
||||
#' as.rsi(x = as.mic(4),
|
||||
#' mo = as.mo("S. pneumoniae"),
|
||||
#' ab = "AMX",
|
||||
#' guideline = "EUCAST")
|
||||
#'
|
||||
#' plot(rsi_data) # for percentages
|
||||
#' barplot(rsi_data) # for frequencies
|
||||
#'
|
||||
#' library(clean)
|
||||
#' freq(rsi_data) # frequency table with informative header
|
||||
#'
|
||||
#' # using dplyr's mutate
|
||||
#' library(dplyr)
|
||||
#' example_isolates %>%
|
||||
#' mutate_at(vars(PEN:RIF), as.rsi)
|
||||
#'
|
||||
#'
|
||||
#' # fastest way to transform all columns with already valid AB results to class `rsi`:
|
||||
#' example_isolates %>%
|
||||
#' mutate_if(is.rsi.eligible,
|
||||
#' as.rsi)
|
||||
#'
|
||||
#' # default threshold of `is.rsi.eligible` is 5%.
|
||||
#' is.rsi.eligible(WHONET$`First name`) # fails, >80% is invalid
|
||||
#' is.rsi.eligible(WHONET$`First name`, threshold = 0.99) # succeeds
|
||||
as.rsi <- function(x, ...) {
|
||||
UseMethod("as.rsi")
|
||||
}
|
||||
|
||||
#' @export
|
||||
as.rsi.default <- function(x, ...) {
|
||||
if (is.rsi(x)) {
|
||||
x
|
||||
} else if (identical(levels(x), c("S", "I", "R"))) {
|
||||
structure(x, class = c("rsi", "ordered", "factor"))
|
||||
} else {
|
||||
|
||||
x <- x %>% unlist()
|
||||
x.bak <- x
|
||||
|
||||
na_before <- x[is.na(x) | x == ""] %>% length()
|
||||
# remove all spaces
|
||||
x <- gsub(" +", "", x)
|
||||
# remove all MIC-like values: numbers, operators and periods
|
||||
x <- gsub("[0-9.,;:<=>]+", "", x)
|
||||
# remove everything between brackets, and 'high' and 'low'
|
||||
x <- gsub("([(].*[)])", "", x)
|
||||
x <- gsub("(high|low)", "", x, ignore.case = TRUE)
|
||||
# disallow more than 3 characters
|
||||
x[nchar(x) > 3] <- NA
|
||||
# set to capitals
|
||||
x <- toupper(x)
|
||||
# remove all invalid characters
|
||||
x <- gsub("[^RSI]+", "", x)
|
||||
# in cases of "S;S" keep S, but in case of "S;I" make it NA
|
||||
x <- gsub("^S+$", "S", x)
|
||||
x <- gsub("^I+$", "I", x)
|
||||
x <- gsub("^R+$", "R", x)
|
||||
x[!x %in% c("S", "I", "R")] <- NA
|
||||
na_after <- x[is.na(x) | x == ""] %>% length()
|
||||
|
||||
if (!isFALSE(list(...)$warn)) { # so as.rsi(..., warn = FALSE) will never throw a warning
|
||||
if (na_before != na_after) {
|
||||
list_missing <- x.bak[is.na(x) & !is.na(x.bak) & x.bak != ""] %>%
|
||||
unique() %>%
|
||||
sort()
|
||||
list_missing <- paste0('"', list_missing, '"', collapse = ", ")
|
||||
warning(na_after - na_before, " results truncated (",
|
||||
round(((na_after - na_before) / length(x)) * 100),
|
||||
"%) that were invalid antimicrobial interpretations: ",
|
||||
list_missing, call. = FALSE)
|
||||
}
|
||||
}
|
||||
|
||||
structure(.Data = factor(x, levels = c("S", "I", "R"), ordered = TRUE),
|
||||
class = c("rsi", "ordered", "factor"))
|
||||
}
|
||||
}
|
||||
|
||||
input_resembles_mic <- function(x) {
|
||||
mic <- x %>%
|
||||
gsub("[^0-9.,]+", "", .) %>%
|
||||
unique()
|
||||
mic_valid <- suppressWarnings(as.mic(mic))
|
||||
result <- sum(!is.na(mic_valid)) / length(mic)
|
||||
if (is.na(result)) {
|
||||
0
|
||||
} else {
|
||||
result
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname as.rsi
|
||||
#' @importFrom dplyr case_when
|
||||
#' @export
|
||||
as.rsi.mic <- function(x, mo, ab, guideline = "EUCAST", ...) {
|
||||
exec_as.rsi(method = "mic",
|
||||
x = x,
|
||||
mo = mo,
|
||||
ab = ab,
|
||||
guideline = guideline)
|
||||
}
|
||||
|
||||
#' @rdname as.rsi
|
||||
#' @export
|
||||
as.rsi.disk <- function(x, mo, ab, guideline = "EUCAST", ...) {
|
||||
exec_as.rsi(method = "disk",
|
||||
x = x,
|
||||
mo = mo,
|
||||
ab = ab,
|
||||
guideline = guideline)
|
||||
}
|
||||
|
||||
exec_as.rsi <- function(method, x, mo, ab, guideline) {
|
||||
if (method == "mic") {
|
||||
x <- as.mic(x) # when as.rsi.mic is called directly
|
||||
} else if (method == "disk") {
|
||||
x <- as.disk(x) # when as.rsi.disk is called directly
|
||||
}
|
||||
|
||||
mo <- as.mo(mo)
|
||||
ab <- as.ab(ab)
|
||||
|
||||
mo_genus <- as.mo(mo_genus(mo))
|
||||
mo_family <- as.mo(mo_family(mo))
|
||||
mo_order <- as.mo(mo_order(mo))
|
||||
mo_becker <- as.mo(mo, Becker = TRUE)
|
||||
mo_lancefield <- as.mo(mo, Lancefield = TRUE)
|
||||
|
||||
guideline_param <- toupper(guideline)
|
||||
if (guideline_param %in% c("CLSI", "EUCAST")) {
|
||||
guideline_param <- AMR::rsi_translation %>%
|
||||
filter(guideline %like% guideline_param) %>%
|
||||
pull(guideline) %>%
|
||||
sort() %>%
|
||||
rev() %>%
|
||||
.[1]
|
||||
}
|
||||
|
||||
if (!guideline_param %in% AMR::rsi_translation$guideline) {
|
||||
stop(paste0("invalid guideline: '", guideline,
|
||||
"'.\nValid guidelines are: ", paste0("'", rev(sort(unique(AMR::rsi_translation$guideline))), "'", collapse = ", ")),
|
||||
call. = FALSE)
|
||||
}
|
||||
|
||||
new_rsi <- rep(NA_character_, length(x))
|
||||
trans <- AMR::rsi_translation %>%
|
||||
filter(guideline == guideline_param) %>%
|
||||
mutate(lookup = paste(mo, ab))
|
||||
|
||||
lookup_mo <- paste(mo, ab)
|
||||
lookup_genus <- paste(mo_genus, ab)
|
||||
lookup_family <- paste(mo_family, ab)
|
||||
lookup_order <- paste(mo_order, ab)
|
||||
lookup_becker <- paste(mo_becker, ab)
|
||||
lookup_lancefield <- paste(mo_lancefield, ab)
|
||||
|
||||
for (i in seq_len(length(x))) {
|
||||
get_record <- trans %>%
|
||||
filter(lookup %in% c(lookup_mo[i],
|
||||
lookup_genus[i],
|
||||
lookup_family[i],
|
||||
lookup_order[i],
|
||||
lookup_becker[i],
|
||||
lookup_lancefield[i])) %>%
|
||||
# be as specific as possible (i.e. prefer species over genus):
|
||||
arrange(desc(nchar(mo))) %>%
|
||||
.[1L, ]
|
||||
|
||||
if (NROW(get_record) > 0) {
|
||||
if (method == "mic") {
|
||||
new_rsi[i] <- case_when(isTRUE(x[i] <= get_record$S_mic) ~ "S",
|
||||
isTRUE(x[i] >= get_record$R_mic) ~ "R",
|
||||
!is.na(get_record$S_mic) & !is.na(get_record$R_mic) ~ "I",
|
||||
TRUE ~ NA_character_)
|
||||
} else if (method == "disk") {
|
||||
new_rsi[i] <- case_when(isTRUE(x[i] >= get_record$S_disk) ~ "S",
|
||||
isTRUE(x[i] <= get_record$R_disk) ~ "R",
|
||||
!is.na(get_record$S_disk) & !is.na(get_record$R_disk) ~ "I",
|
||||
TRUE ~ NA_character_)
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
structure(.Data = factor(new_rsi, levels = c("S", "I", "R"), ordered = TRUE),
|
||||
class = c("rsi", "ordered", "factor"))
|
||||
}
|
||||
|
||||
#' @rdname as.rsi
|
||||
#' @importFrom crayon red blue
|
||||
#' @export
|
||||
as.rsi.data.frame <- function(x, col_mo = NULL, guideline = "EUCAST", ...) {
|
||||
x <- x
|
||||
|
||||
ab_cols <- colnames(x)[sapply(x, function(y) is.mic(y) | is.disk(y))]
|
||||
if (length(ab_cols) == 0) {
|
||||
stop("No columns with MIC values or disk zones found in this data set. Use as.mic or as.disk to transform antimicrobial columns.", call. = FALSE)
|
||||
}
|
||||
|
||||
# try to find columns based on type
|
||||
# -- mo
|
||||
if (is.null(col_mo)) {
|
||||
col_mo <- search_type_in_df(x = x, type = "mo")
|
||||
}
|
||||
if (is.null(col_mo)) {
|
||||
stop("`col_mo` must be set.", call. = FALSE)
|
||||
}
|
||||
|
||||
# transform all MICs
|
||||
ab_cols <- colnames(x)[sapply(x, is.mic)]
|
||||
if (length(ab_cols) > 0) {
|
||||
for (i in seq_len(length(ab_cols))) {
|
||||
if (is.na(suppressWarnings(as.ab(ab_cols[i])))) {
|
||||
message(red(paste0("Unknown drug: `", bold(ab_cols[i]), "`. Rename this column to a drug name or code, and check the output with as.ab().")))
|
||||
next
|
||||
}
|
||||
message(blue(paste0("Interpreting column `", bold(ab_cols[i]), "` (", ab_name(ab_cols[i], tolower = TRUE), ")...")), appendLF = FALSE)
|
||||
x[, ab_cols[i]] <- exec_as.rsi(method = "mic",
|
||||
x = x %>% pull(ab_cols[i]),
|
||||
mo = x %>% pull(col_mo),
|
||||
ab = as.ab(ab_cols[i]),
|
||||
guideline = guideline)
|
||||
message(blue(" OK."))
|
||||
}
|
||||
}
|
||||
# transform all disks
|
||||
ab_cols <- colnames(x)[sapply(x, is.disk)]
|
||||
if (length(ab_cols) > 0) {
|
||||
for (i in seq_len(length(ab_cols))) {
|
||||
if (is.na(suppressWarnings(as.ab(ab_cols[i])))) {
|
||||
message(red(paste0("Unknown drug: `", bold(ab_cols[i]), "`. Rename this column to a drug name or code, and check the output with as.ab().")))
|
||||
next
|
||||
}
|
||||
message(blue(paste0("Interpreting column `", bold(ab_cols[i]), "` (", ab_name(ab_cols[i], tolower = TRUE), ")...")), appendLF = FALSE)
|
||||
x[, ab_cols[i]] <- exec_as.rsi(method = "disk",
|
||||
x = x %>% pull(ab_cols[i]),
|
||||
mo = x %>% pull(col_mo),
|
||||
ab = as.ab(ab_cols[i]),
|
||||
guideline = guideline)
|
||||
message(blue(" OK."))
|
||||
}
|
||||
}
|
||||
|
||||
x
|
||||
}
|
||||
|
||||
#' @rdname as.rsi
|
||||
#' @export
|
||||
is.rsi <- function(x) {
|
||||
identical(class(x),
|
||||
c("rsi", "ordered", "factor"))
|
||||
}
|
||||
|
||||
#' @rdname as.rsi
|
||||
#' @export
|
||||
is.rsi.eligible <- function(x, threshold = 0.05) {
|
||||
if (NCOL(x) > 1) {
|
||||
stop("`x` must be a one-dimensional vector.")
|
||||
}
|
||||
if (any(c("logical",
|
||||
"numeric",
|
||||
"integer",
|
||||
"mo",
|
||||
"Date",
|
||||
"POSIXct",
|
||||
"rsi",
|
||||
"raw",
|
||||
"hms")
|
||||
%in% class(x))) {
|
||||
# no transformation needed
|
||||
FALSE
|
||||
} else {
|
||||
x <- x[!is.na(x) & !is.null(x) & !identical(x, "")]
|
||||
if (length(x) == 0) {
|
||||
return(FALSE)
|
||||
}
|
||||
checked <- suppressWarnings(as.rsi(x))
|
||||
outcome <- sum(is.na(checked)) / length(x)
|
||||
outcome <= threshold
|
||||
}
|
||||
}
|
||||
|
||||
#' @exportMethod print.rsi
|
||||
#' @export
|
||||
#' @importFrom dplyr %>%
|
||||
#' @noRd
|
||||
print.rsi <- function(x, ...) {
|
||||
cat("Class 'rsi'\n")
|
||||
print(as.character(x), quote = FALSE)
|
||||
}
|
||||
|
||||
#' @exportMethod droplevels.rsi
|
||||
#' @export
|
||||
#' @noRd
|
||||
droplevels.rsi <- function(x, exclude = if (anyNA(levels(x))) NULL else NA, ...) {
|
||||
x <- droplevels.factor(x, exclude = exclude, ...)
|
||||
class(x) <- c("rsi", "ordered", "factor")
|
||||
x
|
||||
}
|
||||
|
||||
#' @exportMethod summary.rsi
|
||||
#' @export
|
||||
#' @noRd
|
||||
summary.rsi <- function(object, ...) {
|
||||
x <- object
|
||||
c(
|
||||
"Class" = "rsi",
|
||||
"<NA>" = sum(is.na(x)),
|
||||
"Sum S" = sum(x == "S", na.rm = TRUE),
|
||||
"Sum IR" = sum(x %in% c("I", "R"), na.rm = TRUE),
|
||||
"-Sum R" = sum(x == "R", na.rm = TRUE),
|
||||
"-Sum I" = sum(x == "I", na.rm = TRUE)
|
||||
)
|
||||
}
|
||||
|
||||
#' @exportMethod plot.rsi
|
||||
#' @export
|
||||
#' @importFrom dplyr %>% group_by summarise filter mutate if_else n_distinct
|
||||
#' @importFrom graphics plot text
|
||||
#' @noRd
|
||||
plot.rsi <- function(x,
|
||||
lwd = 2,
|
||||
ylim = NULL,
|
||||
ylab = "Percentage",
|
||||
xlab = "Antimicrobial Interpretation",
|
||||
main = paste("Susceptibility Analysis of", deparse(substitute(x))),
|
||||
axes = FALSE,
|
||||
...) {
|
||||
suppressWarnings(
|
||||
data <- data.frame(x = x,
|
||||
y = 1,
|
||||
stringsAsFactors = TRUE) %>%
|
||||
group_by(x) %>%
|
||||
summarise(n = sum(y)) %>%
|
||||
filter(!is.na(x)) %>%
|
||||
mutate(s = round((n / sum(n)) * 100, 1))
|
||||
)
|
||||
if (!"S" %in% data$x) {
|
||||
data <- rbind(data, data.frame(x = "S", n = 0, s = 0))
|
||||
}
|
||||
if (!"I" %in% data$x) {
|
||||
data <- rbind(data, data.frame(x = "I", n = 0, s = 0))
|
||||
}
|
||||
if (!"R" %in% data$x) {
|
||||
data <- rbind(data, data.frame(x = "R", n = 0, s = 0))
|
||||
}
|
||||
|
||||
data$x <- factor(data$x, levels = c("S", "I", "R"), ordered = TRUE)
|
||||
|
||||
ymax <- if_else(max(data$s) > 95, 105, 100)
|
||||
|
||||
plot(x = data$x,
|
||||
y = data$s,
|
||||
lwd = lwd,
|
||||
ylim = c(0, ymax),
|
||||
ylab = ylab,
|
||||
xlab = xlab,
|
||||
main = main,
|
||||
axes = axes,
|
||||
...)
|
||||
# x axis
|
||||
axis(side = 1, at = 1: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, ")"))
|
||||
}
|
||||
|
||||
|
||||
#' @exportMethod barplot.rsi
|
||||
#' @export
|
||||
#' @importFrom dplyr %>% group_by summarise
|
||||
#' @importFrom graphics barplot axis par
|
||||
#' @noRd
|
||||
barplot.rsi <- function(height,
|
||||
col = c("green3", "orange2", "red3"),
|
||||
xlab = ifelse(beside, "Antimicrobial Interpretation", ""),
|
||||
main = paste("Susceptibility Analysis of", deparse(substitute(height))),
|
||||
ylab = "Frequency",
|
||||
beside = TRUE,
|
||||
axes = beside,
|
||||
...) {
|
||||
|
||||
if (axes == TRUE) {
|
||||
par(mar = c(5, 4, 4, 2) + 0.1)
|
||||
} else {
|
||||
par(mar = c(2, 4, 4, 2) + 0.1)
|
||||
}
|
||||
|
||||
barplot(as.matrix(table(height)),
|
||||
col = col,
|
||||
xlab = xlab,
|
||||
main = main,
|
||||
ylab = ylab,
|
||||
beside = beside,
|
||||
axes = FALSE,
|
||||
...)
|
||||
# y axis, 0-100%
|
||||
axis(side = 2, at = seq(0, max(table(height)) + max(table(height)) * 1.1, by = 25))
|
||||
if (axes == TRUE && beside == TRUE) {
|
||||
axis(side = 1, labels = levels(height), at = c(1, 2, 3) + 0.5, lwd = 0)
|
||||
}
|
||||
}
|
||||
|
||||
#' @importFrom pillar type_sum
|
||||
#' @export
|
||||
type_sum.rsi <- function(x) {
|
||||
"rsi"
|
||||
}
|
||||
|
||||
#' @importFrom pillar pillar_shaft
|
||||
#' @importFrom crayon bgGreen bgYellow bgRed white black
|
||||
#' @export
|
||||
pillar_shaft.rsi <- function(x, ...) {
|
||||
out <- trimws(format(x))
|
||||
out[is.na(x)] <- pillar::style_subtle(" NA")
|
||||
out[x == "S"] <- bgGreen(white(" S "))
|
||||
out[x == "I"] <- bgYellow(black(" I "))
|
||||
out[x == "R"] <- bgRed(white(" R "))
|
||||
pillar::new_pillar_shaft_simple(out, align = "left", min_width = 3)
|
||||
}
|
||||
-256
@@ -1,256 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' @importFrom rlang enquos as_label
|
||||
dots2vars <- function(...) {
|
||||
# this function is to give more informative output about
|
||||
# variable names in count_* and portion_* functions
|
||||
paste(
|
||||
unlist(
|
||||
lapply(enquos(...),
|
||||
function(x) {
|
||||
l <- as_label(x)
|
||||
if (l != ".") {
|
||||
l
|
||||
} else {
|
||||
character(0)
|
||||
}
|
||||
})
|
||||
),
|
||||
collapse = ", ")
|
||||
}
|
||||
|
||||
#' @importFrom dplyr %>% pull all_vars any_vars filter_all funs mutate_all
|
||||
# @importFrom clean percentage
|
||||
rsi_calc <- function(...,
|
||||
ab_result,
|
||||
minimum = 0,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE,
|
||||
only_count = FALSE) {
|
||||
|
||||
data_vars <- dots2vars(...)
|
||||
|
||||
if (!is.numeric(minimum)) {
|
||||
stop("`minimum` must be numeric", call. = FALSE)
|
||||
}
|
||||
if (!is.logical(as_percent)) {
|
||||
stop("`as_percent` must be logical", call. = FALSE)
|
||||
}
|
||||
if (!is.logical(only_all_tested)) {
|
||||
stop("`only_all_tested` must be logical", call. = FALSE)
|
||||
}
|
||||
|
||||
dots_df <- ...elt(1) # it needs this evaluation
|
||||
dots <- base::eval(base::substitute(base::alist(...)))
|
||||
if ("also_single_tested" %in% names(dots)) {
|
||||
stop("`also_single_tested` was replaced by `only_all_tested`. Please read Details in the help page (`?portion`) as this may have a considerable impact on your analysis.", call. = FALSE)
|
||||
}
|
||||
ndots <- length(dots)
|
||||
|
||||
if ("data.frame" %in% class(dots_df)) {
|
||||
# data.frame passed with other columns, like: example_isolates %>% portion_S(amcl, gent)
|
||||
dots <- as.character(dots)
|
||||
dots <- dots[dots != "."]
|
||||
if (length(dots) == 0 | all(dots == "df")) {
|
||||
# for complete data.frames, like example_isolates %>% select(amcl, gent) %>% portion_S()
|
||||
# and the old rsi function, that has "df" as name of the first parameter
|
||||
x <- dots_df
|
||||
} else {
|
||||
x <- dots_df[, dots]
|
||||
}
|
||||
} else if (ndots == 1) {
|
||||
# only 1 variable passed (can also be data.frame), like: portion_S(example_isolates$amcl) and example_isolates$amcl %>% portion_S()
|
||||
x <- dots_df
|
||||
} else {
|
||||
# multiple variables passed without pipe, like: portion_S(example_isolates$amcl, example_isolates$gent)
|
||||
x <- NULL
|
||||
try(x <- as.data.frame(dots), silent = TRUE)
|
||||
if (is.null(x)) {
|
||||
# support for: with(example_isolates, portion_S(amcl, gent))
|
||||
x <- as.data.frame(rlang::list2(...))
|
||||
}
|
||||
}
|
||||
|
||||
if (is.null(x)) {
|
||||
warning("argument is NULL (check if columns exist): returning NA", call. = FALSE)
|
||||
return(NA)
|
||||
}
|
||||
|
||||
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 %>% pull(i))) {
|
||||
rsi_integrity_check <- c(rsi_integrity_check, x %>% pull(i) %>% as.character())
|
||||
x[, i] <- suppressWarnings(x %>% pull(i) %>% as.rsi()) # 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)
|
||||
}
|
||||
|
||||
if (only_all_tested == TRUE) {
|
||||
# THE NUMBER OF ISOLATES WHERE *ALL* ABx ARE S/I/R
|
||||
x <- apply(X = x %>% mutate_all(as.integer),
|
||||
MARGIN = 1,
|
||||
FUN = base::min)
|
||||
numerator <- sum(as.integer(x) %in% as.integer(ab_result), na.rm = TRUE)
|
||||
denominator <- length(x) - sum(is.na(x))
|
||||
|
||||
} else {
|
||||
# THE NUMBER OF ISOLATES WHERE *ANY* ABx IS S/I/R
|
||||
other_values <- base::setdiff(c(NA, levels(ab_result)), ab_result)
|
||||
other_values_filter <- base::apply(x, 1, function(y) {
|
||||
base::all(y %in% other_values) & base::any(is.na(y))
|
||||
})
|
||||
numerator <- x %>% filter_all(any_vars(. %in% ab_result)) %>% nrow()
|
||||
denominator <- x %>% filter(!other_values_filter) %>% nrow()
|
||||
}
|
||||
} 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) {
|
||||
warning("Increase speed by transforming to class `rsi` on beforehand: df %>% mutate_if(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)
|
||||
}
|
||||
warning("Introducing NA: only ", denominator, " results available", data_vars, " (`minimum` was set to ", minimum, ").", call. = FALSE)
|
||||
fraction <- NA
|
||||
} else {
|
||||
fraction <- numerator / denominator
|
||||
}
|
||||
|
||||
if (as_percent == TRUE) {
|
||||
percentage(fraction, digits = 1)
|
||||
} else {
|
||||
fraction
|
||||
}
|
||||
}
|
||||
|
||||
#' @importFrom dplyr %>% summarise_if mutate select everything bind_rows
|
||||
#' @importFrom tidyr gather
|
||||
rsi_calc_df <- function(type, # "portion" or "count"
|
||||
data,
|
||||
translate_ab = "name",
|
||||
language = get_locale(),
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE,
|
||||
combine_SI_missing = FALSE) {
|
||||
|
||||
if (!"data.frame" %in% class(data)) {
|
||||
stop(paste0("`", type, "_df` must be called on a data.frame"), call. = FALSE)
|
||||
}
|
||||
|
||||
if (isTRUE(combine_IR) & isTRUE(combine_SI_missing)) {
|
||||
combine_SI <- FALSE
|
||||
}
|
||||
if (isTRUE(combine_SI) & isTRUE(combine_IR)) {
|
||||
stop("either `combine_SI` or `combine_IR` can be TRUE, not both", call. = FALSE)
|
||||
}
|
||||
|
||||
if (!any(sapply(data, is.rsi), na.rm = TRUE)) {
|
||||
stop("No columns with class 'rsi' found. See ?as.rsi.", call. = FALSE)
|
||||
}
|
||||
|
||||
if (as.character(translate_ab) %in% c("TRUE", "official")) {
|
||||
translate_ab <- "name"
|
||||
}
|
||||
|
||||
get_summaryfunction <- function(int, type) {
|
||||
# look for portion_S, count_S, etc:
|
||||
int_fn <- get(paste0(type, "_", int), envir = asNamespace("AMR"))
|
||||
|
||||
if (type == "portion") {
|
||||
summ <- summarise_if(.tbl = data,
|
||||
.predicate = is.rsi,
|
||||
.funs = int_fn,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent)
|
||||
} else if (type == "count") {
|
||||
summ <- summarise_if(.tbl = data,
|
||||
.predicate = is.rsi,
|
||||
.funs = int_fn)
|
||||
}
|
||||
summ %>%
|
||||
mutate(interpretation = int) %>%
|
||||
select(interpretation, everything())
|
||||
}
|
||||
|
||||
resS <- get_summaryfunction("S", type)
|
||||
resI <- get_summaryfunction("I", type)
|
||||
resR <- get_summaryfunction("R", type)
|
||||
resSI <- get_summaryfunction("SI", type)
|
||||
resIR <- get_summaryfunction("IR", type)
|
||||
data.groups <- group_vars(data)
|
||||
|
||||
if (isFALSE(combine_SI) & isFALSE(combine_IR)) {
|
||||
res <- bind_rows(resS, resI, resR) %>%
|
||||
mutate(interpretation = factor(interpretation,
|
||||
levels = c("S", "I", "R"),
|
||||
ordered = TRUE))
|
||||
|
||||
} else if (isTRUE(combine_IR)) {
|
||||
res <- bind_rows(resS, resIR) %>%
|
||||
mutate(interpretation = factor(interpretation,
|
||||
levels = c("S", "IR"),
|
||||
ordered = TRUE))
|
||||
|
||||
} else if (isTRUE(combine_SI)) {
|
||||
res <- bind_rows(resSI, resR) %>%
|
||||
mutate(interpretation = factor(interpretation,
|
||||
levels = c("SI", "R"),
|
||||
ordered = TRUE))
|
||||
}
|
||||
|
||||
res <- res %>%
|
||||
gather(antibiotic, value, -interpretation, -data.groups) %>%
|
||||
select(antibiotic, everything())
|
||||
|
||||
if (!translate_ab == FALSE) {
|
||||
res <- res %>% mutate(antibiotic = AMR::ab_property(antibiotic, property = translate_ab, language = language))
|
||||
}
|
||||
|
||||
res
|
||||
}
|
||||
-57
@@ -1,57 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' @rdname portion
|
||||
#' @rdname count
|
||||
#' @export
|
||||
rsi_df <- function(data,
|
||||
translate_ab = "name",
|
||||
language = get_locale(),
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE) {
|
||||
|
||||
portions <- rsi_calc_df(type = "portion",
|
||||
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))
|
||||
|
||||
counts <- rsi_calc_df(type = "count",
|
||||
data = data,
|
||||
translate_ab = FALSE,
|
||||
language = "en",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR,
|
||||
combine_SI_missing = missing(combine_SI))
|
||||
|
||||
data.frame(portions,
|
||||
isolates = counts$value,
|
||||
stringsAsFactors = FALSE)
|
||||
|
||||
}
|
||||
@@ -1,62 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.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: the left tail is longer; the mass of the distribution is concentrated on the right of the figure. When positive: the right tail is longer; the mass of the distribution is concentrated on the left of the figure.
|
||||
#' @param x a vector of values, a \code{matrix} or a \code{data frame}
|
||||
#' @param na.rm a logical value indicating whether \code{NA} values should be stripped before the computation proceeds.
|
||||
#' @exportMethod skewness
|
||||
#' @seealso \code{\link{kurtosis}}
|
||||
#' @rdname skewness
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @export
|
||||
skewness <- function(x, na.rm = FALSE) {
|
||||
UseMethod("skewness")
|
||||
}
|
||||
|
||||
#' @exportMethod skewness.default
|
||||
#' @rdname skewness
|
||||
#' @export
|
||||
skewness.default <- function(x, na.rm = FALSE) {
|
||||
x <- as.vector(x)
|
||||
if (na.rm == TRUE) {
|
||||
x <- x[!is.na(x)]
|
||||
}
|
||||
n <- length(x)
|
||||
(base::sum((x - base::mean(x))^3) / n) / (base::sum((x - base::mean(x)) ^ 2) / n) ^ (3 / 2)
|
||||
}
|
||||
|
||||
#' @exportMethod skewness.matrix
|
||||
#' @rdname skewness
|
||||
#' @export
|
||||
skewness.matrix <- function(x, na.rm = FALSE) {
|
||||
base::apply(x, 2, skewness.default, na.rm = na.rm)
|
||||
}
|
||||
|
||||
#' @exportMethod skewness.data.frame
|
||||
#' @rdname skewness
|
||||
#' @export
|
||||
skewness.data.frame <- function(x, na.rm = FALSE) {
|
||||
base::sapply(x, skewness.default, na.rm = na.rm)
|
||||
}
|
||||
Binary file not shown.
-148
@@ -1,148 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Translate strings from AMR package
|
||||
#'
|
||||
#' For language-dependent output of AMR functions, like \code{\link{mo_name}}, \code{\link{mo_type}} and \code{\link{ab_name}}.
|
||||
#' @details Strings will be translated to foreign languages if they are defined in a local translation file. Additions to this file can be suggested at our repository. The file can be found here: \url{https://gitlab.com/msberends/AMR/blob/master/data-raw/translations.tsv}.
|
||||
#'
|
||||
#' Currently supported languages can be found if running: \code{unique(AMR:::translations_file$lang)}.
|
||||
#'
|
||||
#' Please suggest your own translations \href{https://gitlab.com/msberends/AMR/issues/new?issue[title]=Translation\%20suggestion}{by creating a new issue on our repository}.
|
||||
#'
|
||||
#' This file will be read by all functions where a translated output can be desired, like all \code{\link{mo_property}} functions (\code{\link{mo_fullname}}, \code{\link{mo_type}}, etc.).
|
||||
#'
|
||||
#' The system language will be used at default, if that language is supported. The system language can be overwritten with \code{\link{getOption}("AMR_locale")}.
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @rdname translate
|
||||
#' @name translate
|
||||
#' @export
|
||||
#' @examples
|
||||
#' # The 'language' parameter of below functions
|
||||
#' # will be set automatically to your system language
|
||||
#' # with get_locale()
|
||||
#'
|
||||
#' # English
|
||||
#' mo_name("CoNS", language = "en")
|
||||
#' #> "Coagulase-negative Staphylococcus (CoNS)"
|
||||
#'
|
||||
#' # German
|
||||
#' mo_name("CoNS", language = "de")
|
||||
#' #> "Koagulase-negative Staphylococcus (KNS)"
|
||||
#'
|
||||
#' # Dutch
|
||||
#' mo_name("CoNS", language = "nl")
|
||||
#' #> "Coagulase-negatieve Staphylococcus (CNS)"
|
||||
#'
|
||||
#' # Spanish
|
||||
#' mo_name("CoNS", language = "es")
|
||||
#' #> "Staphylococcus coagulasa negativo (SCN)"
|
||||
#'
|
||||
#' # Italian
|
||||
#' mo_name("CoNS", language = "it")
|
||||
#' #> "Staphylococcus negativo coagulasi (CoNS)"
|
||||
#'
|
||||
#' # Portuguese
|
||||
#' mo_name("CoNS", language = "pt")
|
||||
#' #> "Staphylococcus coagulase negativo (CoNS)"
|
||||
get_locale <- function() {
|
||||
if (!is.null(getOption("AMR_locale", default = NULL))) {
|
||||
return(getOption("AMR_locale"))
|
||||
}
|
||||
|
||||
lang <- Sys.getlocale("LC_COLLATE")
|
||||
|
||||
# Check the locale settings for a start with one of these languages:
|
||||
|
||||
# grepl() with ignore.case = FALSE is faster than %like%
|
||||
|
||||
if (grepl("^(English|en_|EN_)", lang, ignore.case = FALSE)) {
|
||||
# as first option to optimise speed
|
||||
"en"
|
||||
} else if (grepl("^(German|Deutsch|de_|DE_)", lang, ignore.case = FALSE)) {
|
||||
"de"
|
||||
} else if (grepl("^(Dutch|Nederlands|nl_|NL_)", lang, ignore.case = FALSE)) {
|
||||
"nl"
|
||||
} else if (grepl("^(Spanish|Espa.ol|es_|ES_)", lang, ignore.case = FALSE)) {
|
||||
"es"
|
||||
} else if (grepl("^(Italian|Italiano|it_|IT_)", lang, ignore.case = FALSE)) {
|
||||
"it"
|
||||
} else if (grepl("^(French|Fran.ais|fr_|FR_)", lang, ignore.case = FALSE)) {
|
||||
"fr"
|
||||
} else if (grepl("^(Portuguese|Portugu.s|pt_|PT_)", lang, ignore.case = FALSE)) {
|
||||
"pt"
|
||||
} else {
|
||||
# other language -> set to English
|
||||
"en"
|
||||
}
|
||||
}
|
||||
|
||||
# translate strings based on inst/translations.tsv
|
||||
#' @importFrom dplyr %>% filter
|
||||
translate_AMR <- function(from, language = get_locale(), only_unknown = FALSE) {
|
||||
|
||||
if (is.null(language)) {
|
||||
return(from)
|
||||
}
|
||||
if (language %in% c("en", "", NA)) {
|
||||
return(from)
|
||||
}
|
||||
|
||||
df_trans <- translations_file # internal data file
|
||||
|
||||
if (!language %in% df_trans$lang) {
|
||||
stop("Unsupported language: '", language, "' - use one of: ",
|
||||
paste0("'", sort(unique(df_trans$lang)), "'", collapse = ", "),
|
||||
call. = FALSE)
|
||||
}
|
||||
|
||||
df_trans <- df_trans %>% filter(lang == language)
|
||||
if (only_unknown == TRUE) {
|
||||
df_trans <- df_trans %>% filter(pattern %like% "unknown")
|
||||
}
|
||||
|
||||
# default case sensitive if value if 'ignore.case' is missing:
|
||||
df_trans$ignore.case[is.na(df_trans$ignore.case)] <- FALSE
|
||||
# default not using regular expressions (fixed = TRUE) if 'fixed' is missing:
|
||||
df_trans$fixed[is.na(df_trans$fixed)] <- TRUE
|
||||
|
||||
# check if text to look for is in one of the patterns
|
||||
any_form_in_patterns <- tryCatch(any(from %like% paste0("(", paste(df_trans$pattern, collapse = "|"), ")")),
|
||||
error = function(e) {
|
||||
warning("Translation not possible. Please open an issue on GitLab (https://gitlab.com/msberends/AMR/issues) or GitHub (https://github.com/msberends/AMR/issues).", call. = FALSE)
|
||||
return(FALSE)
|
||||
})
|
||||
if (NROW(df_trans) == 0 | !any_form_in_patterns) {
|
||||
return(from)
|
||||
}
|
||||
|
||||
for (i in seq_len(nrow(df_trans))) {
|
||||
from <- gsub(x = from,
|
||||
pattern = df_trans$pattern[i],
|
||||
replacement = df_trans$replacement[i],
|
||||
fixed = df_trans$fixed[i],
|
||||
ignore.case = df_trans$ignore.case[i])
|
||||
}
|
||||
|
||||
# force UTF-8 for diacritics
|
||||
base::enc2utf8(from)
|
||||
|
||||
}
|
||||
@@ -1,42 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.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=60px style=margin-bottom:5px} \cr}
|
||||
#' This package contains \strong{all ~450 antimicrobial 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, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/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.
|
||||
#'
|
||||
#' \strong{NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See \url{https://www.whocc.no/copyright_disclaimer/}.}
|
||||
#' @inheritSection AMR Read more on our website!
|
||||
#' @name WHOCC
|
||||
#' @rdname WHOCC
|
||||
#' @examples
|
||||
#' as.ab("meropenem")
|
||||
#' ab_name("J01DH02")
|
||||
#'
|
||||
#' ab_tradenames("flucloxacillin")
|
||||
NULL
|
||||
@@ -1,263 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' @importFrom data.table as.data.table setkey
|
||||
.onLoad <- function(libname, pkgname) {
|
||||
# get new functions not available in older versions of R
|
||||
backports::import(pkgname)
|
||||
|
||||
# register data
|
||||
microorganisms.oldDT <- as.data.table(AMR::microorganisms.old)
|
||||
# for fullname_lower: keep only dots, letters, numbers, slashes, spaces and dashes
|
||||
microorganisms.oldDT$fullname_lower <- gsub("[^.a-z0-9/ \\-]+", "", tolower(microorganisms.oldDT$fullname))
|
||||
setkey(microorganisms.oldDT, prevalence, fullname)
|
||||
|
||||
assign(x = "microorganismsDT",
|
||||
value = make_DT(),
|
||||
envir = asNamespace("AMR"))
|
||||
|
||||
assign(x = "microorganisms.oldDT",
|
||||
value = microorganisms.oldDT,
|
||||
envir = asNamespace("AMR"))
|
||||
|
||||
assign(x = "mo_codes_v0.5.0",
|
||||
value = make_trans_tbl(),
|
||||
envir = asNamespace("AMR"))
|
||||
|
||||
}
|
||||
|
||||
# maybe add survey later: "https://www.surveymonkey.com/r/AMR_for_R"
|
||||
|
||||
#' @importFrom data.table as.data.table setkey
|
||||
make_DT <- function() {
|
||||
microorganismsDT <- as.data.table(AMR::microorganisms %>%
|
||||
mutate(kingdom_index = case_when(kingdom == "Bacteria" ~ 1,
|
||||
kingdom == "Fungi" ~ 2,
|
||||
kingdom == "Protozoa" ~ 3,
|
||||
kingdom == "Archaea" ~ 4,
|
||||
TRUE ~ 6)))
|
||||
# for fullname_lower: keep only dots, letters, numbers, slashes, spaces and dashes
|
||||
microorganismsDT$fullname_lower <- gsub("[^.a-z0-9/ \\-]+", "", tolower(microorganismsDT$fullname))
|
||||
setkey(microorganismsDT,
|
||||
prevalence,
|
||||
kingdom_index,
|
||||
fullname)
|
||||
microorganismsDT
|
||||
}
|
||||
|
||||
make_trans_tbl <- function() {
|
||||
# conversion of old MO codes from v0.5.0 (ITIS) to later versions (Catalogue of Life)
|
||||
c(B_ACHRMB = "B_ACHRM", B_ANNMA = "B_ACTNS", B_ACLLS = "B_ALCYC",
|
||||
B_AHNGM = "B_ARCHN", B_ARMTM = "B_ARMTMN", B_ARTHR = "B_ARTHRB", B_ARTHRS = "B_ARTHR",
|
||||
B_APHLS = "B_AZRHZP", B_BRCHA = "B_BRCHY", B_BCTRM = "B_BRVBCT",
|
||||
B_CLRBCT = "B_CLRBC", B_CTRDM = "B_CLSTR", B_CPRMM = "B_CYLND",
|
||||
B_DLCLN = "B_DPLCL", B_DMCLM = "B_DSLFT", B_DSLFVB = "B_DSLFV",
|
||||
B_FCTRM = "B_FSBCT", B_GNRLA = "B_GRDNR", B_HNRBM = "B_HLNRB",
|
||||
B_HPHGA = "B_HNPHGA", B_HCCCS = "B_HYDRC", B_MCRCLS = "B_MCRCL",
|
||||
B_MTHYLS = "B_MLSMA", B_MARCLS = "B_MRCLS", B_MGCLS = "B_MSTGC",
|
||||
B_MCLLA = "B_MTHYLC", B_MYCPLS = "B_MYCPL", B_NBCTR = "B_NTRBC",
|
||||
B_OCLLS = "B_OCNBC", B_PTHRX = "B_PLNKT", B_PCCCS = "B_PRCHL",
|
||||
B_PSPHN = "B_PRPHY", B_PDMNS = "B_PSDMN", B_SCCHRP = "B_SCCHR",
|
||||
B_SRBCTR = "B_SHRBCTR", B_STRPTC = "B_STRPT", B_SHMNS = "B_SYNTR",
|
||||
B_TRBCTR = "B_THRMN", P_ALBMN = "C_ABMNA", F_ACHLY = "C_ACHLY",
|
||||
P_ACINT = "C_ACINT", P_ARTCL = "C_ACLNA", P_ACRVL = "C_ACRVL",
|
||||
P_ADRCT = "C_ADRCT", P_AMPHS = "C_AHSRS", F_ALBUG = "C_ALBUG",
|
||||
P_ALCNT = "C_ALCNT", P_ALFRD = "C_ALFRD", P_ALLGR = "C_ALLGR",
|
||||
P_AMPHL = "C_ALPTS", F_ALTHR = "C_ALTHR", P_AMLLA = "C_AMLLA",
|
||||
P_ANMLN = "C_AMLNA", P_AMMBC = "C_AMMBC", P_AMMDS = "C_AMMDS",
|
||||
P_AMMLG = "C_AMMLG", P_AMMMR = "C_AMMMR", P_AMMMS = "C_AMMMS",
|
||||
P_AMMON = "C_AMMON", P_AMMSC = "C_AMMSC", P_AMMSP = "C_AMMSP",
|
||||
P_AMMST = "C_AMMST", P_AMMTM = "C_AMMTM", F_AMYCS = "C_AMYCS",
|
||||
P_ANARM = "C_ANARM", P_ANGLD = "C_ANGLD", P_ANGLG = "C_ANGLG",
|
||||
P_ANNLC = "C_ANNLC", F_ANSLP = "C_ANSLP", F_APDCH = "C_APDCH",
|
||||
F_APHND = "C_APHND", F_APLNC = "C_APLNC", F_AQLND = "C_AQLND",
|
||||
P_ARCHS = "C_ARCHAS", P_ASTRN = "C_ARNNN", P_ARNPR = "C_ARNPR",
|
||||
F_ARSPR = "C_ARSPR", P_ARTST = "C_ARTSTR", P_AMPHC = "C_ARYNA",
|
||||
P_ASCHM = "C_ASCHM", P_ASPDS = "C_ASPDS", P_ASTCL = "C_ASTCL",
|
||||
P_ASTRG = "C_ASTRGR", P_ASTRM = "C_ASTRMM", P_ASTRR = "C_ASTRR",
|
||||
P_ASTRT = "C_ASTRTR", F_ATKNS = "C_ATKNS", F_AYLLA = "C_AYLLA",
|
||||
P_BAGGN = "C_BAGGN", P_BCCLL = "C_BCCLL", P_BDLLD = "C_BDLLD",
|
||||
P_BGNRN = "C_BGNRN", P_BLCLN = "C_BLCLN", P_BLMND = "C_BLMND",
|
||||
P_BLMNL = "C_BLMNL", P_BLPHR = "C_BLPHR", P_BLVNT = "C_BLVNT",
|
||||
P_BOLVN = "C_BOLVN", P_BORLS = "C_BORLS", P_BRNNM = "C_BRNNM",
|
||||
P_BRSLN = "C_BRSLN", P_BRSRD = "C_BRSRD", F_BRVLG = "C_BRVLG",
|
||||
F_BNLLA = "C_BRVLGN", P_BSCCM = "C_BSCCM", F_BSDPH = "C_BSDPH",
|
||||
P_BTHYS = "C_BTHYS", P_BTLLN = "C_BTLLN", P_BULMN = "C_BULMN",
|
||||
P_CCLDM = "C_CCLDM", P_CDNLL = "C_CDNLL", P_CLPSS = "C_CDNLLP",
|
||||
P_CHLDN = "C_CHLDNL", P_CHLST = "C_CHLST", P_CHNLM = "C_CHNLM",
|
||||
P_CHRYS = "C_CHRYSL", P_CHTSP = "C_CHTSP", P_CBCDS = "C_CIBCDS",
|
||||
P_CLCRN = "C_CLCRN", P_CLMNA = "C_CLMNA", P_CLPDM = "C_CLPDM",
|
||||
P_CLPHR = "C_CLPHRY", P_CLVLN = "C_CLVLN", P_CMPNL = "C_CMPNL",
|
||||
P_CNCRS = "C_CNCRS", P_CNTCH = "C_CNTCH", F_CNTRM = "C_CNTRMY",
|
||||
P_COLPD = "C_COLPD", P_COLPS = "C_COLPS", P_CPRDS = "C_CPRDS",
|
||||
P_CRNSP = "C_CPRMA", P_CRBNL = "C_CRBNL", P_CRBRB = "C_CRBRB",
|
||||
P_CRBRG = "C_CRBRG", P_CRBRS = "C_CRBRS", P_CRCHS = "C_CRCHS",
|
||||
P_CRCLC = "C_CRCLC", P_CRNLC = "C_CRNLC", P_CRNTH = "C_CRNTH",
|
||||
P_CRPNT = "C_CRPNT", P_CRSTG = "C_CRSTG", P_CRTHN = "C_CRTHN",
|
||||
P_CRTRN = "C_CRTRN", P_CYMBL = "C_CRTTA", P_CRYPT = "C_CRYPT",
|
||||
P_CSHMN = "C_CSHMNL", P_CSSDL = "C_CSSDL", P_CLNDS = "C_CSSDLN",
|
||||
P_CHRNA = "C_CTHRN", P_CTPSS = "C_CTPSS", P_CUNLN = "C_CUNLN",
|
||||
P_CYLND = "C_CVLNA", P_CYCLC = "C_CYCLCB", P_CDNTA = "C_CYCLD",
|
||||
P_CYCLG = "C_CYCLG", P_CYCLM = "C_CYCLM", P_CYRTL = "C_CYRTL",
|
||||
P_CYSTM = "C_CYSTM", P_DCHLM = "C_DCHLM", P_DCRBS = "C_DCRBS",
|
||||
P_DCTYC = "C_DCTYC", P_DIDNM = "C_DIDNM", P_DLPTS = "C_DLPTS",
|
||||
P_DNTLN = "C_DNTLN", P_DNTST = "C_DNTST", P_DORTH = "C_DORTH",
|
||||
P_DCTYP = "C_DPHMS", F_DPLCY = "C_DPLCY", P_DNDRT = "C_DRTNA",
|
||||
P_DSCMM = "C_DSCMM", P_DSCRB = "C_DSCRB", P_DSCRN = "C_DSCRN",
|
||||
P_DSCSP = "C_DSCSP", P_DSNBR = "C_DSNBR", P_DYCBC = "C_DYCBC",
|
||||
F_DCTYC = "C_DYCHS", F_ECTRG = "C_ECTRG", B_EDWRD = "C_EDWRD",
|
||||
P_EGGRL = "C_EGGRL", P_EHLYS = "C_EHLYS", P_EHRNB = "C_EHRNB",
|
||||
P_ELPHD = "C_ELPHD", P_ENCHL = "C_ELYDM", P_EPHDM = "C_EPHDM",
|
||||
P_EPLTS = "C_EPLTS", P_EPLXL = "C_EPLXL", P_EPNDL = "C_EPNDL",
|
||||
P_EPNDS = "C_EPNDS", P_ENLLA = "C_EPSTM", P_EPSTY = "C_EPSTY",
|
||||
F_ERYCH = "C_ERYCH", F_ESMDM = "C_ESMDM", P_ESSYR = "C_ESSYR",
|
||||
P_FSCHR = "C_FHRNA", P_FLRLS = "C_FLRLS", P_FLNTN = "C_FNTNA",
|
||||
P_FRNDC = "C_FRNDC", P_FRNTN = "C_FRNTN", P_FRSNK = "C_FRSNK",
|
||||
P_FNLLA = "C_FSCHRN", P_FSSRN = "C_FSSRN", P_FVCSS = "C_FVCSS",
|
||||
P_GDRYN = "C_GDRYN", F_GELGN = "C_GELGN", P_GERDA = "C_GERDA",
|
||||
P_GLACM = "C_GLACM", P_GLBBL = "C_GLBBL", P_GLBGR = "C_GLBGR",
|
||||
P_GLBLN = "C_GLBLN", P_GRTLA = "C_GLBRT", P_GLBTX = "C_GLBTX",
|
||||
P_GLLNA = "C_GLLNA", P_GLMSP = "C_GLMSP", P_GLNDL = "C_GLNDL",
|
||||
F_GNMCH = "C_GNMCH", P_GOSLL = "C_GOSLL", P_GRNDS = "C_GRNDS",
|
||||
P_GRNTA = "C_GRNTA", P_GLBRT = "C_GTLLA", P_GTTLN = "C_GTTLN",
|
||||
P_GVLNP = "C_GVLNP", P_GYPSN = "C_GYPSN", P_GYRDN = "C_GYRDN",
|
||||
P_HALTR = "C_HALTR", P_HANZW = "C_HANZW", P_HAURN = "C_HAURN",
|
||||
P_HELNN = "C_HELNN", P_HLPHR = "C_HHRYA", P_HLNTA = "C_HLNTA",
|
||||
F_HLPHT = "C_HLPHT", P_HLSTC = "C_HLSTC", P_HMSPH = "C_HMSPH",
|
||||
P_HMTRM = "C_HMTRM", P_HPKNS = "C_HPKNS", P_HPLPH = "C_HPLPH",
|
||||
P_HPPCR = "C_HPPCR", P_HNLLA = "C_HPPCRP", P_HRMSN = "C_HRMSN",
|
||||
P_HRNLL = "C_HRNLL", F_HRPCH = "C_HRPCH", P_HSTGR = "C_HSTGR",
|
||||
P_HSTTL = "C_HSTTL", P_HTRST = "C_HTGNA", P_HTRLL = "C_HTRLL",
|
||||
P_HTRPH = "C_HTRPH", F_HYPHC = "C_HYPHC", P_HYPRM = "C_HYPRM",
|
||||
P_INTRN = "C_INTRN", P_IRIDI = "C_IRIDI", P_ISLND = "C_ISLND",
|
||||
P_JCLLL = "C_JCLLL", P_KHLLL = "C_KHLLL", P_KRNPS = "C_KRNPS",
|
||||
P_KRRRL = "C_KRRRL", P_LABOE = "C_LABOE", P_LAGEN = "C_LAGEN",
|
||||
P_LBSLL = "C_LBSLL", F_LTHLA = "C_LBYRN", P_LCRYM = "C_LCRYM",
|
||||
P_LEMBS = "C_LEMBS", F_LGNDM = "C_LGNDM", P_LGNMM = "C_LGNMM",
|
||||
P_LGNPH = "C_LGNPHR", F_LGNSM = "C_LGNSM", P_LGYNP = "C_LGYNP",
|
||||
P_LITTB = "C_LITTB", P_LITUL = "C_LITUL", P_LMBDN = "C_LMBDN",
|
||||
P_LMRCK = "C_LMRCK", F_LBYRN = "C_LMYXA", P_LNGLN = "C_LNGLN",
|
||||
P_LNTCL = "C_LNTCL", P_LOXDS = "C_LOXDS", F_LPTLG = "C_LPTLG",
|
||||
F_LNLLA = "C_LPTLGN", F_LPTMT = "C_LPTMT", P_LRYNG = "C_LRYNG",
|
||||
P_LTCRN = "C_LTCRN", P_LTHPL = "C_LTHPL", P_LTNTS = "C_LTNTS",
|
||||
F_LTRST = "C_LTRST", P_LXPHY = "C_LXPHY", P_MCRTH = "C_MCRTH",
|
||||
P_MELNS = "C_MELNS", P_MSDNM = "C_MESDNM", P_METPS = "C_METPS",
|
||||
P_MIMSN = "C_MIMSN", P_MINCN = "C_MINCN", P_MLLNL = "C_MLLNL",
|
||||
P_MLMMN = "C_MLMMN", F_MNDNL = "C_MNDNL", P_MNLYS = "C_MNLYS",
|
||||
P_MNPSS = "C_MNPSS", P_MRGNL = "C_MRGNL", P_MRGNP = "C_MRGNP",
|
||||
P_MRSPL = "C_MRSPL", P_MRTNT = "C_MRTNT", P_MSSLN = "C_MSSLN",
|
||||
P_MSSSS = "C_MSSSS", P_MTCNT = "C_MTCNT", P_MYCHS = "C_MYCHS",
|
||||
P_MYSCH = "C_MYSCH", F_MYZCY = "C_MYZCY", P_NASSL = "C_NASSL",
|
||||
P_NBCLN = "C_NBCLN", P_NBCLR = "C_NBCLR", P_NCNRB = "C_NCNRB",
|
||||
P_NDBCL = "C_NDBCL", P_NRLLA = "C_NDBCLR", P_NMMLC = "C_NMMLC",
|
||||
F_NMTPH = "C_NMTPH", P_NNNLL = "C_NNNLL", P_NODSR = "C_NODSR",
|
||||
P_NONIN = "C_NONIN", P_NOURI = "C_NOURI", P_OCLNA = "C_OCLNA",
|
||||
P_OGLNA = "C_OGLNA", P_OPHTH = "C_OLMDM", F_OLPDP = "C_OLPDP",
|
||||
P_ONYCH = "C_OMPSS", P_OOLIN = "C_OOLIN", P_OPRCL = "C_OPRCL",
|
||||
P_ORBLN = "C_ORBLN", F_ORCAD = "C_ORCAD", P_ORDRS = "C_ORDRS",
|
||||
P_OPHRY = "C_ORYDM", P_OSNGL = "C_OSNGL", P_OXYTR = "C_OXYTR",
|
||||
P_PARRN = "C_PARRN", P_PATRS = "C_PATRS", P_PAVNN = "C_PAVNN",
|
||||
P_PTYCH = "C_PCYLS", P_PDPHR = "C_PDPHR", P_PELSN = "C_PELSN",
|
||||
F_PHGMY = "C_PHGMY", F_PSDSP = "C_PHRTA", P_PHRYG = "C_PHRYG",
|
||||
P_PHYSL = "C_PHYSL", F_PHYTP = "C_PHYTP", P_PLACS = "C_PLACS",
|
||||
P_PLCPS = "C_PLCPS", P_PLCPSL = "C_PLCPSL", P_PLCTN = "C_PLCTN",
|
||||
P_PLGPH = "C_PLGPH", B_PLGTH = "C_PLGTH", P_PLMRN = "C_PLMRN",
|
||||
P_PLNCT = "C_PLNCT", P_PLNDSC = "C_PLNDSC", P_PLNGY = "C_PLNGY",
|
||||
P_PLNRBL = "C_PLNLLA", P_PLNLN = "C_PLNLN", P_PLNLR = "C_PLNLR",
|
||||
P_PLNRB = "C_PLNRB", P_PLNSP = "C_PLNSPR", P_PLRNM = "C_PLRNM",
|
||||
P_PLRST = "C_PLRST", P_PLRTR = "C_PLRTR", F_PLSMD = "C_PLSMD",
|
||||
P_PLTYC = "C_PLTYC", P_PSDBL = "C_PLVNA", P_PLYMR = "C_PLYMR",
|
||||
P_PLTYN = "C_PNMTM", P_PNRPL = "C_PNRPL", F_PNTSM = "C_PNTSM",
|
||||
P_PRCNT = "C_PRCNT", P_PRFSS = "C_PRFSS", P_PRMCM = "C_PRMCUM",
|
||||
F_PRNSP = "C_PRNSP", P_PRPND = "C_PRPND", P_PRPYX = "C_PRPYX",
|
||||
P_PRRDN = "C_PRRDN", P_PSDDF = "C_PSDDF", P_PSDMC = "C_PSDMC",
|
||||
P_PSDND = "C_PSDND", P_PSDNN = "C_PSDNN", P_PSDPL = "C_PSDPLY",
|
||||
P_PSMMS = "C_PSMMS", P_PTLLN = "C_PTLLN", P_PTLLND = "C_PTLLND",
|
||||
F_PTRSN = "C_PTRSN", P_PULLN = "C_PULLN", P_PUTLN = "C_PUTLN",
|
||||
P_PRTTR = "C_PYMNA", P_PYRGL = "C_PYRGL", P_PYRGO = "C_PYRGO",
|
||||
P_PYRLN = "C_PYRLN", F_PYTHM = "C_PYTHIM", F_PYTHL = "C_PYTHL",
|
||||
P_PYXCL = "C_PYXCL", P_QNQLC = "C_QNQLC", P_RAMLN = "C_RAMLN",
|
||||
P_RBRTN = "C_RBRTN", P_RCRVD = "C_RCRVD", P_RCTBL = "C_RCTBL",
|
||||
P_RCTCB = "C_RCTCB", P_RCTGL = "C_RCTGL", P_RCTVG = "C_RCTVG",
|
||||
P_RDGDR = "C_RDGDR", P_REMNC = "C_REMNC", P_REPHX = "C_REPHX",
|
||||
P_RHBDM = "C_RHBDMM", F_RHBDS = "C_RHBDSP", P_RHPDD = "C_RHPDD",
|
||||
F_RHPDM = "C_RHPDM", F_RHZDMY = "C_RHZDM", P_RHZMM = "C_RHZMM",
|
||||
P_RIVRN = "C_RIVRN", P_ROSLN = "C_ROSLN", P_ROTAL = "C_ROTAL",
|
||||
P_RPHDP = "C_RPHDP", P_RPRTN = "C_RPRTN", P_RSSLL = "C_RSSLL",
|
||||
P_RTLMM = "C_RTLMM", P_RTYLA = "C_RTYLA", P_RUGID = "C_RUGID",
|
||||
F_RZLLP = "C_RZLLP", P_SAGRN = "C_SAGRN", P_SCCMM = "C_SCCMM",
|
||||
P_SCCRH = "C_SCCRH", P_SCHLM = "C_SCHLM", F_SCLRS = "C_SCLRS",
|
||||
P_SCTLR = "C_SCTLR", P_SEBRK = "C_SEBRK", P_SGMLN = "C_SGMLN",
|
||||
P_SGMLP = "C_SGMLP", P_SGMMR = "C_SGMMR", P_SGMVR = "C_SGMVR",
|
||||
F_SMMRS = "C_SMMRS", P_SNNDS = "C_SNNDS", P_SORTS = "C_SORTS",
|
||||
P_SPHGN = "C_SPHGN", P_SPHNN = "C_SPHNN", P_SNLLA = "C_SPHNNL",
|
||||
P_SPHTR = "C_SPHTR", P_SPHTX = "C_SPHTX", P_SPHVG = "C_SPHVG",
|
||||
P_SPRDT = "C_SPRDT", P_SPRLC = "C_SPRLC", F_SPRLG = "C_SPRLG",
|
||||
P_SPRLL = "C_SPRLL", F_SPRMY = "C_SPRMY", P_SPRPL = "C_SPRPL",
|
||||
P_SPRSG = "C_SPRSG", P_SPRST = "C_SPRST", P_SPHNP = "C_SPRTA",
|
||||
P_SPRZN = "C_SPRZN", P_SPHRG = "C_SPSNA", P_STHDM = "C_SPTHD",
|
||||
P_SRCNR = "C_SRCNR", F_SRLPD = "C_SRLPD", F_SPNGS = "C_SSPRA",
|
||||
F_STEIN = "C_STEIN", P_SPTHD = "C_STHDDS", P_STHRP = "C_STHRP",
|
||||
P_STNFR = "C_STNFR", P_STNSM = "C_STNSM", P_STNTR = "C_STNTR",
|
||||
P_STRBL = "C_STRBL", P_STRMB = "C_STRMB", P_STTSN = "C_STTSN",
|
||||
P_STYLN = "C_SYCHA", F_SCHZC = "C_SYTRM", P_TBNLL = "C_TBNLL",
|
||||
P_TRCHL = "C_TCHLS", P_TCHNT = "C_TCHNT", P_THRCL = "C_THRCL",
|
||||
P_THRMM = "C_THRMM", P_TIARN = "C_TIARN", P_TKPHR = "C_TKPHR",
|
||||
P_TLNMA = "C_TLNMA", P_TLYPM = "C_TLYPM", P_TMNDS = "C_TMNDS",
|
||||
P_TMNTA = "C_TMNTA", P_TNTNN = "C_TNNDM", P_TTNNS = "C_TNTNN",
|
||||
P_TNPSS = "C_TNTNNP", P_TONTN = "C_TONTN", P_TOSAI = "C_TOSAI",
|
||||
P_TPHTR = "C_TPHTR", P_TRCHH = "C_TRCHH", P_TRPHS = "C_TRCHLR",
|
||||
P_TMMNA = "C_TRCHM", P_TRCHS = "C_TRCHSP", P_TRFRN = "C_TRFRN",
|
||||
P_TRLCL = "C_TRLCL", P_TRTXL = "C_TRTXL", P_TRTXS = "C_TRTXS",
|
||||
P_TTRHY = "C_TTRHY", F_TTRMY = "C_TTRMY", P_TXTLR = "C_TXTLR",
|
||||
F_THRST = "C_TYTRM", P_URLPT = "C_ULPTS", P_UNGLT = "C_UNGLT",
|
||||
P_URCNT = "C_URCNT", P_URONM = "C_URONM", P_UROSM = "C_UROSM",
|
||||
P_URTRC = "C_URTRC", P_URSTY = "C_UTYLA", P_UVGRN = "C_UVGRN",
|
||||
P_VLVLN = "C_VALVLN", P_VGNLN = "C_VGNLN", P_VGNLNP = "C_VGNLNP",
|
||||
P_VLNRA = "C_VLVLN", P_VGNCL = "C_VNCLA", P_VRGLN = "C_VRGLN",
|
||||
P_VRGLNP = "C_VRGLNP", P_VRTCL = "C_VRTCL", P_WBBNL = "C_WBBNL",
|
||||
P_WEBBN = "C_WEBBN", P_WSNRL = "C_WSNRL", P_ZTHMN = "C_ZHMNM",
|
||||
B_ZOOGL = "C_ZOOGL", F_DDSCS = "F_DPDSC", F_SCCHR = "F_SMYCS",
|
||||
P_AMTRN = "P_ACNTH", F_AMBDM = "P_AMBDM", F_ARCYR = "P_ARCYR",
|
||||
F_BADHM = "P_BADHM", F_BDHMP = "P_BDHMP", F_BRBYL = "P_BRBYL",
|
||||
F_BRFLD = "P_BRFLD", F_CLMYX = "P_CLMYX", F_CLSTD = "P_CLSTD",
|
||||
F_CMTRC = "P_CMTRC", F_CRBRR = "P_CRBRR", F_CRTMY = "P_CRTMY",
|
||||
F_CRTRM = "P_CRTRM", F_DCTYD = "P_DCTYD", F_DDYMM = "P_DDYMM",
|
||||
F_DIACH = "P_DIACH", F_DIANM = "P_DIANM", F_DIDRM = "P_DIDRM",
|
||||
F_ELMYX = "P_ELMYX", F_ESTLM = "P_ESTLM", F_FULIG = "P_FULIG",
|
||||
F_HMTRC = "P_HMTRC", F_LCRPS = "P_LCRPS", F_LICEA = "P_LICEA",
|
||||
F_LMPRD = "P_LMPRD", F_LPTDR = "P_LPTDR", F_LSTRL = "P_LSTRL",
|
||||
F_LYCGL = "P_LYCGL", F_MCBRD = "P_MCBRD", F_MNKTL = "P_MNKTL",
|
||||
F_MTTRC = "P_MTTRC", F_MUCLG = "P_MUCLG", F_PHYSR = "P_PHYSR",
|
||||
F_PRCHN = "P_PRCHN", F_PRMBD = "P_PRMBD", F_PRTPH = "P_PRTPH",
|
||||
F_PSRNA = "P_PSRNA", F_PYSRM = "P_PYSRM", F_RTCLR = "P_RTCLR",
|
||||
F_STMNT = "P_STMNT", F_SYMPH = "P_SYMPH", F_TRBRK = "P_TRBRK",
|
||||
F_TRICH = "P_TRICH", F_TUBFR = "P_TUBFR",
|
||||
B_GRDNR = "B_GRLLA", B_SGMNS = "B_SNGMNS", B_TCLLS = "B_THBCL",
|
||||
F_CCCCS = "F_CRYPT",
|
||||
# renamings of old genus + species
|
||||
# putting full names here will throw notes with new taxonomic names
|
||||
F_CANDD_GLB = "F_CANDD_GLA", F_CANDD_KRU = "Candida krusei",
|
||||
F_CANDD_GUI = "Candida guilliermondii", F_HNSNL_ANO = "Hansenula anomala",
|
||||
F_CANDD_LUS = "Candida lusitaniae", B_STRPT_TUS = "B_STRPT",
|
||||
B_PRVTL_OLA = "B_PRVTL_OULO", B_FSBCT_RUM = "B_FSBCT",
|
||||
B_CRYNB_EYI = "B_CRYNB_FRE", B_OLGLL_LIS = "B_OLGLL_URE")
|
||||
}
|
||||
@@ -1,59 +1,226 @@
|
||||
% AMR (for R)
|
||||
|
||||
# `AMR` (for R)
|
||||
<img src="man/figures/logo.png" align="right" height="120px" />
|
||||
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/).
|
||||
|
||||
### Not a developer? Then please visit our website [https://msberends.gitlab.io/AMR](https://msberends.gitlab.io/AMR) to read about this package.
|
||||
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.
|
||||
|
||||
**It contains documentation about all of the included functions and also a comprehensive tutorial about how to conduct AMR analysis.**
|
||||
# Prerequisites
|
||||
|
||||
## Development source
|
||||
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:
|
||||
|
||||
*NOTE: the original source code is on GitLab (https://gitlab.com/msberends/AMR). There is a mirror repository on GitHub (https://github.com/msberends/AMR). As the mirror process is automated by GitLab, both repositories always contain the latest changes.*
|
||||
```python
|
||||
# linux and macOS:
|
||||
python -m venv /path/to/new/virtual/environment
|
||||
|
||||
This is the **development source** of `AMR`, a free and open-source [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods.
|
||||
# Windows:
|
||||
python -m venv C:\path\to\new\virtual\environment
|
||||
```
|
||||
|
||||
## Authors
|
||||
Matthijs S. Berends<sup>1,2</sup>,
|
||||
Christian F. Luz<sup>1</sup>,
|
||||
Alex W. Friedrich1</sup>,
|
||||
Bhanu N.M. Sinha<sup>1</sup>,
|
||||
Casper J. Albers<sup>3</sup>,
|
||||
Corinna Glasner<sup>1</sup>
|
||||
|
||||
<sup>1</sup> Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands - [rug.nl](http://www.rug.nl) [umcg.nl](http://www.umcg.nl)<br>
|
||||
<sup>2</sup> Certe Medical Diagnostics & Advice, Groningen, the Netherlands - [certe.nl](http://www.certe.nl)<br>
|
||||
<sup>3</sup> Heymans Institute for Psychological Research, University of Groningen, Groningen, the Netherlands - [rug.nl](http://www.rug.nl)<br>
|
||||
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.
|
||||
|
||||
<a href="https://www.rug.nl"><img src="man/figures/logo_rug.png" height="60px"></a>
|
||||
<a href="https://www.umcg.nl"><img src="man/figures/logo_umcg.png" height="60px"></a>
|
||||
<a href="https://www.certe.nl"><img src="man/figures/logo_certe.png" height="60px"></a>
|
||||
<a href="http://www.eurhealth-1health.eu"><img src="man/figures/logo_eh1h.png" height="60px"></a>
|
||||
<a href="http://www.eurhealth-1health.eu"><img src="man/figures/logo_interreg.png" height="60px"></a>
|
||||
# Install AMR
|
||||
|
||||
## How to get this package
|
||||
Please see [our website](https://msberends.gitlab.io/AMR/#get-this-package).
|
||||
1. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
|
||||
|
||||
## Copyright
|
||||
```bash
|
||||
pip install AMR
|
||||
```
|
||||
|
||||
This R package is licensed under the [GNU General Public License (GPL) v2.0](https://gitlab.com/msberends/AMR/blob/master/LICENSE). In a nutshell, this means that this package:
|
||||
2. Make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
|
||||
|
||||
- May be used for commercial purposes
|
||||
For Linux:
|
||||
|
||||
- May be used for private purposes
|
||||
```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.
|
||||
|
||||
- May **not** be used for patent purposes
|
||||
# Examples of Usage
|
||||
|
||||
- May be modified, although:
|
||||
## Cleaning Taxonomy
|
||||
|
||||
- Modifications **must** be released under the same license when distributing the package
|
||||
- Changes made to the code **must** be documented
|
||||
Here’s an example that demonstrates how to clean microorganism and drug names using the `AMR` Python package:
|
||||
|
||||
- May be distributed, although:
|
||||
```python
|
||||
import pandas as pd
|
||||
import AMR
|
||||
|
||||
- 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.
|
||||
# Sample data
|
||||
data = {
|
||||
"MOs": ['E. coli', 'ESCCOL', 'esco', 'Esche coli'],
|
||||
"Drug": ['Cipro', 'CIP', 'J01MA02', 'Ciproxin']
|
||||
}
|
||||
df = pd.DataFrame(data)
|
||||
|
||||
- Comes with a LIMITATION of liability
|
||||
# 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'])
|
||||
|
||||
- Comes with NO warranty
|
||||
# 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.
|
||||
-193
@@ -1,193 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
title: "AMR (for R)"
|
||||
url: "https://msberends.gitlab.io/AMR"
|
||||
|
||||
development:
|
||||
mode: "release" # improves indexing by search engines
|
||||
version_tooltip: "Latest development version"
|
||||
|
||||
news:
|
||||
one_page: true
|
||||
|
||||
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: "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 article
|
||||
- text: "Get properties of an antibiotic"
|
||||
icon: "fa-capsules"
|
||||
href: "reference/ab_property.html" # reference instead of article
|
||||
- text: "Other: benchmarks"
|
||||
icon: "fa-shipping-fast"
|
||||
href: "articles/benchmarks.html"
|
||||
- text: "Manual"
|
||||
icon: "fa-book-open"
|
||||
href: "reference/"
|
||||
- text: "Authors"
|
||||
icon: "fa-users"
|
||||
href: "authors.html"
|
||||
- text: "Changelog"
|
||||
icon: "far fa-newspaper"
|
||||
href: "news/"
|
||||
right:
|
||||
- text: "Source Code"
|
||||
icon: "fab fa-gitlab"
|
||||
href: "https://gitlab.com/msberends/AMR"
|
||||
- text: "Licence"
|
||||
icon: "fa-book"
|
||||
href: "LICENSE-text.html"
|
||||
|
||||
reference:
|
||||
- title: "Background information"
|
||||
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`"
|
||||
- "`catalogue_of_life`"
|
||||
- "`catalogue_of_life_version`"
|
||||
- "`WHOCC`"
|
||||
- title: "Cleaning your data"
|
||||
desc: >
|
||||
Functions for cleaning and optimising your data, to be able to add
|
||||
variables later on (like taxonomic properties) or to fix and extend
|
||||
antibiotic interpretations by applying [EUCAST rules](http://www.eucast.org/expert_rules_and_intrinsic_resistance/).
|
||||
contents:
|
||||
- starts_with("as.")
|
||||
- "`mo_source`"
|
||||
- "`eucast_rules`"
|
||||
- "`rsi_translation`"
|
||||
- "`guess_ab_col`"
|
||||
- "`read.4D`"
|
||||
- title: "Adding variables to your data"
|
||||
desc: >
|
||||
Functions to add new data to existing data, like the determination
|
||||
of first isolates, multi-drug resistant microorganisms (MDRO), getting
|
||||
properties of microorganisms or antibiotics and determining the age of
|
||||
patients or divide ages into age groups.
|
||||
contents:
|
||||
- "`first_isolate`"
|
||||
- "`mdro`"
|
||||
- "`key_antibiotics`"
|
||||
- "`mo_property`"
|
||||
- "`ab_property`"
|
||||
- "`age`"
|
||||
- "`age_groups`"
|
||||
- "`p_symbol`"
|
||||
- "`join`"
|
||||
- "`atc_online_property`"
|
||||
- title: "Analysing your data"
|
||||
desc: >
|
||||
Functions for conducting AMR analysis, like counting isolates, calculating
|
||||
resistance or susceptibility, or make plots.
|
||||
contents:
|
||||
- "`availability`"
|
||||
- "`bug_drug_combinations`"
|
||||
- "`count`"
|
||||
- "`portion`"
|
||||
- "`filter_ab_class`"
|
||||
- "`g.test`"
|
||||
- "`ggplot_rsi`"
|
||||
- "`kurtosis`"
|
||||
- "`resistance_predict`"
|
||||
- "`skewness`"
|
||||
- title: "Included data sets"
|
||||
desc: >
|
||||
References for microorganisms and antibiotics, and even a
|
||||
genuine data set with isolates from septic patients.
|
||||
contents:
|
||||
- "`antibiotics`"
|
||||
- "`microorganisms`"
|
||||
- "`example_isolates`"
|
||||
- "`WHONET`"
|
||||
- "`microorganisms.codes`"
|
||||
- "`microorganisms.old`"
|
||||
- title: Other 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:
|
||||
- "`get_locale`"
|
||||
- "`like`"
|
||||
- title: Extended functions
|
||||
desc: >
|
||||
These functions are extensions of functions in other packages.
|
||||
contents:
|
||||
- "`extended-functions`"
|
||||
- title: functions
|
||||
desc: >
|
||||
These functions are deprecated, meaning that they still
|
||||
work but show a warning with every use and will be removed
|
||||
in a future version.
|
||||
contents:
|
||||
- "`AMR-deprecated`"
|
||||
|
||||
authors:
|
||||
Matthijs S. Berends:
|
||||
href: https://www.rug.nl/staff/m.s.berends/
|
||||
Christian F. Luz:
|
||||
href: https://www.rug.nl/staff/c.f.luz/
|
||||
Alex W. Friedrich:
|
||||
href: https://www.rug.nl/staff/a.w.friedrich/
|
||||
Bhanu N. M. Sinha:
|
||||
href: https://www.rug.nl/staff/b.sinha/
|
||||
Casper J. Albers:
|
||||
href: https://www.rug.nl/staff/c.j.albers/
|
||||
Corinna Glasner:
|
||||
href: https://www.rug.nl/staff/c.glasner/
|
||||
|
||||
template:
|
||||
assets: "pkgdown/logos" # use logos in this folder
|
||||
params:
|
||||
noindex: false
|
||||
bootswatch: "flatly"
|
||||
docsearch:
|
||||
# using algolia.com
|
||||
api_key: "f737050abfd4d726c63938e18f8c496e"
|
||||
index_name: "amr"
|
||||
@@ -1,75 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://gitlab.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# 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. #
|
||||
# #
|
||||
# This R package was created for academic research and was publicly #
|
||||
# released in the hope that it will be useful, but it comes WITHOUT #
|
||||
# ANY WARRANTY OR LIABILITY. #
|
||||
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
|
||||
# ==================================================================== #
|
||||
|
||||
# Download script file from GitHub
|
||||
init:
|
||||
ps: |
|
||||
$ErrorActionPreference = "Stop"
|
||||
Invoke-WebRequest https://raw.githubusercontent.com/krlmlr/r-appveyor/master/scripts/appveyor-tool.ps1 -OutFile "..\appveyor-tool.ps1"
|
||||
Import-Module '..\appveyor-tool.ps1'
|
||||
|
||||
install:
|
||||
ps: Bootstrap
|
||||
|
||||
cache:
|
||||
- C:\RLibrary
|
||||
|
||||
# Adapt as necessary starting from here
|
||||
|
||||
environment:
|
||||
R_ARCH: x64
|
||||
GCC_PATH: mingw_64
|
||||
WARNINGS_ARE_ERRORS: 1
|
||||
PKGTYPE: win.binary
|
||||
# USE_RTOOLS: true
|
||||
|
||||
matrix:
|
||||
- R_VERSION: release
|
||||
- R_VERSION: devel
|
||||
|
||||
build_script:
|
||||
- travis-tool.sh install_deps
|
||||
|
||||
test_script:
|
||||
- travis-tool.sh run_tests
|
||||
|
||||
on_failure:
|
||||
- 7z a failure.zip *.Rcheck\*
|
||||
- appveyor PushArtifact failure.zip
|
||||
|
||||
artifacts:
|
||||
- path: '*.Rcheck\**\*.log'
|
||||
name: Logs
|
||||
|
||||
- path: '*.Rcheck\**\*.out'
|
||||
name: Logs
|
||||
|
||||
- path: '*.Rcheck\**\*.fail'
|
||||
name: Logs
|
||||
|
||||
- path: '*.Rcheck\**\*.Rout'
|
||||
name: Logs
|
||||
|
||||
- path: '\*_*.tar.gz'
|
||||
name: Bits
|
||||
|
||||
- path: '\*_*.zip'
|
||||
name: Bits
|
||||
-22
@@ -1,22 +0,0 @@
|
||||
codecov:
|
||||
notify:
|
||||
require_ci_to_pass: no # allow fail
|
||||
ci:
|
||||
- !appveyor # ignore CI builds by AppVeyor
|
||||
|
||||
comment: no
|
||||
|
||||
coverage:
|
||||
precision: 1
|
||||
round: up
|
||||
range: "0...100"
|
||||
status:
|
||||
project: no
|
||||
patch: no
|
||||
changes: no
|
||||
|
||||
ignore:
|
||||
- "R/atc_online.R"
|
||||
- "R/mo_source.R"
|
||||
- "R/resistance_predict.R"
|
||||
- "R/aa_test.R"
|
||||
@@ -1,5 +0,0 @@
|
||||
# Version 0.8.0
|
||||
|
||||
* A NOTE for having a data directory over 3 MB. This is needed to offer users reference data for the complete taxonomy of microorganisms - one of the most important features of this pacakge. Has been this way since version 0.3.0.
|
||||
|
||||
* This package writes lines to `[library path]/AMR/mo_history/mo_history.csv` when using the `as.mo()` function, in the exact same way (and borrowed from) the `extrafont` package on CRAN (version 0.17) writes to the user library path. Users are notified about this with a `message()`, and staged install on R >= 3.6.0 still works. The CSV file is never newly created or deleted by this package, it only changes this file to improve speed and reliability of the `as.mo()` function. See the source code of functions `set_mo_history()` and `clear_mo_history()` in file `R/mo_history.R`.
|
||||
Binary file not shown.
@@ -1,192 +0,0 @@
|
||||
# -------------------------------------------------------------------------------------------------------------------------------
|
||||
# For editing this EUCAST reference file, these values can all be used for target antibiotics:
|
||||
# 'all_betalactams', 'aminoglycosides', 'aminopenicillins', 'carbapenems', 'cephalosporins', 'cephalosporins_without_CAZ',
|
||||
# 'fluoroquinolones', 'glycopeptides', 'macrolides', 'polymyxins', 'streptogramins', 'tetracyclines', 'ureidopenicillins'
|
||||
# and all separate EARS-Net letter codes like 'AMC'. They can be separated by comma: 'AMC, fluoroquinolones'.
|
||||
# The 'if_mo_property' column can be any column name from the AMR::microorganisms data set, or "genus_species" or "gramstain".
|
||||
# The like.is.one_of column must be 'like' or 'is' or 'one_of' ('like' will read the 'this_value' column as regular expression)
|
||||
# The EUCAST guideline contains references to the 'Burkholderia cepacia complex'. All species in this group can be found in: LiPuma J, Curr Opin Pulm Med. 2005 Nov;11(6):528-33. (PMID 16217180).
|
||||
# >>>>> IF YOU WANT TO IMPORT THIS FILE INTO YOUR OWN SOFTWARE, HAVE THE FIRST 10 LINES SKIPPED <<<<<
|
||||
# -------------------------------------------------------------------------------------------------------------------------------
|
||||
if_mo_property like.is.one_of this_value and_these_antibiotics have_these_values then_change_these_antibiotics to_value reference.rule reference.rule_group
|
||||
order is Enterobacteriales AMP S AMX S Enterobacteriales (Order) Breakpoints
|
||||
order is Enterobacteriales AMP I AMX I Enterobacteriales (Order) Breakpoints
|
||||
order is Enterobacteriales AMP R AMX R Enterobacteriales (Order) Breakpoints
|
||||
genus is Staphylococcus PEN, FOX S AMP, AMX, PIP, TIC S Staphylococcus Breakpoints
|
||||
genus is Staphylococcus PEN, FOX R, S OXA, FLC S Staphylococcus Breakpoints
|
||||
genus is Staphylococcus FOX R all_betalactams R Staphylococcus Breakpoints
|
||||
genus_species is Staphylococcus saprophyticus AMP S AMX, AMC, PIP, TZP S Staphylococcus Breakpoints
|
||||
genus is Staphylococcus FOX S carbapenems, cephalosporins_without_CAZ S Staphylococcus Breakpoints
|
||||
genus is Staphylococcus FOX I carbapenems, cephalosporins_without_CAZ I Staphylococcus Breakpoints
|
||||
genus is Staphylococcus FOX R carbapenems, cephalosporins_without_CAZ R Staphylococcus Breakpoints
|
||||
genus is Staphylococcus NOR S CIP, LVX, MFX, OFX S Staphylococcus Breakpoints
|
||||
genus is Staphylococcus ERY S AZM, CLR, RXT S Staphylococcus Breakpoints
|
||||
genus is Staphylococcus ERY I AZM, CLR, RXT I Staphylococcus Breakpoints
|
||||
genus is Staphylococcus ERY R AZM, CLR, RXT R Staphylococcus Breakpoints
|
||||
genus is Staphylococcus TCY S DOX, MNO S Staphylococcus Breakpoints
|
||||
genus_species is Enterococcus faecium AMP R all_betalactams R Enterococcus Breakpoints
|
||||
genus is Enterococcus AMP S AMX, AMC, PIP, TZP S Enterococcus Breakpoints
|
||||
genus is Enterococcus AMP I AMX, AMC, PIP, TZP I Enterococcus Breakpoints
|
||||
genus is Enterococcus AMP R AMX, AMC, PIP, TZP R Enterococcus Breakpoints
|
||||
genus is Enterococcus NOR S CIP, LVX S Enterococcus Breakpoints
|
||||
genus is Enterococcus NOR I CIP, LVX I Enterococcus Breakpoints
|
||||
genus is Enterococcus NOR R CIP, LVX R Enterococcus Breakpoints
|
||||
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ PEN S aminopenicillins, ureidopenicillins, cephalosporins_without_CAZ, carbapenems, FLC, AMC S Streptococcus groups A, B, C, G Breakpoints
|
||||
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ PEN I aminopenicillins, ureidopenicillins, cephalosporins_without_CAZ, carbapenems, FLC, AMC I Streptococcus groups A, B, C, G Breakpoints
|
||||
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ PEN R aminopenicillins, ureidopenicillins, cephalosporins_without_CAZ, carbapenems, FLC, AMC R Streptococcus groups A, B, C, G Breakpoints
|
||||
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ NOR S LVX, MFX S Streptococcus groups A, B, C, G Breakpoints
|
||||
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ ERY S AZM, CLR, RXT S Streptococcus groups A, B, C, G Breakpoints
|
||||
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ ERY I AZM, CLR, RXT I Streptococcus groups A, B, C, G Breakpoints
|
||||
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ ERY R AZM, CLR, RXT R Streptococcus groups A, B, C, G Breakpoints
|
||||
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ TCY S DOX, MNO S Streptococcus groups A, B, C, G Breakpoints
|
||||
genus_species is Streptococcus pneumoniae PEN S AMP, AMX, AMC, PIP, TZP S Streptococcus pneumoniae Breakpoints
|
||||
genus_species is Streptococcus pneumoniae AMP S AMX, AMC, PIP, TZP S Streptococcus pneumoniae Breakpoints
|
||||
genus_species is Streptococcus pneumoniae AMP I AMX, AMC, PIP, TZP I Streptococcus pneumoniae Breakpoints
|
||||
genus_species is Streptococcus pneumoniae AMP R AMX, AMC, PIP, TZP R Streptococcus pneumoniae Breakpoints
|
||||
genus_species is Streptococcus pneumoniae NOR S LVX, MFX S Streptococcus pneumoniae Breakpoints
|
||||
genus_species is Streptococcus pneumoniae ERY S AZM, CLR, RXT S Streptococcus pneumoniae Breakpoints
|
||||
genus_species is Streptococcus pneumoniae ERY I AZM, CLR, RXT I Streptococcus pneumoniae Breakpoints
|
||||
genus_species is Streptococcus pneumoniae ERY R AZM, CLR, RXT R Streptococcus pneumoniae Breakpoints
|
||||
genus_species is Streptococcus pneumoniae TCY S DOX, MNO S Streptococcus pneumoniae Breakpoints
|
||||
genus_species like ^Streptococcus (australis|bovis|constellatus|cristatus|gallolyticus|gordonii|infantarius|infantis|mitis|mutans|oligofermentans|oralis|peroris|pseudopneumoniae|salivarius|sinensis|sobrinus|thermophilus|vestibularis|anginosus|equinus|intermedius|parasanguinis|sanguinis)$ PEN S AMP, AMX, AMC, PIP, TZP S Viridans group streptococci Breakpoints
|
||||
genus_species like ^Streptococcus (australis|bovis|constellatus|cristatus|gallolyticus|gordonii|infantarius|infantis|mitis|mutans|oligofermentans|oralis|peroris|pseudopneumoniae|salivarius|sinensis|sobrinus|thermophilus|vestibularis|anginosus|equinus|intermedius|parasanguinis|sanguinis)$ AMP S AMX, AMC, PIP, TZP S Viridans group streptococci Breakpoints
|
||||
genus_species like ^Streptococcus (australis|bovis|constellatus|cristatus|gallolyticus|gordonii|infantarius|infantis|mitis|mutans|oligofermentans|oralis|peroris|pseudopneumoniae|salivarius|sinensis|sobrinus|thermophilus|vestibularis|anginosus|equinus|intermedius|parasanguinis|sanguinis)$ AMP I AMX, AMC, PIP, TZP I Viridans group streptococci Breakpoints
|
||||
genus_species like ^Streptococcus (australis|bovis|constellatus|cristatus|gallolyticus|gordonii|infantarius|infantis|mitis|mutans|oligofermentans|oralis|peroris|pseudopneumoniae|salivarius|sinensis|sobrinus|thermophilus|vestibularis|anginosus|equinus|intermedius|parasanguinis|sanguinis)$ AMP R AMX, AMC, PIP, TZP R Viridans group streptococci Breakpoints
|
||||
genus_species is Haemophilus influenzae AMP S AMX, PIP S Haemophilus influenzae Breakpoints
|
||||
genus_species is ^Haemophilus influenzae AMP I AMX, PIP I Haemophilus influenzae Breakpoints
|
||||
genus_species is Haemophilus influenzae AMP R AMX, PIP R Haemophilus influenzae Breakpoints
|
||||
genus_species is Haemophilus influenzae PEN S AMP, AMX, AMC, PIP, TZP S Haemophilus influenzae Breakpoints
|
||||
genus_species is Haemophilus influenzae AMC S TZP S Haemophilus influenzae Breakpoints
|
||||
genus_species is Haemophilus influenzae AMC I TZP I Haemophilus influenzae Breakpoints
|
||||
genus_species is Haemophilus influenzae AMC R TZP R Haemophilus influenzae Breakpoints
|
||||
genus_species is Haemophilus influenzae NAL S CIP, LVX, MFX, OFX S Haemophilus influenzae Breakpoints
|
||||
genus_species is Haemophilus influenzae TCY S DOX, MNO S Haemophilus influenzae Breakpoints
|
||||
genus_species is Moraxella catarrhalis AMC S TZP S Moraxella catarrhalis Breakpoints
|
||||
genus_species is Moraxella catarrhalis AMC I TZP I Moraxella catarrhalis Breakpoints
|
||||
genus_species is Moraxella catarrhalis AMC R TZP R Moraxella catarrhalis Breakpoints
|
||||
genus_species is Moraxella catarrhalis NAL S CIP, LVX, MFX, OFX S Moraxella catarrhalis Breakpoints
|
||||
genus_species is Moraxella catarrhalis ERY S AZM, CLR, RXT S Moraxella catarrhalis Breakpoints
|
||||
genus_species is Moraxella catarrhalis ERY I AZM, CLR, RXT I Moraxella catarrhalis Breakpoints
|
||||
genus_species is Moraxella catarrhalis ERY R AZM, CLR, RXT R Moraxella catarrhalis Breakpoints
|
||||
genus_species is Moraxella catarrhalis TCY S DOX, MNO S Moraxella catarrhalis Breakpoints
|
||||
genus one_of Actinomyces, Bifidobacterium, Clostridium, Cutibacterium, Eggerthella, Eubacterium, Lactobacillus, Propionibacterium PEN S AMP, AMX, PIP, TZP, TIC S Anaerobic Gram-positives Breakpoints
|
||||
genus one_of Actinomyces, Bifidobacterium, Clostridium, Cutibacterium, Eggerthella, Eubacterium, Lactobacillus, Propionibacterium PEN I AMP, AMX, PIP, TZP, TIC I Anaerobic Gram-positives Breakpoints
|
||||
genus one_of Actinomyces, Bifidobacterium, Clostridium, Cutibacterium, Eggerthella, Eubacterium, Lactobacillus, Propionibacterium PEN R AMP, AMX, PIP, TZP, TIC R Anaerobic Gram-positives Breakpoints
|
||||
genus one_of Bacteroides, Bilophila , Fusobacterium, Mobiluncus, Porphyromonas, Prevotella PEN S AMP, AMX, PIP, TZP, TIC S Anaerobic Gram-negatives Breakpoints
|
||||
genus one_of Bacteroides, Bilophila , Fusobacterium, Mobiluncus, Porphyromonas, Prevotella PEN I AMP, AMX, PIP, TZP, TIC I Anaerobic Gram-negatives Breakpoints
|
||||
genus one_of Bacteroides, Bilophila , Fusobacterium, Mobiluncus, Porphyromonas, Prevotella PEN R AMP, AMX, PIP, TZP, TIC R Anaerobic Gram-negatives Breakpoints
|
||||
genus_species is Pasteurella multocida PEN S AMP, AMX S Pasteurella multocida Breakpoints
|
||||
genus_species is Pasteurella multocida PEN I AMP, AMX I Pasteurella multocida Breakpoints
|
||||
genus_species is Pasteurella multocida PEN R AMP, AMX R Pasteurella multocida Breakpoints
|
||||
genus_species is Campylobacter coli ERY S AZM, CLR S Campylobacter coli Breakpoints
|
||||
genus_species is Campylobacter coli ERY I AZM, CLR I Campylobacter coli Breakpoints
|
||||
genus_species is Campylobacter coli ERY R AZM, CLR R Campylobacter coli Breakpoints
|
||||
genus_species is Campylobacter coli TCY S DOX S Campylobacter coli Breakpoints
|
||||
genus_species is Campylobacter coli TCY I DOX I Campylobacter coli Breakpoints
|
||||
genus_species is Campylobacter coli TCY R DOX R Campylobacter coli Breakpoints
|
||||
genus_species is Campylobacter jejuni ERY S AZM, CLR S Campylobacter jejuni Breakpoints
|
||||
genus_species is Campylobacter jejuni ERY I AZM, CLR I Campylobacter jejuni Breakpoints
|
||||
genus_species is Campylobacter jejuni ERY R AZM, CLR R Campylobacter jejuni Breakpoints
|
||||
genus_species is Campylobacter jejuni TCY S DOX S Campylobacter jejuni Breakpoints
|
||||
genus_species is Campylobacter jejuni TCY I DOX I Campylobacter jejuni Breakpoints
|
||||
genus_species is Campylobacter jejuni TCY R DOX R Campylobacter jejuni Breakpoints
|
||||
genus_species is Aerococcus sanguinicola NOR S fluoroquinolones S Aerococcus sanguinicola Breakpoints
|
||||
genus_species is Aerococcus sanguinicola NOR I fluoroquinolones I Aerococcus sanguinicola Breakpoints
|
||||
genus_species is Aerococcus sanguinicola NOR R fluoroquinolones R Aerococcus sanguinicola Breakpoints
|
||||
genus_species is Aerococcus sanguinicola CIP S LVX S Aerococcus sanguinicola Breakpoints
|
||||
genus_species is Aerococcus sanguinicola CIP I LVX I Aerococcus sanguinicola Breakpoints
|
||||
genus_species is Aerococcus sanguinicola CIP R LVX R Aerococcus urinae Breakpoints
|
||||
genus_species is Aerococcus urinae NOR S fluoroquinolones S Aerococcus urinae Breakpoints
|
||||
genus_species is Aerococcus urinae NOR I fluoroquinolones I Aerococcus urinae Breakpoints
|
||||
genus_species is Aerococcus urinae NOR R fluoroquinolones R Aerococcus urinae Breakpoints
|
||||
genus_species is Aerococcus urinae CIP S LVX S Aerococcus urinae Breakpoints
|
||||
genus_species is Aerococcus urinae CIP I LVX I Aerococcus urinae Breakpoints
|
||||
genus_species is Aerococcus urinae CIP R LVX R Aerococcus urinae Breakpoints
|
||||
genus_species is Kingella kingae PEN S AMP, AMX S Kingella kingae Breakpoints
|
||||
genus_species is Kingella kingae PEN I AMP, AMX I Kingella kingae Breakpoints
|
||||
genus_species is Kingella kingae PEN R AMP, AMX R Kingella kingae Breakpoints
|
||||
genus_species is Kingella kingae ERY S AZM, CLR S Kingella kingae Breakpoints
|
||||
genus_species is Kingella kingae ERY I AZM, CLR I Kingella kingae Breakpoints
|
||||
genus_species is Kingella kingae ERY R AZM, CLR R Kingella kingae Breakpoints
|
||||
genus_species is Kingella kingae TCY S DOX S Kingella kingae Breakpoints
|
||||
family is Enterobacteriaceae PEN, glycopeptides, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
fullname like ^Citrobacter (koseri|amalonaticus|sedlakii|farmeri|rodentium) aminopenicillins, TIC R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
fullname like ^Citrobacter (freundii|braakii|murliniae|werkmanii|youngae) aminopenicillins, AMC, CZO, FOX R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Enterobacter cloacae aminopenicillins, AMC, CZO, FOX R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Enterobacter aerogenes aminopenicillins, AMC, CZO, FOX R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Escherichia hermanni aminopenicillins, TIC R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Hafnia alvei aminopenicillins, AMC, CZO, FOX R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus is Klebsiella aminopenicillins, TIC R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Morganella morganii aminopenicillins, AMC, CZO, tetracyclines, polymyxins, NIT R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Proteus mirabilis tetracyclines, TGC, polymyxins, NIT R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Proteus penneri aminopenicillins, CZO, CXM, tetracyclines, TGC, polymyxins, NIT R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Proteus vulgaris aminopenicillins, CZO, CXM, tetracyclines, TGC, polymyxins, NIT R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Providencia rettgeri aminopenicillins, AMC, CZO, CXM, tetracyclines, TGC, polymyxins, NIT R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Providencia stuartii aminopenicillins, AMC, CZO, CXM, tetracyclines, TGC, polymyxins, NIT R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus is Raoultella aminopenicillins, TIC R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Serratia marcescens aminopenicillins, AMC, CZO, FOX, CXM, DOX, TCY, polymyxins, NIT R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Yersinia enterocolitica aminopenicillins, AMC, TIC, CZO, FOX R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus_species is Yersinia pseudotuberculosis PLB, COL R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
|
||||
genus one_of Achromobacter, Acinetobacter, Alcaligenes, Bordatella, Burkholderia, Elizabethkingia, Flavobacterium, Ochrobactrum, Pseudomonas, Stenotrophomonas PEN, FOX, CXM, glycopeptides, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
|
||||
genus_species is Acinetobacter baumannii aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
|
||||
genus_species is Acinetobacter pittii aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
|
||||
genus_species is Acinetobacter nosocomialis aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
|
||||
genus_species is Acinetobacter calcoaceticus aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
|
||||
genus_species is Achromobacter xylosoxidans aminopenicillins, CZO, CTX, CRO, ETP R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
|
||||
fullname like ^Burkholderia (cepacia|multivorans|cenocepacia|stabilis|vietnamiensis|dolosa|ambifaria|anthina|pyrrocinia|ubonensis) aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, ATM, ETP, CIP, CHL, aminoglycosides, TMP, FOS, polymyxins R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
|
||||
genus_species is Elizabethkingia meningoseptica aminopenicillins, AMC, TIC, CZO, CTX, CRO, CAZ, FEP, ATM, ETP, IPM, MEM, polymyxins R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
|
||||
genus_species is Ochrobactrum anthropi aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
|
||||
genus_species is Pseudomonas aeruginosa aminopenicillins, AMC, CZO, CTX, CRO, ETP, CHL, KAN, NEO, TMP, SXT, tetracyclines, TGC R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
|
||||
genus_species is Stenotrophomonas maltophilia aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, CAZ, ATM, ETP, IPM, MEM, aminoglycosides, TMP, FOS, TCY R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
|
||||
genus one_of Haemophilus, Moraxella, Neisseria, Campylobacter glycopeptides, LIN, DAP, LNZ R Table 03: Intrinsic resistance in other Gram-negative bacteria Expert Rules
|
||||
genus_species is Haemophilus influenzae FUS, streptogramins R Table 03: Intrinsic resistance in other Gram-negative bacteria Expert Rules
|
||||
genus_species is Moraxella catarrhalis TMP R Table 03: Intrinsic resistance in other Gram-negative bacteria Expert Rules
|
||||
genus is Neisseria TMP R Table 03: Intrinsic resistance in other Gram-negative bacteria Expert Rules
|
||||
genus_species is Campylobacter fetus FUS, streptogramins, TMP, NAL R Table 03: Intrinsic resistance in other Gram-negative bacteria Expert Rules
|
||||
genus_species is Campylobacter jejuni FUS, streptogramins, TMP R Table 03: Intrinsic resistance in other Gram-negative bacteria Expert Rules
|
||||
genus_species is Campylobacter coli FUS, streptogramins, TMP R Table 03: Intrinsic resistance in other Gram-negative bacteria Expert Rules
|
||||
gramstain is Gram-positive ATM, polymyxins, NAL R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Staphylococcus saprophyticus FUS, CAZ, FOS, NOV R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Staphylococcus cohnii CAZ, NOV R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Staphylococcus xylosus CAZ, NOV R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Staphylococcus capitis CAZ, FOS R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Staphylococcus aureus CAZ R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Staphylococcus epidermidis CAZ R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Staphylococcus coagulase-negative CAZ R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Staphylococcus hominis CAZ R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Staphylococcus haemolyticus CAZ R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Staphylococcus intermedius CAZ R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Staphylococcus pseudintermedius CAZ R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus is Streptococcus FUS, CAZ, aminoglycosides R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Enterococcus faecalis FUS, CAZ, cephalosporins_without_CAZ, aminoglycosides, macrolides, CLI, QDA, TMP, SXT R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Enterococcus gallinarum FUS, CAZ, cephalosporins_without_CAZ, aminoglycosides, macrolides, CLI, QDA, VAN, TMP, SXT R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Enterococcus casseliflavus FUS, CAZ, cephalosporins_without_CAZ, aminoglycosides, macrolides, CLI, QDA, VAN, TMP, SXT R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Enterococcus faecium FUS, CAZ, cephalosporins_without_CAZ, aminoglycosides, macrolides, TMP, SXT R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus is Corynebacterium FOS R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Listeria monocytogenes cephalosporins R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus is Leuconostoc, Pediococcus glycopeptides R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus is Lactobacillus glycopeptides R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Clostridium ramosum VAN R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species is Clostridium innocuum VAN R Table 04: Intrinsic resistance in Gram-positive bacteria Expert Rules
|
||||
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G) PEN S aminopenicillins, cephalosporins_without_CAZ, carbapenems S Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci Expert Rules
|
||||
genus is Enterococcus AMP R ureidopenicillins, carbapenems R Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci Expert Rules
|
||||
genus is Enterococcus AMX R ureidopenicillins, carbapenems R Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci Expert Rules
|
||||
family is Enterobacteriaceae TIC, PIP R, S PIP R Table 09: Interpretive rules for B-lactam agents and Gram-negative rods Expert Rules
|
||||
genus is .* ERY S AZM, CLR S Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins Expert Rules
|
||||
genus is .* ERY I AZM, CLR I Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins Expert Rules
|
||||
genus is .* ERY R AZM, CLR R Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins Expert Rules
|
||||
genus is Staphylococcus TOB R KAN, AMK R Table 12: Interpretive rules for aminoglycosides Expert Rules
|
||||
genus is Staphylococcus GEN R aminoglycosides R Table 12: Interpretive rules for aminoglycosides Expert Rules
|
||||
family is Enterobacteriaceae GEN, TOB I, S GEN R Table 12: Interpretive rules for aminoglycosides Expert Rules
|
||||
family is Enterobacteriaceae GEN, TOB R, I TOB R Table 12: Interpretive rules for aminoglycosides Expert Rules
|
||||
genus is Staphylococcus MFX R fluoroquinolones R Table 13: Interpretive rules for quinolones Expert Rules
|
||||
genus_species is Streptococcus pneumoniae MFX R fluoroquinolones R Table 13: Interpretive rules for quinolones Expert Rules
|
||||
family is Enterobacteriaceae CIP R fluoroquinolones R Table 13: Interpretive rules for quinolones Expert Rules
|
||||
genus_species is Neisseria gonorrhoeae CIP R fluoroquinolones R Table 13: Interpretive rules for quinolones Expert Rules
|
||||
genus is .* AMC R AMP, AMX R Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R Other rules
|
||||
genus is .* TZP R PIP R Non-EUCAST: piperacillin = R where piperacillin/tazobactam = R Other rules
|
||||
genus is .* SXT R TMP R Non-EUCAST: trimethoprim = R where trimethoprim/sulfa = R Other rules
|
||||
genus is .* AMP S AMC S Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S Other rules
|
||||
genus is .* AMX S AMC S Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S Other rules
|
||||
genus is .* PIP S TZP S Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S Other rules
|
||||
genus is .* TMP S SXT S Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S Other rules
|
||||
|
Can't render this file because it contains an unexpected character in line 6 and column 96.
|
@@ -1,62 +0,0 @@
|
||||
# ---------------------------------------------------------------------------------------------------
|
||||
# For editing this EUCAST reference file, these values can all be used for target antibiotics:
|
||||
# all_betalactams, aminoglycosides, carbapenems, cephalosporins, cephalosporins_without_CAZ, fluoroquinolones,
|
||||
# glycopeptides, macrolides, minopenicillins, polymyxins, streptogramins, tetracyclines, ureidopenicillins
|
||||
# and all separate EARS-Net letter codes like AMC. They can be separated by comma: 'AMC, fluoroquinolones'.
|
||||
# The if_mo_property column can be any column name from the AMR::microorganisms data set, or "genus_species" or "gramstain".
|
||||
# The EUCAST guideline contains references to the 'Burkholderia cepacia complex'. All species in this group can be found in:
|
||||
# LiPuma J, Curr Opin Pulm Med. 2005 Nov;11(6):528-33. (PMID 16217180).
|
||||
# >>>>> IF YOU WANT TO IMPORT THIS FILE INTO YOUR OWN SOFTWARE, HAVE THE FIRST 10 LINES SKIPPED <<<<<
|
||||
# ---------------------------------------------------------------------------------------------------
|
||||
eucast_rules_file <- dplyr::arrange(
|
||||
.data = utils::read.delim(file = "data-raw/eucast_rules.tsv",
|
||||
skip = 10,
|
||||
sep = "\t",
|
||||
stringsAsFactors = FALSE,
|
||||
header = TRUE,
|
||||
strip.white = TRUE,
|
||||
na = c(NA, "", NULL)),
|
||||
reference.rule_group,
|
||||
reference.rule)
|
||||
|
||||
# Translations ----
|
||||
translations_file <- 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 = "")
|
||||
|
||||
# Old microorganism codes -------------------------------------------------
|
||||
|
||||
microorganisms.translation <- readRDS("data-raw/microorganisms.translation.rds")
|
||||
|
||||
# Export to package as internal data ----
|
||||
usethis::use_data(eucast_rules_file, translations_file, microorganisms.translation,
|
||||
internal = TRUE,
|
||||
overwrite = TRUE,
|
||||
version = 2)
|
||||
|
||||
# Remove from global environment ----
|
||||
rm(eucast_rules_file)
|
||||
rm(translations_file)
|
||||
rm(microorganisms.translation)
|
||||
|
||||
# Clean mo history ----
|
||||
usethis::ui_done(paste0("Resetting {usethis::ui_value('mo_history.csv')}"))
|
||||
tryCatch(
|
||||
write.csv(x = data.frame(x = character(0),
|
||||
mo = character(0),
|
||||
uncertainty_level = integer(0),
|
||||
package_version = character(0),
|
||||
stringsAsFactors = FALSE),
|
||||
row.names = FALSE,
|
||||
file = "inst/mo_history/mo_history.csv"),
|
||||
warning = function(w) cat("Warning:", w$message, "\n"),
|
||||
error = function(e) cat("Error:", e$message, "\n"))
|
||||
Binary file not shown.
@@ -1,356 +0,0 @@
|
||||
|
||||
library(dplyr)
|
||||
|
||||
# got EARS-Net codes (= ECDC/WHO codes) from here:
|
||||
|
||||
# Installed WHONET 2019 software on Windows (http://www.whonet.org/software.html),
|
||||
# opened C:\WHONET\Codes\WHONETCodes.mdb in MS Access
|
||||
# and exported table 'DRGLST' to MS Excel
|
||||
library(readxl)
|
||||
DRGLST <- read_excel("DRGLST.xlsx")
|
||||
abx <- DRGLST %>%
|
||||
select(ab = WHON5_CODE,
|
||||
name = ANTIBIOTIC) %>%
|
||||
# remove the ones without WHONET code
|
||||
filter(!is.na(ab)) %>%
|
||||
distinct(name, .keep_all = TRUE) %>%
|
||||
# add the ones without WHONET code
|
||||
bind_rows(
|
||||
DRGLST %>%
|
||||
select(ab = WHON5_CODE,
|
||||
name = ANTIBIOTIC) %>%
|
||||
filter(is.na(ab)) %>%
|
||||
distinct(name, .keep_all = TRUE)
|
||||
# add new ab code later
|
||||
) %>%
|
||||
arrange(name)
|
||||
|
||||
# add old ATC codes
|
||||
ab_old <- AMR::antibiotics %>%
|
||||
mutate(official = gsub("( and |, )", "/", official),
|
||||
abbr = tolower(paste(ifelse(is.na(abbr), "", abbr),
|
||||
ifelse(is.na(certe), "", certe),
|
||||
ifelse(is.na(umcg), "", umcg),
|
||||
sep = "|")))
|
||||
for (i in 1:nrow(ab_old)) {
|
||||
abbr <- ab_old[i, "abbr"]
|
||||
abbr <- strsplit(abbr, "|", fixed = TRUE) %>% unlist() %>% unique()
|
||||
abbr <- abbr[abbr != ""]
|
||||
#print(abbr)
|
||||
if (length(abbr) == 0) {
|
||||
ab_old[i, "abbr"] <- NA_character_
|
||||
} else {
|
||||
ab_old[i, "abbr"] <- paste(abbr, collapse = "|")
|
||||
}
|
||||
}
|
||||
|
||||
# create reference data set: to be able to map ab to atc
|
||||
abx_atc1 <- abx %>%
|
||||
mutate(name_lower = tolower(name)) %>%
|
||||
left_join(ab_old %>%
|
||||
select(ears_net, atc), by = c(ab = "ears_net")) %>%
|
||||
rename(atc1 = atc) %>%
|
||||
left_join(ab_old %>%
|
||||
mutate(official = gsub(", combinations", "", official, fixed = TRUE)) %>%
|
||||
transmute(official = tolower(official), atc), by = c(name_lower = "official")) %>%
|
||||
rename(atc2 = atc) %>%
|
||||
left_join(ab_old %>%
|
||||
mutate(official = gsub(", combinations", "", official, fixed = TRUE)) %>%
|
||||
mutate(official = gsub("f", "ph", official)) %>%
|
||||
transmute(official = tolower(official), atc), by = c(name_lower = "official")) %>%
|
||||
rename(atc3 = atc) %>%
|
||||
left_join(ab_old %>%
|
||||
mutate(official = gsub(", combinations", "", official, fixed = TRUE)) %>%
|
||||
mutate(official = gsub("t", "th", official)) %>%
|
||||
transmute(official = tolower(official), atc), by = c(name_lower = "official")) %>%
|
||||
rename(atc4 = atc) %>%
|
||||
left_join(ab_old %>%
|
||||
mutate(official = gsub(", combinations", "", official, fixed = TRUE)) %>%
|
||||
mutate(official = gsub("f", "ph", official)) %>%
|
||||
mutate(official = gsub("t", "th", official)) %>%
|
||||
transmute(official = tolower(official), atc), by = c(name_lower = "official")) %>%
|
||||
rename(atc5 = atc) %>%
|
||||
left_join(ab_old %>%
|
||||
mutate(official = gsub(", combinations", "", official, fixed = TRUE)) %>%
|
||||
mutate(official = gsub("f", "ph", official)) %>%
|
||||
mutate(official = gsub("t", "th", official)) %>%
|
||||
mutate(official = gsub("ine$", "in", official)) %>%
|
||||
transmute(official = tolower(official), atc), by = c(name_lower = "official")) %>%
|
||||
rename(atc6 = atc) %>%
|
||||
mutate(atc = case_when(!is.na(atc1) ~ atc1,
|
||||
!is.na(atc2) ~ atc2,
|
||||
!is.na(atc3) ~ atc3,
|
||||
!is.na(atc4) ~ atc4,
|
||||
!is.na(atc4) ~ atc5,
|
||||
TRUE ~ atc6)) %>%
|
||||
distinct(ab, name, .keep_all = TRUE) %>%
|
||||
select(ab, atc, name)
|
||||
|
||||
abx_atc2 <- ab_old %>%
|
||||
filter(!atc %in% abx_atc1$atc,
|
||||
is.na(ears_net),
|
||||
!is.na(atc_group1),
|
||||
!atc_group1 %like% ("virus|vaccin|viral|immun"),
|
||||
!official %like% "(combinations| with )") %>%
|
||||
mutate(ab = NA_character_) %>%
|
||||
as.data.frame(stringsAsFactors = FALSE) %>%
|
||||
select(ab, atc, name = official)
|
||||
|
||||
abx2 <- bind_rows(abx_atc1, abx_atc2)
|
||||
|
||||
rm(abx_atc1)
|
||||
rm(abx_atc2)
|
||||
|
||||
abx2$ab[is.na(abx2$ab)] <- toupper(abbreviate(gsub("[/0-9-]",
|
||||
" ",
|
||||
abx2$name[is.na(abx2$ab)]),
|
||||
minlength = 3,
|
||||
method = "left.kept",
|
||||
strict = TRUE))
|
||||
|
||||
n_distinct(abx2$ab)
|
||||
|
||||
abx2 <- abx2 %>% arrange(ab)
|
||||
seqnr <- 0
|
||||
# add follow up nrs
|
||||
for (i in 2:nrow(abx2)) {
|
||||
if (abx2[i, "ab"] == abx2[i - 1, "ab"]) {
|
||||
seqnr <- seqnr + 1
|
||||
abx2[i, "seqnr"] <- seqnr
|
||||
} else {
|
||||
seqnr <- 0
|
||||
}
|
||||
}
|
||||
for (i in 2:nrow(abx2)) {
|
||||
if (!is.na(abx2[i, "seqnr"])) {
|
||||
abx2[i, "ab"] <- paste0(abx2[i, "ab"], abx2[i, "seqnr"])
|
||||
}
|
||||
}
|
||||
abx2 <- abx2 %>% select(-seqnr) %>% arrange(name)
|
||||
|
||||
# everything unique??
|
||||
nrow(abx2) == n_distinct(abx2$ab)
|
||||
|
||||
# get ATC properties
|
||||
abx2 <- abx2 %>%
|
||||
left_join(ab_old %>%
|
||||
select(atc, abbr, atc_group1, atc_group2,
|
||||
oral_ddd, oral_units, iv_ddd, iv_units))
|
||||
|
||||
abx2$abbr <- lapply(as.list(abx2$abbr), function(x) unlist(strsplit(x, "|", fixed = TRUE)))
|
||||
|
||||
# vector with official names, returns vector with CIDs
|
||||
get_CID <- function(ab) {
|
||||
CID <- rep(NA_integer_, length(ab))
|
||||
p <- progress_estimated(n = length(ab), min_time = 0)
|
||||
for (i in 1:length(ab)) {
|
||||
p$tick()$print()
|
||||
|
||||
CID[i] <- tryCatch(
|
||||
data.table::fread(paste0("https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
|
||||
URLencode(ab[i], reserved = TRUE),
|
||||
"/cids/TXT?name_type=complete"),
|
||||
showProgress = FALSE)[[1]][1],
|
||||
error = function(e) NA_integer_)
|
||||
if (is.na(CID[i])) {
|
||||
# try with removing the text in brackets
|
||||
CID[i] <- tryCatch(
|
||||
data.table::fread(paste0("https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
|
||||
URLencode(trimws(gsub("[(].*[)]", "", ab[i])), reserved = TRUE),
|
||||
"/cids/TXT?name_type=complete"),
|
||||
showProgress = FALSE)[[1]][1],
|
||||
error = function(e) NA_integer_)
|
||||
}
|
||||
if (is.na(CID[i])) {
|
||||
# try match on word and take the lowest CID value (sorted)
|
||||
ab[i] <- gsub("[^a-z0-9]+", " ", ab[i], ignore.case = TRUE)
|
||||
CID[i] <- tryCatch(
|
||||
data.table::fread(paste0("https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
|
||||
URLencode(ab[i], reserved = TRUE),
|
||||
"/cids/TXT?name_type=word"),
|
||||
showProgress = FALSE)[[1]][1],
|
||||
error = function(e) NA_integer_)
|
||||
}
|
||||
Sys.sleep(0.1)
|
||||
}
|
||||
CID
|
||||
}
|
||||
|
||||
# get CIDs (2-3 min)
|
||||
CIDs <- get_CID(abx2$name)
|
||||
# These could not be found:
|
||||
abx2[is.na(CIDs),] %>% View()
|
||||
|
||||
# returns list with synonyms (brand names), with CIDs as names
|
||||
get_synonyms <- function(CID, clean = TRUE) {
|
||||
synonyms <- rep(NA_character_, length(CID))
|
||||
p <- progress_estimated(n = length(CID), min_time = 0)
|
||||
|
||||
for (i in 1:length(CID)) {
|
||||
p$tick()$print()
|
||||
|
||||
synonyms_txt <- ""
|
||||
|
||||
if (is.na(CID[i])) {
|
||||
next
|
||||
}
|
||||
|
||||
synonyms_txt <- tryCatch(
|
||||
data.table::fread(paste0("https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/fastidentity/cid/",
|
||||
CID[i],
|
||||
"/synonyms/TXT"),
|
||||
sep = "\n",
|
||||
showProgress = FALSE)[[1]],
|
||||
error = function(e) NA_character_)
|
||||
|
||||
Sys.sleep(0.1)
|
||||
|
||||
if (clean == TRUE) {
|
||||
# remove text between brackets
|
||||
synonyms_txt <- trimws(gsub("[(].*[)]", "",
|
||||
gsub("[[].*[]]", "",
|
||||
gsub("[(].*[]]", "",
|
||||
gsub("[[].*[)]", "", synonyms_txt)))))
|
||||
synonyms_txt <- gsub("Co-", "Co", synonyms_txt, fixed = TRUE)
|
||||
# only length 6 to 20 and no txt with reading marks or numbers and must start with capital letter (= brand)
|
||||
synonyms_txt <- synonyms_txt[nchar(synonyms_txt) %in% c(6:20)
|
||||
& !grepl("[-&{},_0-9/]", synonyms_txt)
|
||||
& grepl("^[A-Z]", synonyms_txt, ignore.case = FALSE)]
|
||||
synonyms_txt <- unlist(strsplit(synonyms_txt, ";", fixed = TRUE))
|
||||
}
|
||||
synonyms_txt <- unique(trimws(synonyms_txt[tolower(synonyms_txt) %in% unique(tolower(synonyms_txt))]))
|
||||
synonyms[i] <- list(sort(synonyms_txt))
|
||||
}
|
||||
names(synonyms) <- CID
|
||||
synonyms
|
||||
}
|
||||
|
||||
# get brand names from PubChem (2-3 min)
|
||||
synonyms <- get_synonyms(CIDs)
|
||||
synonyms <- lapply(synonyms,
|
||||
function(x) {
|
||||
if (length(x) == 0 | all(is.na(x))) {
|
||||
""
|
||||
} else {
|
||||
x
|
||||
}})
|
||||
|
||||
# add them to data set
|
||||
antibiotics <- abx2 %>%
|
||||
left_join(DRGLST %>%
|
||||
select(ab = WHON5_CODE, CLASS, SUBCLASS) %>%
|
||||
distinct(ab, .keep_all = TRUE), by = "ab") %>%
|
||||
transmute(ab,
|
||||
atc,
|
||||
cid = CIDs,
|
||||
# no capital after a slash: Ampicillin/Sulbactam -> Ampicillin/sulbactam
|
||||
name = name %>%
|
||||
gsub("([/-])([A-Z])", "\\1\\L\\2", ., perl = TRUE) %>%
|
||||
gsub("edta", "EDTA", ., ignore.case = TRUE),
|
||||
group = case_when(
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "am(ph|f)enicol" ~ "Amphenicols",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "aminoglycoside" ~ "Aminoglycosides",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "carbapenem" | name %like% "(imipenem|meropenem)" ~ "Carbapenems",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "First-generation cephalosporin" ~ "Cephalosporins (1st gen.)",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "Second-generation cephalosporin" ~ "Cephalosporins (2nd gen.)",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "Third-generation cephalosporin" ~ "Cephalosporins (3rd gen.)",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "Fourth-generation cephalosporin" ~ "Cephalosporins (4th gen.)",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "(tuberculosis|mycobacter)" ~ "Antimycobacterials",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "cephalosporin" ~ "Cephalosporins",
|
||||
name %like% "^Ce" & is.na(atc_group1) & paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "beta-?lactam" ~ "Cephalosporins",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "(beta-?lactam|penicillin)" ~ "Beta-lactams/penicillins",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "quinolone" ~ "Quinolones",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "glycopeptide" ~ "Glycopeptides",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "macrolide" ~ "Macrolides/lincosamides",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "tetracycline" ~ "Tetracyclines",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "trimethoprim" ~ "Trimethoprims",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "polymyxin" ~ "Polymyxins",
|
||||
paste(atc_group1, atc_group2, CLASS, SUBCLASS) %like% "(fungal|mycot)" ~ "Antifungals/antimycotics",
|
||||
TRUE ~ "Other antibacterials"
|
||||
),
|
||||
atc_group1, atc_group2,
|
||||
abbreviations = unname(abbr),
|
||||
synonyms = unname(synonyms),
|
||||
oral_ddd, oral_units,
|
||||
iv_ddd, iv_units) %>%
|
||||
as.data.frame(stringsAsFactors = FALSE)
|
||||
|
||||
# some exceptions
|
||||
antibiotics[which(antibiotics$ab == "DOX"), "abbreviations"][[1]] <- list(c("dox", "doxy"))
|
||||
antibiotics[which(antibiotics$ab == "FLC"), "abbreviations"][[1]] <- list(c("clox"))
|
||||
antibiotics[which(antibiotics$ab == "CEC"), "abbreviations"][[1]] <- list(c(antibiotics[which(antibiotics$ab == "CEC"), "abbreviations"][[1]], "CFC")) # cefaclor old WHONET4 code
|
||||
antibiotics[which(antibiotics$ab == "AMX"), "synonyms"][[1]] <- list(sort(c(antibiotics[which(antibiotics$ab == "AMX"), "synonyms"][[1]], "Amoxy")))
|
||||
# 'Polymixin B' (POL) and 'Polymyxin B' (PLB) both exist, so:
|
||||
antibiotics[which(antibiotics$ab == "PLB"), "abbreviations"][[1]] <- list(c(antibiotics[which(antibiotics$ab == "PLB"), "abbreviations"][[1]], "POL", "Polymixin", "Polymixin B"))
|
||||
antibiotics <- filter(antibiotics, ab != "POL")
|
||||
# 'Latamoxef' (LTM) and 'Moxalactam (Latamoxef)' (MOX) both exist, so:
|
||||
antibiotics[which(antibiotics$ab == "LTM"), "abbreviations"][[1]] <- list(c("MOX", "moxa"))
|
||||
antibiotics <- filter(antibiotics, ab != "MOX")
|
||||
# RFP and RFP1 (the J0 one) both mean 'rifapentine', although 'rifp' is not recognised, so:
|
||||
antibiotics <- filter(antibiotics, ab != "RFP")
|
||||
antibiotics[which(antibiotics$ab == "RFP1"), "ab"] <- "RFP"
|
||||
antibiotics[which(antibiotics$ab == "RFP"), "abbreviations"][[1]] <- list(c("rifp"))
|
||||
# Rifampicin is better known as a drug than Rifampin (Rifampin is still listed as a brand name), so:
|
||||
antibiotics[which(antibiotics$ab == "RIF"), "name"] <- "Rifampicin"
|
||||
# PME and PVM1 (the J0 one) both mean 'Pivmecillinam', so:
|
||||
antibiotics <- filter(antibiotics, ab != "PME")
|
||||
antibiotics[which(antibiotics$ab == "PVM1"), "ab"] <- "PME"
|
||||
# Remove Sinecatechins
|
||||
antibiotics <- filter(antibiotics, ab != "SNC")
|
||||
# ESBL E-test codes:
|
||||
antibiotics[which(antibiotics$ab == "CCV"), "abbreviations"][[1]] <- list(c("xtzl"))
|
||||
antibiotics[which(antibiotics$ab == "CAZ"), "abbreviations"][[1]] <- list(c(antibiotics[which(antibiotics$ab == "CAZ"), "abbreviations"][[1]], "xtz", "cefta"))
|
||||
antibiotics[which(antibiotics$ab == "CPC"), "abbreviations"][[1]] <- list(c("xpml"))
|
||||
antibiotics[which(antibiotics$ab == "FEP"), "abbreviations"][[1]] <- list(c(antibiotics[which(antibiotics$ab == "FEP"), "abbreviations"][[1]], "xpm"))
|
||||
antibiotics[which(antibiotics$ab == "CTC"), "abbreviations"][[1]] <- list(c("xctl"))
|
||||
antibiotics[which(antibiotics$ab == "CTX"), "abbreviations"][[1]] <- list(c(antibiotics[which(antibiotics$ab == "CTX"), "abbreviations"][[1]], "xct"))
|
||||
# High level Gentamcin and Streptomycin
|
||||
antibiotics[which(antibiotics$ab == "GEH"), "abbreviations"][[1]] <- list(c("gehl"))
|
||||
antibiotics[which(antibiotics$ab == "STH"), "abbreviations"][[1]] <- list(c("sthl"))
|
||||
|
||||
|
||||
antibiotics <- antibiotics %>% arrange(name)
|
||||
|
||||
# set cephalosporins groups for the ones that could not be determined automatically:
|
||||
antibiotics <- antibiotics %>%
|
||||
mutate(group = case_when(
|
||||
name == "Cefcapene" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefcapene pivoxil" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefditoren pivoxil" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefepime/clavulanic acid" ~ "Cephalosporins (4th gen.)",
|
||||
name == "Cefepime/tazobactam" ~ "Cephalosporins (4th gen.)",
|
||||
name == "Cefetamet pivoxil" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefetecol (Cefcatacol)" ~ "Cephalosporins (4th gen.)",
|
||||
name == "Cefetrizole" ~ "Cephalosporins (unclassified gen.)",
|
||||
name == "Cefoselis" ~ "Cephalosporins (4th gen.)",
|
||||
name == "Cefotaxime/clavulanic acid" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefotaxime/sulbactam" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefotiam hexetil" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefovecin" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefozopran" ~ "Cephalosporins (4th gen.)",
|
||||
name == "Cefpimizole" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefpodoxime proxetil" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefpodoxime/clavulanic acid" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefquinome" ~ "Cephalosporins (4th gen.)",
|
||||
name == "Cefsumide" ~ "Cephalosporins (unclassified gen.)",
|
||||
name == "Ceftaroline" ~ "Cephalosporins (5th gen.)",
|
||||
name == "Ceftaroline/avibactam" ~ "Cephalosporins (5th gen.)",
|
||||
name == "Ceftazidime/avibactam" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefteram" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Cefteram pivoxil" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Ceftiofur" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Ceftizoxime alapivoxil" ~ "Cephalosporins (3rd gen.)",
|
||||
name == "Ceftobiprole" ~ "Cephalosporins (5th gen.)",
|
||||
name == "Ceftobiprole medocaril" ~ "Cephalosporins (5th gen.)",
|
||||
name == "Ceftolozane/enzyme inhibitor" ~ "Cephalosporins (5th gen.)",
|
||||
name == "Ceftolozane/tazobactam" ~ "Cephalosporins (5th gen.)",
|
||||
name == "Cefuroxime axetil" ~ "Cephalosporins (2nd gen.)",
|
||||
TRUE ~ group))
|
||||
|
||||
# set as data.frame again
|
||||
antibiotics <- as.data.frame(antibiotics, stringsAsFactors = FALSE)
|
||||
class(antibiotics$ab) <- "ab"
|
||||
|
||||
dim(antibiotics) # for R/data.R
|
||||
usethis::use_data(antibiotics, overwrite = TRUE)
|
||||
rm(antibiotics)
|
||||
@@ -1,739 +0,0 @@
|
||||
# Reproduction of the `microorganisms` data set
|
||||
|
||||
# Data retrieved from the Catalogue of Life (CoL) through the Encyclopaedia of Life:
|
||||
# https://opendata.eol.org/dataset/catalogue-of-life/
|
||||
# (download the resource file with a name like "Catalogue of Life yyyy-mm-dd")
|
||||
# and from the Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures
|
||||
# https://www.dsmz.de/support/bacterial-nomenclature-up-to-date-downloads.html
|
||||
# (download the latest "Complete List" as xlsx file)
|
||||
|
||||
library(dplyr)
|
||||
library(AMR)
|
||||
|
||||
# unzip and extract taxon.tab (around 1.5 GB) from the CoL archive, then:
|
||||
data_col <- data.table::fread("data-raw/taxon.tab")
|
||||
|
||||
# read the xlsx file from DSMZ (only around 2.5 MB):
|
||||
data_dsmz <- readxl::read_xlsx("data-raw/DSMZ_bactnames.xlsx")
|
||||
|
||||
# the CoL data is over 3.7M rows:
|
||||
data_col %>% freq(kingdom)
|
||||
# Item Count Percent Cum. Count Cum. Percent
|
||||
# --- ---------- ---------- -------- ----------- -------------
|
||||
# 1 Animalia 2,225,627 59.1% 2,225,627 59.1%
|
||||
# 2 Plantae 1,177,412 31.3% 3,403,039 90.4%
|
||||
# 3 Fungi 290,145 7.7% 3,693,184 98.1%
|
||||
# 4 Chromista 47,126 1.3% 3,740,310 99.3%
|
||||
# 5 Bacteria 14,478 0.4% 3,754,788 99.7%
|
||||
# 6 Protozoa 6,060 0.2% 3,760,848 99.9%
|
||||
# 7 Viruses 3,827 0.1% 3,764,675 100.0%
|
||||
# 8 Archaea 610 0.0% 3,765,285 100.0%
|
||||
|
||||
# clean data_col
|
||||
data_col <- data_col %>%
|
||||
as_tibble() %>%
|
||||
select(col_id = taxonID,
|
||||
col_id_new = acceptedNameUsageID,
|
||||
fullname = scientificName,
|
||||
kingdom,
|
||||
phylum,
|
||||
class,
|
||||
order,
|
||||
family,
|
||||
genus,
|
||||
species = specificEpithet,
|
||||
subspecies = infraspecificEpithet,
|
||||
rank = taxonRank,
|
||||
ref = scientificNameAuthorship,
|
||||
species_id = furtherInformationURL)
|
||||
data_col$source <- "CoL"
|
||||
|
||||
# clean data_dsmz
|
||||
data_dsmz <- data_dsmz %>%
|
||||
as_tibble() %>%
|
||||
transmute(col_id = NA_integer_,
|
||||
col_id_new = NA_integer_,
|
||||
fullname = "",
|
||||
# kingdom = "",
|
||||
# phylum = "",
|
||||
# class = "",
|
||||
# order = "",
|
||||
# family = "",
|
||||
genus = ifelse(is.na(GENUS), "", GENUS),
|
||||
species = ifelse(is.na(SPECIES), "", SPECIES),
|
||||
subspecies = ifelse(is.na(SUBSPECIES), "", SUBSPECIES),
|
||||
rank = ifelse(species == "", "genus", "species"),
|
||||
ref = AUTHORS,
|
||||
species_id = as.character(RECORD_NO),
|
||||
source = "DSMZ")
|
||||
|
||||
# DSMZ only contains genus/(sub)species, try to find taxonomic properties based on genus and data_col
|
||||
ref_taxonomy <- data_col %>%
|
||||
filter(genus %in% data_dsmz$genus,
|
||||
family != "") %>%
|
||||
distinct(genus, .keep_all = TRUE) %>%
|
||||
select(kingdom, phylum, class, order, family, genus)
|
||||
|
||||
data_dsmz <- data_dsmz %>%
|
||||
left_join(ref_taxonomy, by = "genus") %>%
|
||||
mutate(kingdom = "Bacteria",
|
||||
phylum = ifelse(is.na(phylum), "(unknown phylum)", phylum),
|
||||
class = ifelse(is.na(class), "(unknown class)", class),
|
||||
order = ifelse(is.na(order), "(unknown order)", order),
|
||||
family = ifelse(is.na(family), "(unknown family)", family),
|
||||
)
|
||||
|
||||
# combine everything
|
||||
data_total <- data_col %>%
|
||||
bind_rows(data_dsmz)
|
||||
|
||||
rm(data_col)
|
||||
rm(data_dsmz)
|
||||
rm(ref_taxonomy)
|
||||
|
||||
mo_found_in_NL <- c("Absidia", "Acremonium", "Actinotignum", "Aedes", "Alternaria", "Anaerosalibacter", "Ancylostoma",
|
||||
"Angiostrongylus", "Anisakis", "Anopheles", "Apophysomyces", "Arachnia", "Ascaris", "Aspergillus",
|
||||
"Aureobacterium", "Aureobasidium", "Bacteroides", "Balantidum", "Basidiobolus", "Beauveria",
|
||||
"Bilophilia", "Blastocystis", "Branhamella", "Brochontrix", "Brugia", "Calymmatobacterium", "Candida", "Capillaria",
|
||||
"Capnocytophaga", "Catabacter", "Cdc", "Chaetomium", "Chilomastix", "Chryseobacterium",
|
||||
"Chryseomonas", "Chrysonilia", "Cladophialophora", "Cladosporium", "Clonorchis", "Conidiobolus",
|
||||
"Contracaecum", "Cordylobia", "Cryptococcus", "Curvularia", "Demodex", "Dermatobia", "Dicrocoelium",
|
||||
"Dioctophyma", "Diphyllobothrium", "Dipylidium", "Dirofilaria", "Dracunculus", "Echinococcus",
|
||||
"Echinostoma", "Elisabethkingia", "Enterobius", "Enteromonas", "Euascomycetes", "Exophiala",
|
||||
"Exserohilum", "Fasciola", "Fasciolopsis", "Flavobacterium", "Fonsecaea", "Fusarium", "Fusobacterium",
|
||||
"Giardia", "Gnathostoma", "Hendersonula", "Heterophyes", "Hymenolepis", "Hypomyces",
|
||||
"Hysterothylacium", "Kloeckera", "Koserella", "Larva", "Lecythophora", "Leishmania", "Lelliottia",
|
||||
"Leptomyxida", "Leptosphaeria", "Leptotrichia", "Loa", "Lucilia", "Lumbricus", "Malassezia",
|
||||
"Malbranchea", "Mansonella", "Mesocestoides", "Metagonimus", "Metarrhizium", "Molonomonas",
|
||||
"Mortierella", "Mucor", "Multiceps", "Mycocentrospora", "Mycoplasma", "Nanophetus", "Nattrassia",
|
||||
"Necator", "Nectria", "Novospingobium", "Ochroconis", "Oesophagostomum", "Oidiodendron", "Onchocerca",
|
||||
"Opisthorchis", "Opistorchis", "Paragonimus", "Paramyxovirus", "Pediculus", "Phlebotomus",
|
||||
"Phocanema", "Phoma", "Phthirus", "Piedraia", "Pithomyces", "Pityrosporum", "Prevotella",
|
||||
"Pseudallescheria", "Pseudoterranova", "Pulex", "Retortamonas", "Rhizomucor", "Rhizopus",
|
||||
"Rhodotorula", "Salinococcus", "Sanguibacteroides", "Sarcophagidae", "Sarcoptes", "Schistosoma",
|
||||
"Scolecobasidium", "Scopulariopsis", "Scytalidium", "Spirometra", "Sporobolomyces", "Stachybotrys",
|
||||
"Stenotrophomononas", "Stomatococcus", "Strongyloides", "Syncephalastraceae", "Syngamus", "Taenia",
|
||||
"Ternidens", "Torulopsis", "Toxocara", "Toxoplasma", "Treponema", "Trichinella", "Trichobilharzia", "Trichoderma",
|
||||
"Trichomonas", "Trichophyton", "Trichosporon", "Trichostrongylus", "Trichuris", "Tritirachium",
|
||||
"Trombicula", "Trypanosoma", "Tunga", "Ureaplasma", "Wuchereria")
|
||||
|
||||
MOs <- data_total %>%
|
||||
filter(
|
||||
(
|
||||
# we only want all MICROorganisms and no viruses
|
||||
!kingdom %in% c("Animalia", "Plantae", "Viruses")
|
||||
# and not all fungi: Aspergillus, Candida, Trichphyton and Pneumocystis are the most important,
|
||||
# so only keep these orders from the fungi:
|
||||
& !(kingdom == "Fungi"
|
||||
& !order %in% c("Eurotiales", "Microascales", "Mucorales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales", "Onygenales", "Pneumocystales"))
|
||||
)
|
||||
# or the genus has to be one of the genera we found in our hospitals last decades (Northern Netherlands, 2002-2018)
|
||||
| genus %in% mo_found_in_NL
|
||||
# or the taxonomic entry is old - the species was renamed
|
||||
| !is.na(col_id_new)
|
||||
) %>%
|
||||
# really no Plantae (e.g. Dracunculus exist both as worm and as plant)
|
||||
filter(kingdom != "Plantae") %>%
|
||||
filter(!rank %in% c("kingdom", "phylum", "class", "order", "family", "genus"))
|
||||
|
||||
# include all ranks other than species for the included species
|
||||
MOs <- MOs %>% bind_rows(data_total %>%
|
||||
filter((kingdom %in% MOs$kingdom & rank == "kingdom")
|
||||
| (phylum %in% MOs$phylum & rank == "phylum")
|
||||
| (class %in% MOs$class & rank == "class")
|
||||
| (order %in% MOs$order & rank == "order")
|
||||
| (family %in% MOs$family & rank == "family")
|
||||
| (genus %in% MOs$genus & rank == "genus")))
|
||||
|
||||
# filter old taxonomic names so only the ones with an existing reference will be kept
|
||||
MOs <- MOs %>%
|
||||
filter(is.na(col_id_new) | (!is.na(col_id_new) & col_id_new %in% MOs$col_id))
|
||||
|
||||
MOs <- MOs %>%
|
||||
# remove text if it contains 'Not assigned' like phylum in viruses
|
||||
mutate_all(~gsub("(Not assigned|\\[homonym\\]|\\[mistake\\])", "", ., ignore.case = TRUE))
|
||||
|
||||
MOs <- MOs %>%
|
||||
# Only keep first author, e.g. transform 'Smith, Jones, 2011' to 'Smith et al., 2011':
|
||||
mutate(authors2 = iconv(ref, from = "UTF-8", to = "ASCII//TRANSLIT"),
|
||||
# remove leading and trailing brackets
|
||||
authors2 = gsub("^[(](.*)[)]$", "\\1", authors2),
|
||||
# only take part after brackets if there's a name
|
||||
authors2 = ifelse(grepl(".*[)] [a-zA-Z]+.*", authors2),
|
||||
gsub(".*[)] (.*)", "\\1", authors2),
|
||||
authors2),
|
||||
# get year from last 4 digits
|
||||
lastyear = as.integer(gsub(".*([0-9]{4})$", "\\1", authors2)),
|
||||
# can never be later than now
|
||||
lastyear = ifelse(lastyear > as.integer(format(Sys.Date(), "%Y")),
|
||||
NA,
|
||||
lastyear),
|
||||
# get authors without last year
|
||||
authors = gsub("(.*)[0-9]{4}$", "\\1", authors2),
|
||||
# remove nonsense characters from names
|
||||
authors = gsub("[^a-zA-Z,'& -]", "", authors),
|
||||
# remove trailing and leading spaces
|
||||
authors = trimws(authors),
|
||||
# only keep first author and replace all others by 'et al'
|
||||
authors = gsub("(,| and| et| &| ex| emend\\.?) .*", " et al.", authors),
|
||||
# et al. always with ending dot
|
||||
authors = gsub(" et al\\.?", " et al.", authors),
|
||||
authors = gsub(" ?,$", "", authors),
|
||||
# don't start with 'sensu' or 'ehrenb'
|
||||
authors = gsub("^(sensu|Ehrenb.?) ", "", authors, ignore.case = TRUE),
|
||||
# no initials, only surname
|
||||
authors = gsub("^([A-Z]+ )+", "", authors, ignore.case = FALSE),
|
||||
# combine author and year if year is available
|
||||
ref = ifelse(!is.na(lastyear),
|
||||
paste0(authors, ", ", lastyear),
|
||||
authors),
|
||||
# fix beginning and ending
|
||||
ref = gsub(", $", "", ref),
|
||||
ref = gsub("^, ", "", ref),
|
||||
ref = gsub("^(emend|et al.,?)", "", ref),
|
||||
ref = trimws(ref)
|
||||
)
|
||||
# a lot start with a lowercase character - fix that
|
||||
MOs$ref[!grepl("^d[A-Z]", MOs$ref)] <- gsub("^([a-z])", "\\U\\1", MOs$ref[!grepl("^d[A-Z]", MOs$ref)], perl = TRUE)
|
||||
# specific one for the French that are named dOrbigny
|
||||
MOs$ref[grepl("^d[A-Z]", MOs$ref)] <- gsub("^d", "d'", MOs$ref[grepl("^d[A-Z]", MOs$ref)])
|
||||
|
||||
# Remove non-ASCII characters (these are not allowed by CRAN)
|
||||
MOs <- MOs %>%
|
||||
lapply(iconv, from = "UTF-8", to = "ASCII//TRANSLIT") %>%
|
||||
as_tibble(stringsAsFactors = FALSE) %>%
|
||||
# remove invalid characters
|
||||
mutate_all(~gsub("[\"'`]+", "", .))
|
||||
|
||||
# Split old taxonomic names - they refer in the original data to a new `taxonID` with `acceptedNameUsageID`
|
||||
MOs.old <- MOs %>%
|
||||
filter(!is.na(col_id_new),
|
||||
ref != "",
|
||||
source != "DSMZ") %>%
|
||||
transmute(col_id,
|
||||
col_id_new,
|
||||
fullname =
|
||||
trimws(
|
||||
gsub("(.*)[(].*", "\\1",
|
||||
stringr::str_replace(
|
||||
string = fullname,
|
||||
pattern = stringr::fixed(authors2),
|
||||
replacement = "")) %>%
|
||||
gsub(" (var|f|subsp)[.]", "", .)),
|
||||
ref) %>%
|
||||
filter(!is.na(fullname)) %>%
|
||||
distinct(fullname, .keep_all = TRUE) %>%
|
||||
arrange(col_id)
|
||||
|
||||
MO.bak <- MOs
|
||||
|
||||
MOs <- MOs %>%
|
||||
filter(is.na(col_id_new) | source == "DSMZ") %>%
|
||||
transmute(col_id,
|
||||
fullname = trimws(case_when(rank == "family" ~ family,
|
||||
rank == "order" ~ order,
|
||||
rank == "class" ~ class,
|
||||
rank == "phylum" ~ phylum,
|
||||
rank == "kingdom" ~ kingdom,
|
||||
TRUE ~ paste(genus, species, subspecies))),
|
||||
kingdom,
|
||||
phylum,
|
||||
class,
|
||||
order,
|
||||
family,
|
||||
genus = gsub(":", "", genus),
|
||||
species,
|
||||
subspecies,
|
||||
rank,
|
||||
ref,
|
||||
species_id = gsub(".*/([a-f0-9]+)", "\\1", species_id),
|
||||
source) %>%
|
||||
#distinct(fullname, .keep_all = TRUE) %>%
|
||||
filter(!grepl("unassigned", fullname, ignore.case = TRUE)) %>%
|
||||
# prefer DSMZ over CoL, since that's more recent
|
||||
arrange(desc(source)) %>%
|
||||
distinct(kingdom, fullname, .keep_all = TRUE)
|
||||
|
||||
# remove all genera that have no species - they are irrelevant for microbiology and almost all from the kingdom of Animalia
|
||||
to_remove <- MOs %>%
|
||||
filter(!kingdom %in% c("Bacteria", "Protozoa")) %>%
|
||||
group_by(kingdom, genus) %>%
|
||||
count() %>%
|
||||
filter(n == 1) %>%
|
||||
ungroup() %>%
|
||||
mutate(kingdom_genus = paste(kingdom, genus)) %>%
|
||||
pull(kingdom_genus)
|
||||
MOs <- MOs %>% filter(!(paste(kingdom, genus) %in% to_remove))
|
||||
rm(to_remove)
|
||||
|
||||
# add CoL's col_id, source and ref from MOs.bak, for the cases where DSMZ took preference
|
||||
MOs <- MOs %>%
|
||||
mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
|
||||
left_join(MO.bak %>%
|
||||
filter(is.na(col_id_new), !is.na(col_id)) %>%
|
||||
transmute(col_id, species_id, source, ref, kingdom_fullname = trimws(paste(kingdom, genus, species, subspecies))),
|
||||
by = "kingdom_fullname",
|
||||
suffix = c("_dsmz", "_col")) %>%
|
||||
mutate(col_id = col_id_col,
|
||||
species_id = ifelse(!is.na(species_id_col), gsub(".*/(.*)$", "\\1", species_id_col), species_id_dsmz),
|
||||
source = ifelse(!is.na(species_id_col), source_col, source_dsmz),
|
||||
ref = ifelse(!is.na(species_id_col) & ref_col != "", ref_col, ref_dsmz)) %>%
|
||||
select(-matches("(_col|_dsmz|kingdom_fullname)"))
|
||||
|
||||
|
||||
MOs.old <- MOs.old %>%
|
||||
# remove the ones that are in the MOs data set
|
||||
filter(col_id_new %in% MOs$col_id) %>%
|
||||
# and remove the ones that have the exact same fullname in the MOs data set, like Moraxella catarrhalis
|
||||
left_join(MOs, by = "fullname") %>%
|
||||
filter(col_id_new != col_id.y | is.na(col_id.y)) %>%
|
||||
select(col_id = col_id.x, col_id_new, fullname, ref = ref.x)
|
||||
|
||||
# remove the records that are in MOs.old
|
||||
sum(MOs.old$fullname %in% MOs$fullname)
|
||||
MOs <- MOs %>% filter(!fullname %in% MOs.old$fullname)
|
||||
sum(MOs.old$fullname %in% MOs$fullname)
|
||||
|
||||
# what characters are in the fullnames?
|
||||
table(sort(unlist(strsplit(x = paste(MOs$fullname, collapse = ""), split = ""))))
|
||||
|
||||
table(MOs$kingdom, MOs$rank)
|
||||
table(AMR::microorganisms$kingdom, AMR::microorganisms$rank)
|
||||
|
||||
# set prevalence per species
|
||||
MOs <- MOs %>%
|
||||
mutate(prevalence = case_when(
|
||||
class == "Gammaproteobacteria"
|
||||
| genus %in% c("Enterococcus", "Staphylococcus", "Streptococcus")
|
||||
~ 1,
|
||||
kingdom %in% c("Archaea", "Bacteria", "Chromista", "Fungi")
|
||||
& (phylum %in% c("Proteobacteria",
|
||||
"Firmicutes",
|
||||
"Actinobacteria",
|
||||
"Sarcomastigophora")
|
||||
| genus %in% mo_found_in_NL
|
||||
| rank %in% c("kingdom", "phylum", "class", "order", "family"))
|
||||
~ 2,
|
||||
TRUE ~ 3
|
||||
))
|
||||
|
||||
# Add abbreviations so we can easily know which ones are which ones.
|
||||
# These will become valid and unique microbial IDs for the AMR package.
|
||||
MOs <- MOs %>%
|
||||
arrange(prevalence, genus, species, subspecies) %>%
|
||||
group_by(kingdom) %>%
|
||||
mutate(abbr_other = case_when(
|
||||
rank == "family" ~ paste0("[FAM]_",
|
||||
abbreviate(family,
|
||||
minlength = 8,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides",
|
||||
strict = FALSE)),
|
||||
rank == "order" ~ paste0("[ORD]_",
|
||||
abbreviate(order,
|
||||
minlength = 8,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides",
|
||||
strict = FALSE)),
|
||||
rank == "class" ~ paste0("[CLS]_",
|
||||
abbreviate(class,
|
||||
minlength = 8,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides",
|
||||
strict = FALSE)),
|
||||
rank == "phylum" ~ paste0("[PHL]_",
|
||||
abbreviate(phylum,
|
||||
minlength = 8,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides",
|
||||
strict = FALSE)),
|
||||
rank == "kingdom" ~ paste0("[KNG]_", kingdom),
|
||||
TRUE ~ NA_character_
|
||||
)) %>%
|
||||
# abbreviations may be same for genera between kingdoms,
|
||||
# because each abbreviation starts with the the first character(s) of the kingdom
|
||||
mutate(abbr_genus = abbreviate(gsub("^ae", "\u00E6\u00E6", genus, ignore.case = TRUE), # keep a starting Latin ae
|
||||
minlength = 5,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides")) %>%
|
||||
ungroup() %>%
|
||||
group_by(genus) %>%
|
||||
# species abbreviations may be the same between genera
|
||||
# because the genus abbreviation is part of the abbreviation
|
||||
mutate(abbr_species = abbreviate(gsub("^ae", "\u00E6\u00E6", species),
|
||||
minlength = 4,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides")) %>%
|
||||
ungroup() %>%
|
||||
group_by(genus, species) %>%
|
||||
mutate(abbr_subspecies = abbreviate(gsub("^ae", "\u00E6\u00E6", subspecies),
|
||||
minlength = 4,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides")) %>%
|
||||
ungroup() %>%
|
||||
# remove trailing underscores
|
||||
mutate(mo = gsub("_+$", "",
|
||||
toupper(paste(ifelse(kingdom %in% c("Animalia", "Plantae"),
|
||||
substr(kingdom, 1, 2),
|
||||
substr(kingdom, 1, 1)),
|
||||
ifelse(is.na(abbr_other),
|
||||
paste(abbr_genus,
|
||||
abbr_species,
|
||||
abbr_subspecies,
|
||||
sep = "_"),
|
||||
abbr_other),
|
||||
sep = "_"))),
|
||||
mo = gsub("(\u00C6|\u00E6)+", "AE", mo)) %>%
|
||||
mutate(mo = ifelse(duplicated(.$mo),
|
||||
# these one or two must be unique too
|
||||
paste0(mo, "1"),
|
||||
mo),
|
||||
fullname = ifelse(fullname == "",
|
||||
trimws(paste(genus, species, subspecies)),
|
||||
fullname)) %>%
|
||||
# put `mo` in front, followed by the rest
|
||||
select(mo, everything(), -abbr_other, -abbr_genus, -abbr_species, -abbr_subspecies)
|
||||
|
||||
# add non-taxonomic entries
|
||||
MOs <- MOs %>%
|
||||
bind_rows(
|
||||
# Unknowns
|
||||
data.frame(mo = "UNKNOWN",
|
||||
col_id = NA_integer_,
|
||||
fullname = "(unknown name)",
|
||||
kingdom = "(unknown kingdom)",
|
||||
phylum = "(unknown phylum)",
|
||||
class = "(unknown class)",
|
||||
order = "(unknown order)",
|
||||
family = "(unknown family)",
|
||||
genus = "(unknown genus)",
|
||||
species = "(unknown species)",
|
||||
subspecies = "(unknown subspecies)",
|
||||
rank = "(unknown rank)",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added",
|
||||
prevalence = 1,
|
||||
stringsAsFactors = FALSE),
|
||||
data.frame(mo = "B_GRAMN",
|
||||
col_id = NA_integer_,
|
||||
fullname = "(unknown Gram-negatives)",
|
||||
kingdom = "Bacteria",
|
||||
phylum = "(unknown phylum)",
|
||||
class = "(unknown class)",
|
||||
order = "(unknown order)",
|
||||
family = "(unknown family)",
|
||||
genus = "(unknown Gram-negatives)",
|
||||
species = "(unknown species)",
|
||||
subspecies = "(unknown subspecies)",
|
||||
rank = "species",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added",
|
||||
prevalence = 1,
|
||||
stringsAsFactors = FALSE),
|
||||
data.frame(mo = "B_GRAMP",
|
||||
col_id = NA_integer_,
|
||||
fullname = "(unknown Gram-positives)",
|
||||
kingdom = "Bacteria",
|
||||
phylum = "(unknown phylum)",
|
||||
class = "(unknown class)",
|
||||
order = "(unknown order)",
|
||||
family = "(unknown family)",
|
||||
genus = "(unknown Gram-positives)",
|
||||
species = "(unknown species)",
|
||||
subspecies = "(unknown subspecies)",
|
||||
rank = "species",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added",
|
||||
prevalence = 1,
|
||||
stringsAsFactors = FALSE),
|
||||
data.frame(mo = "F_YEAST",
|
||||
col_id = NA_integer_,
|
||||
fullname = "(unknown yeast)",
|
||||
kingdom = "Fungi",
|
||||
phylum = "(unknown phylum)",
|
||||
class = "(unknown class)",
|
||||
order = "(unknown order)",
|
||||
family = "(unknown family)",
|
||||
genus = "(unknown genus)",
|
||||
species = "(unknown species)",
|
||||
subspecies = "(unknown subspecies)",
|
||||
rank = "species",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added",
|
||||
prevalence = 2,
|
||||
stringsAsFactors = FALSE),
|
||||
data.frame(mo = "F_FUNGUS",
|
||||
col_id = NA_integer_,
|
||||
fullname = "(unknown fungus)",
|
||||
kingdom = "Fungi",
|
||||
phylum = "(unknown phylum)",
|
||||
class = "(unknown class)",
|
||||
order = "(unknown order)",
|
||||
family = "(unknown family)",
|
||||
genus = "(unknown genus)",
|
||||
species = "(unknown species)",
|
||||
subspecies = "(unknown subspecies)",
|
||||
rank = "species",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added",
|
||||
prevalence = 2,
|
||||
stringsAsFactors = FALSE),
|
||||
# CoNS
|
||||
MOs %>%
|
||||
filter(genus == "Staphylococcus", species == "epidermidis") %>% .[1,] %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_CONS", mo),
|
||||
col_id = NA_integer_,
|
||||
species = "coagulase-negative",
|
||||
fullname = "Coagulase-negative Staphylococcus (CoNS)",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
# CoPS
|
||||
MOs %>%
|
||||
filter(genus == "Staphylococcus", species == "epidermidis") %>% .[1,] %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_COPS", mo),
|
||||
col_id = NA_integer_,
|
||||
species = "coagulase-positive",
|
||||
fullname = "Coagulase-positive Staphylococcus (CoPS)",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
# Streptococci groups A, B, C, F, H, K
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "pyogenes") %>% .[1,] %>%
|
||||
# we can keep all other details, since S. pyogenes is the only member of group A
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPA", mo),
|
||||
species = "group A" ,
|
||||
fullname = "Streptococcus group A",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
# we can keep all other details, since S. agalactiae is the only member of group B
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPB", mo),
|
||||
species = "group B" ,
|
||||
fullname = "Streptococcus group B",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "dysgalactiae") %>% .[1,] %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPC", mo),
|
||||
col_id = NA_integer_,
|
||||
species = "group C" ,
|
||||
fullname = "Streptococcus group C",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPD", mo),
|
||||
col_id = NA_integer_,
|
||||
species = "group D" ,
|
||||
fullname = "Streptococcus group D",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPF", mo),
|
||||
col_id = NA_integer_,
|
||||
species = "group F" ,
|
||||
fullname = "Streptococcus group F",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPG", mo),
|
||||
col_id = NA_integer_,
|
||||
species = "group G" ,
|
||||
fullname = "Streptococcus group G",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPH", mo),
|
||||
col_id = NA_integer_,
|
||||
species = "group H" ,
|
||||
fullname = "Streptococcus group H",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPK", mo),
|
||||
col_id = NA_integer_,
|
||||
species = "group K" ,
|
||||
fullname = "Streptococcus group K",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
# Beta haemolytic Streptococci
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_HAEM", mo),
|
||||
col_id = NA_integer_,
|
||||
species = "beta-haemolytic" ,
|
||||
fullname = "Beta-haemolytic Streptococcus",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
# Viridans Streptococci
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_VIRI", mo),
|
||||
col_id = NA_integer_,
|
||||
species = "viridans" ,
|
||||
fullname = "Viridans Group Streptococcus (VGS)",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
# Milleri Streptococci
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_MILL", mo),
|
||||
col_id = NA_integer_,
|
||||
species = "milleri" ,
|
||||
fullname = "Milleri Group Streptococcus (MGS)",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
# Blastocystis hominis does not exist (it means 'got a Bastocystis from humans', PMID 15634993)
|
||||
# but let's be nice to the clinical people in microbiology
|
||||
MOs %>%
|
||||
filter(fullname == "Blastocystis") %>%
|
||||
mutate(mo = paste0(mo, "_HMNS"),
|
||||
fullname = paste(fullname, "hominis"),
|
||||
species = "hominis",
|
||||
col_id = NA,
|
||||
source = "manually added",
|
||||
ref = NA_character_,
|
||||
species_id = ""),
|
||||
# Trichomonas vaginalis is missing, same order as Dientamoeba
|
||||
MOs %>%
|
||||
filter(fullname == "Dientamoeba") %>%
|
||||
mutate(mo = gsub("(.*?)_.*", "\\1_THMNS", mo),
|
||||
col_id = NA,
|
||||
fullname = "Trichomonas",
|
||||
family = "Trichomonadidae",
|
||||
genus = "Trichomonas",
|
||||
source = "manually added",
|
||||
ref = "Donne, 1836",
|
||||
species_id = ""),
|
||||
MOs %>%
|
||||
filter(fullname == "Dientamoeba fragilis") %>%
|
||||
mutate(mo = gsub("(.*?)_.*", "\\1_THMNS_VAG", mo),
|
||||
col_id = NA,
|
||||
fullname = "Trichomonas vaginalis",
|
||||
family = "Trichomonadidae",
|
||||
genus = "Trichomonas",
|
||||
species = "vaginalis",
|
||||
source = "manually added",
|
||||
ref = "Donne, 1836",
|
||||
species_id = ""),
|
||||
MOs %>% # add family as such too
|
||||
filter(fullname == "Monocercomonadidae") %>%
|
||||
mutate(mo = gsub("(.*)_(.*)_.*", "\\1_\\2_TRCHMNDD", mo),
|
||||
col_id = NA,
|
||||
fullname = "Trichomonadidae",
|
||||
family = "Trichomonadidae",
|
||||
rank = "family",
|
||||
genus = "",
|
||||
species = "",
|
||||
source = "manually added",
|
||||
ref = "",
|
||||
species_id = ""),
|
||||
)
|
||||
|
||||
MOs <- MOs %>%
|
||||
group_by(kingdom) %>%
|
||||
distinct(fullname, .keep_all = TRUE) %>%
|
||||
ungroup() %>%
|
||||
filter(fullname != "")
|
||||
|
||||
# add prevalence to old taxonomic names
|
||||
MOs.old <- MOs.old %>%
|
||||
left_join(MOs %>% select(col_id, prevalence), by = c("col_id_new" = "col_id"))
|
||||
|
||||
# everything distinct?
|
||||
sum(duplicated(MOs$mo))
|
||||
sum(duplicated(MOs$fullname))
|
||||
colnames(MOs)
|
||||
|
||||
# here we welcome the new ones:
|
||||
MOs %>% arrange(fullname) %>% filter(!fullname %in% AMR::microorganisms$fullname) %>% View()
|
||||
MOs.old %>% arrange(fullname) %>% filter(!fullname %in% AMR::microorganisms.old$fullname) %>% View()
|
||||
# and the ones we lost:
|
||||
AMR::microorganisms %>% filter(!fullname %in% MOs$fullname) %>% View()
|
||||
# and these IDs have changed:
|
||||
old_new <- MOs %>%
|
||||
mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
|
||||
filter(kingdom_fullname %in% (AMR::microorganisms %>% mutate(kingdom_fullname = paste(kingdom, fullname)) %>% pull(kingdom_fullname))) %>%
|
||||
left_join(AMR::microorganisms %>% mutate(kingdom_fullname = paste(kingdom, fullname)) %>% select(mo, kingdom_fullname), by = "kingdom_fullname", suffix = c("_new", "_old")) %>%
|
||||
filter(mo_new != mo_old) %>%
|
||||
select(mo_old, mo_new, everything())
|
||||
old_new %>%
|
||||
View()
|
||||
# and these codes are now missing (which will throw a unit test error):
|
||||
AMR::microorganisms.codes %>% filter(!mo %in% MOs$mo)
|
||||
AMR::rsi_translation %>% filter(!mo %in% MOs$mo)
|
||||
AMR::microorganisms.translation %>% filter(!mo_new %in% MOs$mo)
|
||||
# this is how to fix it
|
||||
microorganisms.codes <- AMR::microorganisms.codes %>%
|
||||
left_join(MOs %>%
|
||||
mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
|
||||
left_join(AMR::microorganisms %>%
|
||||
mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
|
||||
select(mo, kingdom_fullname), by = "kingdom_fullname", suffix = c("_new", "_old")) %>%
|
||||
select(mo_old, mo_new),
|
||||
by = c("mo" = "mo_old")) %>%
|
||||
select(code, mo = mo_new) %>%
|
||||
filter(!is.na(mo))
|
||||
microorganisms.codes %>% filter(!mo %in% MOs$mo)
|
||||
|
||||
# arrange
|
||||
MOs <- MOs %>% arrange(fullname)
|
||||
MOs.old <- MOs.old %>% arrange(fullname)
|
||||
microorganisms.codes <- microorganisms.codes %>% arrange(code)
|
||||
|
||||
# transform
|
||||
MOs <- as.data.frame(MOs, stringsAsFactors = FALSE)
|
||||
MOs.old <- as.data.frame(MOs.old, stringsAsFactors = FALSE)
|
||||
microorganisms.codes <- as.data.frame(microorganisms.codes, stringsAsFactors = FALSE)
|
||||
class(MOs$mo) <- "mo"
|
||||
class(microorganisms.codes$mo) <- "mo"
|
||||
MOs$col_id <- as.integer(MOs$col_id)
|
||||
MOs.old$col_id <- as.integer(MOs.old$col_id)
|
||||
MOs.old$col_id_new <- as.integer(MOs.old$col_id_new)
|
||||
|
||||
# SAVE
|
||||
### for other server
|
||||
saveRDS(MOs, "microorganisms.rds")
|
||||
saveRDS(MOs.old, "microorganisms.old.rds")
|
||||
saveRDS(microorganisms.codes, "microorganisms.codes.rds")
|
||||
### for same server
|
||||
microorganisms <- MOs
|
||||
microorganisms.old <- MOs.old
|
||||
microorganisms.translation <- old_new %>% select(mo_old, mo_new)
|
||||
class(microorganisms.translation$mo_old) <- "mo"
|
||||
class(microorganisms.translation$mo_new) <- "mo"
|
||||
|
||||
# on the server, do:
|
||||
usethis::use_data(microorganisms, overwrite = TRUE, version = 2)
|
||||
usethis::use_data(microorganisms.old, overwrite = TRUE, version = 2)
|
||||
usethis::use_data(microorganisms.codes, overwrite = TRUE, version = 2)
|
||||
saveRDS(microorganisms.translation, file = "data-raw/microorganisms.translation.rds", version = 2) # this one will be covered in data-raw/internals.R
|
||||
rm(microorganisms)
|
||||
rm(microorganisms.old)
|
||||
rm(microorganisms.codes)
|
||||
rm(microorganisms.translation)
|
||||
devtools::load_all(".")
|
||||
|
||||
# TO DO AFTER THIS
|
||||
# * Update the year and dim()s in R/data.R
|
||||
# * Rerun data-raw/reproduction_of_rsi_translation.R
|
||||
# * Run unit tests
|
||||
@@ -1,661 +0,0 @@
|
||||
# ---------------------------------------------------------------------------------
|
||||
# Reproduction of the `microorganisms` data set
|
||||
# ---------------------------------------------------------------------------------
|
||||
# Data retrieved from:
|
||||
#
|
||||
# [1] Catalogue of Life (CoL) through the Encyclopaedia of Life
|
||||
# https://opendata.eol.org/dataset/catalogue-of-life/
|
||||
# * Download the resource file with a name like "Catalogue of Life yyyy-mm-dd"
|
||||
# * Extract "taxon.tab"
|
||||
#
|
||||
# [2] Global Biodiversity Information Facility (GBIF)
|
||||
# https://doi.org/10.15468/39omei
|
||||
# * Extract "Taxon.tsv"
|
||||
#
|
||||
# [3] Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ)
|
||||
# https://www.dsmz.de/support/bacterial-nomenclature-up-to-date-downloads.html
|
||||
# * Download the latest "Complete List" as xlsx file (DSMZ_bactnames.xlsx)
|
||||
# ---------------------------------------------------------------------------------
|
||||
|
||||
library(dplyr)
|
||||
library(AMR)
|
||||
|
||||
data_col <- data.table::fread("Documents/taxon.tab")
|
||||
data_gbif <- data.table::fread("Documents/Taxon.tsv")
|
||||
|
||||
# read the xlsx file from DSMZ (only around 2.5 MB):
|
||||
data_dsmz <- readxl::read_xlsx("Downloads/DSMZ_bactnames.xlsx")
|
||||
|
||||
# the CoL data is over 3.7M rows:
|
||||
data_col %>% freq(kingdom)
|
||||
# Item Count Percent Cum. Count Cum. Percent
|
||||
# --- ---------- ---------- -------- ----------- -------------
|
||||
# 1 Animalia 2,225,627 59.1% 2,225,627 59.1%
|
||||
# 2 Plantae 1,177,412 31.3% 3,403,039 90.4%
|
||||
# 3 Fungi 290,145 7.7% 3,693,184 98.1%
|
||||
# 4 Chromista 47,126 1.3% 3,740,310 99.3%
|
||||
# 5 Bacteria 14,478 0.4% 3,754,788 99.7%
|
||||
# 6 Protozoa 6,060 0.2% 3,760,848 99.9%
|
||||
# 7 Viruses 3,827 0.1% 3,764,675 100.0%
|
||||
# 8 Archaea 610 0.0% 3,765,285 100.0%
|
||||
|
||||
# the GBIF data is over 5.8M rows:
|
||||
data_gbif %>% freq(kingdom)
|
||||
# Item Count Percent Cum. Count Cum. Percent
|
||||
# --- --------------- ---------- -------- ----------- -------------
|
||||
# 1 Animalia 3,264,138 55.7% 3,264,138 55.7%
|
||||
# 2 Plantae 1,814,962 31.0% 5,079,100 86.7%
|
||||
# 3 Fungi 538,086 9.2% 5,617,186 95.9%
|
||||
# 4 Chromista 181,374 3.1% 5,798,560 99.0%
|
||||
# 5 Bacteria 24,048 0.4% 5,822,608 99.4%
|
||||
# 6 Protozoa 15,138 0.3% 5,837,746 99.7%
|
||||
# 7 incertae sedis 9,995 0.2% 5,847,741 99.8%
|
||||
# 8 Viruses 9,630 0.2% 5,857,371 100.0%
|
||||
# 9 Archaea 771 0.0% 5,858,142 100.0%
|
||||
|
||||
|
||||
# Clean up helper function ------------------------------------------------
|
||||
clean_new <- function(new) {
|
||||
new %>%
|
||||
# only the ones that have no new ID to refer to a newer name
|
||||
filter(is.na(col_id_new)) %>%
|
||||
filter(
|
||||
(
|
||||
# we only want all MICROorganisms and no viruses
|
||||
!kingdom %in% c("Animalia", "Chromista", "Plantae", "Viruses")
|
||||
# and not all fungi: Aspergillus, Candida, Trichphyton and Pneumocystis are the most important,
|
||||
# so only keep these orders from the fungi:
|
||||
& !(kingdom == "Fungi"
|
||||
& !order %in% c("Eurotiales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales", "Onygenales", "Pneumocystales"))
|
||||
)
|
||||
# or the family has to contain a genus we found in our hospitals last decades (Northern Netherlands, 2002-2018)
|
||||
| genus %in% c("Absidia", "Acremonium", "Actinotignum", "Alternaria", "Anaerosalibacter", "Ancylostoma", "Anisakis", "Apophysomyces",
|
||||
"Arachnia", "Ascaris", "Aureobacterium", "Aureobasidium", "Balantidum", "Bilophilia", "Branhamella", "Brochontrix",
|
||||
"Brugia", "Calymmatobacterium", "Catabacter", "Chilomastix", "Chryseomonas", "Cladophialophora", "Cladosporium",
|
||||
"Clonorchis", "Cordylobia", "Curvularia", "Demodex", "Dermatobia", "Diphyllobothrium", "Dracunculus", "Echinococcus",
|
||||
"Enterobius", "Euascomycetes", "Exophiala", "Fasciola", "Fusarium", "Hendersonula", "Hymenolepis", "Kloeckera",
|
||||
"Koserella", "Larva", "Leishmania", "Lelliottia", "Loa", "Lumbricus", "Malassezia", "Metagonimus", "Molonomonas",
|
||||
"Mucor", "Nattrassia", "Necator", "Novospingobium", "Onchocerca", "Opistorchis", "Paragonimus", "Paramyxovirus",
|
||||
"Pediculus", "Phoma", "Phthirus", "Pityrosporum", "Pseudallescheria", "Pulex", "Rhizomucor", "Rhizopus", "Rhodotorula",
|
||||
"Salinococcus", "Sanguibacteroides", "Schistosoma", "Scopulariopsis", "Scytalidium", "Sporobolomyces", "Stomatococcus",
|
||||
"Strongyloides", "Syncephalastraceae", "Taenia", "Torulopsis", "Trichinella", "Trichobilharzia", "Trichomonas",
|
||||
"Trichosporon", "Trichuris", "Trypanosoma", "Wuchereria")) %>%
|
||||
mutate(
|
||||
authors2 = iconv(ref, from = "UTF-8", to = "ASCII//TRANSLIT"),
|
||||
# remove leading and trailing brackets
|
||||
authors2 = gsub("^[(](.*)[)]$", "\\1", authors2),
|
||||
# only take part after brackets if there's a name
|
||||
authors2 = ifelse(grepl(".*[)] [a-zA-Z]+.*", authors2),
|
||||
gsub(".*[)] (.*)", "\\1", authors2),
|
||||
authors2),
|
||||
# get year from last 4 digits
|
||||
lastyear = as.integer(gsub(".*([0-9]{4})$", "\\1", authors2)),
|
||||
# can never be later than now
|
||||
lastyear = ifelse(lastyear > as.integer(format(Sys.Date(), "%Y")),
|
||||
NA,
|
||||
lastyear),
|
||||
# get authors without last year
|
||||
authors = gsub("(.*)[0-9]{4}$", "\\1", authors2),
|
||||
# remove nonsense characters from names
|
||||
authors = gsub("[^a-zA-Z,'& -]", "", authors),
|
||||
# remove trailing and leading spaces
|
||||
authors = trimws(authors),
|
||||
# only keep first author and replace all others by 'et al'
|
||||
authors = gsub("(,| and| et| &| ex| emend\\.?) .*", " et al.", authors),
|
||||
# et al. always with ending dot
|
||||
authors = gsub(" et al\\.?", " et al.", authors),
|
||||
authors = gsub(" ?,$", "", authors),
|
||||
# don't start with 'sensu' or 'ehrenb'
|
||||
authors = gsub("^(sensu|Ehrenb.?) ", "", authors, ignore.case = TRUE),
|
||||
# no initials, only surname
|
||||
authors = gsub("^([A-Z]+ )+", "", authors, ignore.case = FALSE),
|
||||
# combine author and year if year is available
|
||||
ref = ifelse(!is.na(lastyear),
|
||||
paste0(authors, ", ", lastyear),
|
||||
authors),
|
||||
# fix beginning and ending
|
||||
ref = gsub(", $", "", ref),
|
||||
ref = gsub("^, ", "", ref)) %>%
|
||||
# remove text if it contains 'Not assigned' like phylum in viruses
|
||||
mutate_all(~gsub("Not assigned", "", .)) %>%
|
||||
# Remove non-ASCII characters (these are not allowed by CRAN)
|
||||
lapply(iconv, from = "UTF-8", to = "ASCII//TRANSLIT") %>%
|
||||
as_tibble(stringsAsFactors = FALSE) %>%
|
||||
mutate(fullname = trimws(case_when(rank == "family" ~ family,
|
||||
rank == "order" ~ order,
|
||||
rank == "class" ~ class,
|
||||
rank == "phylum" ~ phylum,
|
||||
rank == "kingdom" ~ kingdom,
|
||||
TRUE ~ paste(genus, species, subspecies))))
|
||||
}
|
||||
clean_old <- function(old, new) {
|
||||
old %>%
|
||||
# only the ones that exist in the new data set
|
||||
filter(col_id_new %in% new$col_id) %>%
|
||||
mutate(
|
||||
authors2 = iconv(ref, from = "UTF-8", to = "ASCII//TRANSLIT"),
|
||||
# remove leading and trailing brackets
|
||||
authors2 = gsub("^[(](.*)[)]$", "\\1", authors2),
|
||||
# only take part after brackets if there's a name
|
||||
authors2 = ifelse(grepl(".*[)] [a-zA-Z]+.*", authors2),
|
||||
gsub(".*[)] (.*)", "\\1", authors2),
|
||||
authors2),
|
||||
# get year from last 4 digits
|
||||
lastyear = as.integer(gsub(".*([0-9]{4})$", "\\1", authors2)),
|
||||
# can never be later than now
|
||||
lastyear = ifelse(lastyear > as.integer(format(Sys.Date(), "%Y")),
|
||||
NA,
|
||||
lastyear),
|
||||
# get authors without last year
|
||||
authors = gsub("(.*)[0-9]{4}$", "\\1", authors2),
|
||||
# remove nonsense characters from names
|
||||
authors = gsub("[^a-zA-Z,'& -]", "", authors),
|
||||
# remove trailing and leading spaces
|
||||
authors = trimws(authors),
|
||||
# only keep first author and replace all others by 'et al'
|
||||
authors = gsub("(,| and| et| &| ex| emend\\.?) .*", " et al.", authors),
|
||||
# et al. always with ending dot
|
||||
authors = gsub(" et al\\.?", " et al.", authors),
|
||||
authors = gsub(" ?,$", "", authors),
|
||||
# don't start with 'sensu' or 'ehrenb'
|
||||
authors = gsub("^(sensu|Ehrenb.?) ", "", authors, ignore.case = TRUE),
|
||||
# no initials, only surname
|
||||
authors = gsub("^([A-Z]+ )+", "", authors, ignore.case = FALSE),
|
||||
# combine author and year if year is available
|
||||
ref = ifelse(!is.na(lastyear),
|
||||
paste0(authors, ", ", lastyear),
|
||||
authors),
|
||||
# fix beginning and ending
|
||||
ref = gsub(", $", "", ref),
|
||||
ref = gsub("^, ", "", ref)) %>%
|
||||
# remove text if it contains 'Not assigned' like phylum in viruses
|
||||
mutate_all(~gsub("Not assigned", "", .)) %>%
|
||||
# Remove non-ASCII characters (these are not allowed by CRAN)
|
||||
lapply(iconv, from = "UTF-8", to = "ASCII//TRANSLIT") %>%
|
||||
as_tibble(stringsAsFactors = FALSE) %>%
|
||||
select(col_id_new, fullname, ref, authors2) %>%
|
||||
left_join(new %>% select(col_id, fullname_new = fullname), by = c(col_id_new = "col_id")) %>%
|
||||
mutate(fullname = trimws(
|
||||
gsub("(.*)[(].*", "\\1",
|
||||
stringr::str_replace(
|
||||
string = fullname,
|
||||
pattern = stringr::fixed(authors2),
|
||||
replacement = "")) %>%
|
||||
gsub(" (var|f|subsp)[.]", "", .))) %>%
|
||||
select(-c("col_id_new", "authors2")) %>%
|
||||
filter(!is.na(fullname), !is.na(fullname_new)) %>%
|
||||
filter(fullname != fullname_new, !fullname %like% "^[?]")
|
||||
}
|
||||
|
||||
# clean CoL and GBIF ----
|
||||
# clean data_col
|
||||
data_col <- data_col %>%
|
||||
as_tibble() %>%
|
||||
select(col_id = taxonID,
|
||||
col_id_new = acceptedNameUsageID,
|
||||
fullname = scientificName,
|
||||
kingdom,
|
||||
phylum,
|
||||
class,
|
||||
order,
|
||||
family,
|
||||
genus,
|
||||
species = specificEpithet,
|
||||
subspecies = infraspecificEpithet,
|
||||
rank = taxonRank,
|
||||
ref = scientificNameAuthorship,
|
||||
species_id = furtherInformationURL) %>%
|
||||
mutate(source = "CoL")
|
||||
# split into old and new
|
||||
data_col.new <- data_col %>% clean_new()
|
||||
data_col.old <- data_col %>% clean_old(new = data_col.new)
|
||||
rm(data_col)
|
||||
|
||||
# clean data_gbif
|
||||
data_gbif <- data_gbif %>%
|
||||
as_tibble() %>%
|
||||
filter(
|
||||
# no uncertain taxonomic placements
|
||||
taxonRemarks != "doubtful",
|
||||
kingdom != "incertae sedis",
|
||||
taxonRank != "unranked") %>%
|
||||
transmute(col_id = taxonID,
|
||||
col_id_new = acceptedNameUsageID,
|
||||
fullname = scientificName,
|
||||
kingdom,
|
||||
phylum,
|
||||
class,
|
||||
order,
|
||||
family,
|
||||
genus,
|
||||
species = specificEpithet,
|
||||
subspecies = infraspecificEpithet,
|
||||
rank = taxonRank,
|
||||
ref = scientificNameAuthorship,
|
||||
species_id = as.character(parentNameUsageID)) %>%
|
||||
mutate(source = "GBIF")
|
||||
# split into old and new
|
||||
data_gbif.new <- data_gbif %>% clean_new()
|
||||
data_gbif.old <- data_gbif %>% clean_old(new = data_gbif.new)
|
||||
rm(data_gbif)
|
||||
|
||||
# put CoL and GBIF together ----
|
||||
MOs.new <- bind_rows(data_col.new,
|
||||
data_gbif.new) %>%
|
||||
mutate(taxonomic_tree_length = nchar(trimws(paste(kingdom, phylum, class, order, family, genus, species, subspecies)))) %>%
|
||||
arrange(desc(taxonomic_tree_length)) %>%
|
||||
distinct(fullname, .keep_all = TRUE) %>%
|
||||
select(-c("col_id_new", "authors2", "authors", "lastyear", "taxonomic_tree_length")) %>%
|
||||
arrange(fullname)
|
||||
MOs.old <- bind_rows(data_col.old,
|
||||
data_gbif.old) %>%
|
||||
distinct(fullname, .keep_all = TRUE) %>%
|
||||
arrange(fullname)
|
||||
|
||||
# clean up DSMZ ---
|
||||
data_dsmz <- data_dsmz %>%
|
||||
as_tibble() %>%
|
||||
transmute(col_id = NA_integer_,
|
||||
col_id_new = NA_integer_,
|
||||
fullname = "",
|
||||
# kingdom = "",
|
||||
# phylum = "",
|
||||
# class = "",
|
||||
# order = "",
|
||||
# family = "",
|
||||
genus = ifelse(is.na(GENUS), "", GENUS),
|
||||
species = ifelse(is.na(SPECIES), "", SPECIES),
|
||||
subspecies = ifelse(is.na(SUBSPECIES), "", SUBSPECIES),
|
||||
rank = ifelse(species == "", "genus", "species"),
|
||||
ref = AUTHORS,
|
||||
species_id = as.character(RECORD_NO),
|
||||
source = "DSMZ")
|
||||
|
||||
# DSMZ only contains genus/(sub)species, try to find taxonomic properties based on genus and data_col
|
||||
ref_taxonomy <- MOs.new %>%
|
||||
distinct(genus, .keep_all = TRUE) %>%
|
||||
filter(family != "") %>%
|
||||
filter(genus %in% data_dsmz$genus) %>%
|
||||
distinct(genus, .keep_all = TRUE) %>%
|
||||
select(kingdom, phylum, class, order, family, genus)
|
||||
|
||||
data_dsmz <- data_dsmz %>%
|
||||
left_join(ref_taxonomy, by = "genus") %>%
|
||||
mutate(kingdom = "Bacteria")
|
||||
|
||||
data_dsmz.new <- data_dsmz %>%
|
||||
clean_new() %>%
|
||||
distinct(fullname, .keep_all = TRUE) %>%
|
||||
select(colnames(MOs.new)) %>%
|
||||
arrange(fullname)
|
||||
|
||||
# combine everything ----
|
||||
MOs <- bind_rows(MOs.new,
|
||||
data_dsmz.new) %>%
|
||||
distinct(fullname, .keep_all = TRUE) %>%
|
||||
# not the ones that are old
|
||||
filter(!fullname %in% MOs.old$fullname) %>%
|
||||
arrange(fullname) %>%
|
||||
mutate(col_id = ifelse(source != "CoL", NA_integer_, col_id)) %>%
|
||||
filter(fullname != "")
|
||||
|
||||
rm(data_col.new)
|
||||
rm(data_col.old)
|
||||
rm(data_gbif.new)
|
||||
rm(data_gbif.old)
|
||||
rm(data_dsmz)
|
||||
rm(data_dsmz.new)
|
||||
rm(ref_taxonomy)
|
||||
rm(MOs.new)
|
||||
|
||||
MOs.bak <- MOs
|
||||
|
||||
# Trichomonas trick ----
|
||||
# for species in Trypanosoma and Trichomonas we observe al lot of taxonomic info missing
|
||||
MOs %>% filter(genus %in% c("Trypanosoma", "Trichomonas")) %>% View()
|
||||
MOs[which(MOs$genus == "Trypanosoma"), "kingdom"] <- MOs[which(MOs$fullname == "Trypanosoma"),]$kingdom
|
||||
MOs[which(MOs$genus == "Trypanosoma"), "phylum"] <- MOs[which(MOs$fullname == "Trypanosoma"),]$phylum
|
||||
MOs[which(MOs$genus == "Trypanosoma"), "class"] <- MOs[which(MOs$fullname == "Trypanosoma"),]$class
|
||||
MOs[which(MOs$genus == "Trypanosoma"), "order"] <- MOs[which(MOs$fullname == "Trypanosoma"),]$order
|
||||
MOs[which(MOs$genus == "Trypanosoma"), "family"] <- MOs[which(MOs$fullname == "Trypanosoma"),]$family
|
||||
MOs[which(MOs$genus == "Trichomonas"), "kingdom"] <- MOs[which(MOs$fullname == "Trichomonas"),]$kingdom
|
||||
MOs[which(MOs$genus == "Trichomonas"), "phylum"] <- MOs[which(MOs$fullname == "Trichomonas"),]$phylum
|
||||
MOs[which(MOs$genus == "Trichomonas"), "class"] <- MOs[which(MOs$fullname == "Trichomonas"),]$class
|
||||
MOs[which(MOs$genus == "Trichomonas"), "order"] <- MOs[which(MOs$fullname == "Trichomonas"),]$order
|
||||
MOs[which(MOs$genus == "Trichomonas"), "family"] <- MOs[which(MOs$fullname == "Trichomonas"),]$family
|
||||
|
||||
# fill taxonomic properties that are missing
|
||||
MOs <- MOs %>%
|
||||
mutate(phylum = ifelse(phylum %in% c(NA, ""), "(unknown phylum)", phylum),
|
||||
class = ifelse(class %in% c(NA, ""), "(unknown class)", class),
|
||||
order = ifelse(order %in% c(NA, ""), "(unknown order)", order),
|
||||
family = ifelse(family %in% c(NA, ""), "(unknown family)", family))
|
||||
|
||||
# Abbreviations ----
|
||||
# Add abbreviations so we can easily know which ones are which ones.
|
||||
# These will become valid and unique microbial IDs for the AMR package.
|
||||
MOs <- MOs %>%
|
||||
arrange(kingdom, fullname) %>%
|
||||
group_by(kingdom) %>%
|
||||
mutate(abbr_other = case_when(
|
||||
rank == "family" ~ paste0("[FAM]_",
|
||||
abbreviate(family,
|
||||
minlength = 8,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides",
|
||||
strict = FALSE)),
|
||||
rank == "order" ~ paste0("[ORD]_",
|
||||
abbreviate(order,
|
||||
minlength = 8,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides",
|
||||
strict = FALSE)),
|
||||
rank == "class" ~ paste0("[CLS]_",
|
||||
abbreviate(class,
|
||||
minlength = 8,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides",
|
||||
strict = FALSE)),
|
||||
rank == "phylum" ~ paste0("[PHL]_",
|
||||
abbreviate(phylum,
|
||||
minlength = 8,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides",
|
||||
strict = FALSE)),
|
||||
rank == "kingdom" ~ paste0("[KNG]_", kingdom),
|
||||
TRUE ~ NA_character_
|
||||
)) %>%
|
||||
# abbreviations determined per kingdom and family
|
||||
# becuase they are part of the abbreviation
|
||||
mutate(abbr_genus = abbreviate(genus,
|
||||
minlength = 7,
|
||||
use.classes = TRUE,
|
||||
method = "both.sides",
|
||||
strict = FALSE)) %>%
|
||||
ungroup() %>%
|
||||
group_by(genus) %>%
|
||||
# species abbreviations may be the same between genera
|
||||
# because the genus abbreviation is part of the abbreviation
|
||||
mutate(abbr_species = abbreviate(stringr::str_to_title(species),
|
||||
minlength = 3,
|
||||
use.classes = FALSE,
|
||||
method = "both.sides")) %>%
|
||||
ungroup() %>%
|
||||
group_by(genus, species) %>%
|
||||
mutate(abbr_subspecies = abbreviate(stringr::str_to_title(subspecies),
|
||||
minlength = 3,
|
||||
use.classes = FALSE,
|
||||
method = "both.sides")) %>%
|
||||
ungroup() %>%
|
||||
# remove trailing underscores
|
||||
mutate(mo = gsub("_+$", "",
|
||||
toupper(paste(
|
||||
# first character: kingdom
|
||||
ifelse(kingdom %in% c("Animalia", "Plantae"),
|
||||
substr(kingdom, 1, 2),
|
||||
substr(kingdom, 1, 1)),
|
||||
# next: genus, species, subspecies
|
||||
ifelse(is.na(abbr_other),
|
||||
paste(abbr_genus,
|
||||
abbr_species,
|
||||
abbr_subspecies,
|
||||
sep = "_"),
|
||||
abbr_other),
|
||||
sep = "_")))) %>%
|
||||
mutate(mo = ifelse(duplicated(.$mo),
|
||||
# these one or two must be unique too
|
||||
paste0(mo, "1"),
|
||||
mo),
|
||||
fullname = ifelse(fullname == "",
|
||||
trimws(paste(genus, species, subspecies)),
|
||||
fullname)) %>%
|
||||
# put `mo` in front, followed by the rest
|
||||
select(mo, everything(), -abbr_other, -abbr_genus, -abbr_species, -abbr_subspecies)
|
||||
|
||||
# add non-taxonomic entries
|
||||
MOs <- MOs %>%
|
||||
bind_rows(
|
||||
# Unknowns
|
||||
data.frame(mo = "UNKNOWN",
|
||||
col_id = NA_integer_,
|
||||
fullname = "(unknown name)",
|
||||
kingdom = "(unknown kingdom)",
|
||||
phylum = "(unknown phylum)",
|
||||
class = "(unknown class)",
|
||||
order = "(unknown order)",
|
||||
family = "(unknown family)",
|
||||
genus = "(unknown genus)",
|
||||
species = "(unknown species)",
|
||||
subspecies = "(unknown subspecies)",
|
||||
rank = "(unknown rank)",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added",
|
||||
stringsAsFactors = FALSE),
|
||||
data.frame(mo = "B_GRAMN",
|
||||
col_id = NA_integer_,
|
||||
fullname = "(unknown Gram-negatives)",
|
||||
kingdom = "Bacteria",
|
||||
phylum = "(unknown phylum)",
|
||||
class = "(unknown class)",
|
||||
order = "(unknown order)",
|
||||
family = "(unknown family)",
|
||||
genus = "(unknown Gram-negatives)",
|
||||
species = "(unknown species)",
|
||||
subspecies = "(unknown subspecies)",
|
||||
rank = "species",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added",
|
||||
stringsAsFactors = FALSE),
|
||||
data.frame(mo = "B_GRAMP",
|
||||
col_id = NA_integer_,
|
||||
fullname = "(unknown Gram-positives)",
|
||||
kingdom = "Bacteria",
|
||||
phylum = "(unknown phylum)",
|
||||
class = "(unknown class)",
|
||||
order = "(unknown order)",
|
||||
family = "(unknown family)",
|
||||
genus = "(unknown Gram-positives)",
|
||||
species = "(unknown species)",
|
||||
subspecies = "(unknown subspecies)",
|
||||
rank = "species",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added",
|
||||
stringsAsFactors = FALSE),
|
||||
# CoNS
|
||||
MOs %>%
|
||||
filter(genus == "Staphylococcus", species == "") %>% .[1,] %>%
|
||||
mutate(mo = paste(mo, "CNS", sep = "_"),
|
||||
rank = "species",
|
||||
col_id = NA_integer_,
|
||||
species = "coagulase-negative",
|
||||
fullname = "Coagulase-negative Staphylococcus (CoNS)",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
# CoPS
|
||||
MOs %>%
|
||||
filter(genus == "Staphylococcus", species == "") %>% .[1,] %>%
|
||||
mutate(mo = paste(mo, "CPS", sep = "_"),
|
||||
rank = "species",
|
||||
col_id = NA_integer_,
|
||||
species = "coagulase-positive",
|
||||
fullname = "Coagulase-positive Staphylococcus (CoPS)",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
# Streptococci groups A, B, C, F, H, K
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "pyogenes") %>% .[1,] %>%
|
||||
# we can keep all other details, since S. pyogenes is the only member of group A
|
||||
mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRA", sep = "_"),
|
||||
species = "group A" ,
|
||||
fullname = "Streptococcus group A"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
# we can keep all other details, since S. agalactiae is the only member of group B
|
||||
mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRB", sep = "_"),
|
||||
species = "group B" ,
|
||||
fullname = "Streptococcus group B"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "dysgalactiae") %>% .[1,] %>%
|
||||
mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRC", sep = "_"),
|
||||
col_id = NA_integer_,
|
||||
species = "group C" ,
|
||||
fullname = "Streptococcus group C",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRD", sep = "_"),
|
||||
col_id = NA_integer_,
|
||||
species = "group D" ,
|
||||
fullname = "Streptococcus group D",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRF", sep = "_"),
|
||||
col_id = NA_integer_,
|
||||
species = "group F" ,
|
||||
fullname = "Streptococcus group F",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRG", sep = "_"),
|
||||
col_id = NA_integer_,
|
||||
species = "group G" ,
|
||||
fullname = "Streptococcus group G",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRH", sep = "_"),
|
||||
col_id = NA_integer_,
|
||||
species = "group H" ,
|
||||
fullname = "Streptococcus group H",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "GRK", sep = "_"),
|
||||
col_id = NA_integer_,
|
||||
species = "group K" ,
|
||||
fullname = "Streptococcus group K",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added"),
|
||||
# Beta-haemolytic Streptococci
|
||||
MOs %>%
|
||||
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
|
||||
mutate(mo = paste(MOs[MOs$fullname == "Streptococcus",]$mo, "HAE", sep = "_"),
|
||||
col_id = NA_integer_,
|
||||
species = "beta-haemolytic" ,
|
||||
fullname = "Beta-haemolytic Streptococcus",
|
||||
ref = NA_character_,
|
||||
species_id = "",
|
||||
source = "manually added")
|
||||
)
|
||||
|
||||
|
||||
# everything distinct?
|
||||
sum(duplicated(MOs$mo))
|
||||
colnames(MOs)
|
||||
|
||||
# set prevalence per species
|
||||
MOs <- MOs %>%
|
||||
mutate(prevalence = case_when(
|
||||
class == "Gammaproteobacteria"
|
||||
| genus %in% c("Enterococcus", "Staphylococcus", "Streptococcus")
|
||||
| mo %in% c("UNKNOWN", "B_GRAMN", "B_GRAMP")
|
||||
~ 1,
|
||||
phylum %in% c("Proteobacteria",
|
||||
"Firmicutes",
|
||||
"Actinobacteria",
|
||||
"Sarcomastigophora")
|
||||
| genus %in% c("Aspergillus",
|
||||
"Bacteroides",
|
||||
"Candida",
|
||||
"Capnocytophaga",
|
||||
"Chryseobacterium",
|
||||
"Cryptococcus",
|
||||
"Elisabethkingia",
|
||||
"Flavobacterium",
|
||||
"Fusobacterium",
|
||||
"Giardia",
|
||||
"Leptotrichia",
|
||||
"Mycoplasma",
|
||||
"Prevotella",
|
||||
"Rhodotorula",
|
||||
"Treponema",
|
||||
"Trichophyton",
|
||||
"Trichomonas",
|
||||
"Ureaplasma")
|
||||
| rank %in% c("kingdom", "phylum", "class", "order", "family")
|
||||
~ 2,
|
||||
TRUE ~ 3
|
||||
))
|
||||
|
||||
# arrange
|
||||
MOs <- MOs %>% arrange(fullname)
|
||||
|
||||
# transform
|
||||
MOs <- as.data.frame(MOs, stringsAsFactors = FALSE)
|
||||
MOs.old <- as.data.frame(MOs.old, stringsAsFactors = FALSE)
|
||||
class(MOs$mo) <- "mo"
|
||||
MOs$col_id <- as.integer(MOs$col_id)
|
||||
|
||||
# get differences in MO codes between this data and the package version
|
||||
MO_diff <- AMR::microorganisms %>%
|
||||
mutate(pastedtext = paste(mo, fullname)) %>%
|
||||
filter(!pastedtext %in% (MOs %>% mutate(pastedtext = paste(mo, fullname)) %>% pull(pastedtext))) %>%
|
||||
select(mo_old = mo, fullname, pastedtext) %>%
|
||||
left_join(MOs %>%
|
||||
transmute(mo_new = mo, fullname_new = fullname, pastedtext = paste(mo, fullname)), "pastedtext") %>%
|
||||
select(mo_old, mo_new, fullname_new)
|
||||
|
||||
mo_diff2 <- AMR::microorganisms %>%
|
||||
select(mo, fullname) %>%
|
||||
left_join(MOs %>%
|
||||
select(mo, fullname),
|
||||
by = "fullname",
|
||||
suffix = c("_old", "_new")) %>%
|
||||
filter(mo_old != mo_new,
|
||||
#!mo_new %in% mo_old,
|
||||
!mo_old %like% "\\[")
|
||||
|
||||
mo_diff3 <- tibble(previous_old = names(AMR:::make_trans_tbl()),
|
||||
previous_new = AMR:::make_trans_tbl()) %>%
|
||||
left_join(AMR::microorganisms %>% select(mo, fullname), by = c(previous_new = "mo")) %>%
|
||||
left_join(MOs %>% select(mo_new = mo, fullname), by = "fullname")
|
||||
|
||||
# what did we win most?
|
||||
MOs %>% filter(!fullname %in% AMR::microorganisms$fullname) %>% freq(genus)
|
||||
# what did we lose most?
|
||||
AMR::microorganisms %>%
|
||||
filter(kingdom != "Chromista" & !fullname %in% MOs$fullname & !fullname %in% MOs.old$fullname) %>%
|
||||
freq(genus)
|
||||
|
||||
|
||||
# save
|
||||
saveRDS(MOs, "microorganisms.rds")
|
||||
saveRDS(MOs.old, "microorganisms.old.rds")
|
||||
|
||||
# on the server, do:
|
||||
usethis::use_data(microorganisms, overwrite = TRUE, version = 2)
|
||||
usethis::use_data(microorganisms.old, overwrite = TRUE, version = 2)
|
||||
rm(microorganisms)
|
||||
rm(microorganisms.old)
|
||||
|
||||
# TO DO AFTER THIS
|
||||
# * Update the year and dim()s in R/data.R
|
||||
# * Rerun data-raw/reproduction_of_rsi_translation.R
|
||||
# * Run unit tests
|
||||
@@ -1,55 +0,0 @@
|
||||
library(dplyr)
|
||||
library(readxl)
|
||||
|
||||
# Installed WHONET 2019 software on Windows (http://www.whonet.org/software.html),
|
||||
# opened C:\WHONET\Codes\WHONETCodes.mdb in MS Access
|
||||
# and exported table 'DRGLST1' to MS Excel
|
||||
DRGLST1 <- read_excel("data-raw/DRGLST1.xlsx")
|
||||
rsi_translation <- DRGLST1 %>%
|
||||
# only keep CLSI and EUCAST guidelines:
|
||||
filter(GUIDELINES %like% "^(CLSI|EUCST)") %>%
|
||||
# set a nice layout:
|
||||
transmute(guideline = gsub("([0-9]+)$", " 20\\1", gsub("EUCST", "EUCAST", GUIDELINES)),
|
||||
method = TESTMETHOD,
|
||||
mo = as.mo(ORG_CODE),
|
||||
ab = as.ab(WHON5_CODE),
|
||||
ref_tbl = REF_TABLE,
|
||||
dose_disk = POTENCY,
|
||||
S_disk = as.disk(DISK_S),
|
||||
R_disk = as.disk(DISK_R),
|
||||
S_mic = as.mic(MIC_S),
|
||||
R_mic = as.mic(MIC_R)) %>%
|
||||
filter(!is.na(mo) & !is.na(ab)) %>%
|
||||
arrange(desc(guideline), mo, ab)
|
||||
|
||||
print(mo_failures())
|
||||
|
||||
# create 2 tables: MIC and disk
|
||||
tbl_mic <- rsi_translation %>%
|
||||
filter(method == "MIC") %>%
|
||||
select(-ends_with("_disk")) %>%
|
||||
mutate(joinstring = paste(guideline, mo, ab))
|
||||
tbl_disk <- rsi_translation %>%
|
||||
filter(method == "DISK") %>%
|
||||
select(-S_mic, -R_mic) %>%
|
||||
mutate(joinstring = paste(guideline, mo, ab)) %>%
|
||||
select(joinstring, ends_with("_disk"))
|
||||
|
||||
# merge them so every record is a unique combination of method, mo and ab
|
||||
rsi_translation <- tbl_mic %>%
|
||||
left_join(tbl_disk,
|
||||
by = "joinstring") %>%
|
||||
select(-joinstring, -method) %>%
|
||||
as.data.frame(stringsAsFactors = FALSE) %>%
|
||||
# force classes again
|
||||
mutate(mo = as.mo(mo),
|
||||
ab = as.ab(ab),
|
||||
S_mic = as.mic(S_mic),
|
||||
R_mic = as.mic(R_mic),
|
||||
S_disk = as.disk(S_disk),
|
||||
R_disk = as.disk(R_disk))
|
||||
|
||||
# save to package
|
||||
usethis::use_data(rsi_translation, overwrite = TRUE)
|
||||
rm(rsi_translation)
|
||||
devtools::load_all(".")
|
||||
@@ -1,382 +0,0 @@
|
||||
lang pattern replacement fixed ignore.case
|
||||
de Coagulase-negative Staphylococcus Koagulase-negative Staphylococcus FALSE FALSE
|
||||
de Coagulase-positive Staphylococcus Koagulase-positive Staphylococcus FALSE FALSE
|
||||
de Beta-haemolytic Streptococcus Beta-hämolytischer Streptococcus FALSE FALSE
|
||||
de unknown Gram-negatives unbekannte Gramnegativen FALSE FALSE
|
||||
de unknown Gram-positives unbekannte Grampositiven FALSE FALSE
|
||||
de unknown name unbekannte Name FALSE FALSE
|
||||
de unknown kingdom unbekanntes Reich FALSE FALSE
|
||||
de unknown phylum unbekannter Stamm FALSE FALSE
|
||||
de unknown class unbekannte Klasse FALSE FALSE
|
||||
de unknown order unbekannte Ordnung FALSE FALSE
|
||||
de unknown family unbekannte Familie FALSE FALSE
|
||||
de unknown genus unbekannte Gattung FALSE FALSE
|
||||
de unknown species unbekannte Art FALSE FALSE
|
||||
de unknown subspecies unbekannte Unterart FALSE FALSE
|
||||
de unknown rank unbekannter Rang FALSE FALSE
|
||||
de CoNS KNS TRUE FALSE
|
||||
de CoPS KPS TRUE FALSE
|
||||
de Gram-negative Gramnegativ FALSE FALSE
|
||||
de Gram-positive Grampositiv FALSE FALSE
|
||||
de Bacteria Bakterien FALSE FALSE
|
||||
de Fungi Hefen/Pilze FALSE FALSE
|
||||
de Protozoa Protozoen FALSE FALSE
|
||||
de biogroup Biogruppe FALSE FALSE
|
||||
de biotype Biotyp FALSE FALSE
|
||||
de vegetative vegetativ FALSE FALSE
|
||||
de ([([ ]*?)group \\1Gruppe FALSE FALSE
|
||||
de ([([ ]*?)Group \\1Gruppe FALSE FALSE
|
||||
nl Coagulase-negative Staphylococcus Coagulase-negatieve Staphylococcus FALSE FALSE
|
||||
nl Coagulase-positive Staphylococcus Coagulase-positieve Staphylococcus FALSE FALSE
|
||||
nl Beta-haemolytic Streptococcus Beta-hemolytische Streptococcus FALSE FALSE
|
||||
nl unknown Gram-negatives onbekende Gram-negatieven FALSE FALSE
|
||||
nl unknown Gram-positives onbekende Gram-positieven FALSE FALSE
|
||||
nl unknown name onbekende naam FALSE FALSE
|
||||
nl unknown kingdom onbekend koninkrijk FALSE FALSE
|
||||
nl unknown phylum onbekend fylum FALSE FALSE
|
||||
nl unknown class onbekende klasse FALSE FALSE
|
||||
nl unknown order onbekende orde FALSE FALSE
|
||||
nl unknown family onbekende familie FALSE FALSE
|
||||
nl unknown genus onbekend geslacht FALSE FALSE
|
||||
nl unknown species onbekende soort FALSE FALSE
|
||||
nl unknown subspecies onbekende ondersoort FALSE FALSE
|
||||
nl unknown rank onbekende rang FALSE FALSE
|
||||
nl CoNS CNS TRUE FALSE
|
||||
nl CoPS CPS TRUE FALSE
|
||||
nl Gram-negative Gram-negatief FALSE FALSE
|
||||
nl Gram-positive Gram-positief FALSE FALSE
|
||||
nl Bacteria Bacteriën FALSE FALSE
|
||||
nl Fungi Schimmels/gisten FALSE FALSE
|
||||
nl Protozoa protozoën FALSE FALSE
|
||||
nl biogroup biogroep FALSE FALSE
|
||||
nl vegetative vegetatief FALSE FALSE
|
||||
nl ([([ ]*?)group \\1groep FALSE FALSE
|
||||
nl ([([ ]*?)Group \\1Groep FALSE FALSE
|
||||
nl antibiotic antibioticum FALSE FALSE
|
||||
nl Antibiotic Antibioticum FALSE FALSE
|
||||
nl Drug Middel FALSE FALSE
|
||||
nl drug middel FALSE FALSE
|
||||
es Coagulase-negative Staphylococcus Staphylococcus coagulasa negativo FALSE FALSE
|
||||
es Coagulase-positive Staphylococcus Staphylococcus coagulasa positivo FALSE FALSE
|
||||
es Beta-haemolytic Streptococcus Streptococcus Beta-hemolítico FALSE FALSE
|
||||
es unknown Gram-negatives Gram negativos desconocidos FALSE FALSE
|
||||
es unknown Gram-positives Gram positivos desconocidos FALSE FALSE
|
||||
es unknown name nombre desconocido FALSE FALSE
|
||||
es unknown kingdom reino desconocido FALSE FALSE
|
||||
es unknown phylum filo desconocido FALSE FALSE
|
||||
es unknown class clase desconocida FALSE FALSE
|
||||
es unknown order orden desconocido FALSE FALSE
|
||||
es unknown family familia desconocida FALSE FALSE
|
||||
es unknown genus género desconocido FALSE FALSE
|
||||
es unknown species especie desconocida FALSE FALSE
|
||||
es unknown subspecies subespecie desconocida FALSE FALSE
|
||||
es unknown rank rango desconocido FALSE FALSE
|
||||
es CoNS SCN TRUE FALSE
|
||||
es CoPS SCP TRUE FALSE
|
||||
es Gram-negative Gram negativo FALSE FALSE
|
||||
es Gram-positive Gram positivo FALSE FALSE
|
||||
es Bacteria Bacterias FALSE FALSE
|
||||
es Fungi Hongos FALSE FALSE
|
||||
es Protozoa Protozoarios FALSE FALSE
|
||||
es biogroup biogrupo FALSE FALSE
|
||||
es biotype biotipo FALSE FALSE
|
||||
es vegetative vegetativo FALSE FALSE
|
||||
es ([([ ]*?)group \\1grupo FALSE FALSE
|
||||
es ([([ ]*?)Group \\1Grupo FALSE FALSE
|
||||
it Coagulase-negative Staphylococcus Staphylococcus negativo coagulasi FALSE FALSE
|
||||
it Coagulase-positive Staphylococcus Staphylococcus positivo coagulasi FALSE FALSE
|
||||
it Beta-haemolytic Streptococcus Streptococcus Beta-emolitico FALSE FALSE
|
||||
it unknown Gram-negatives Gram negativi sconosciuti FALSE FALSE
|
||||
it unknown Gram-positives Gram positivi sconosciuti FALSE FALSE
|
||||
it unknown name nome sconosciuto FALSE FALSE
|
||||
it unknown kingdom regno sconosciuto FALSE FALSE
|
||||
it unknown phylum phylum sconosciuto FALSE FALSE
|
||||
it unknown class classe sconosciuta FALSE FALSE
|
||||
it unknown order ordine sconosciuto FALSE FALSE
|
||||
it unknown family famiglia sconosciuta FALSE FALSE
|
||||
it unknown genus genere sconosciuto FALSE FALSE
|
||||
it unknown species specie sconosciute FALSE FALSE
|
||||
it unknown subspecies sottospecie sconosciute FALSE FALSE
|
||||
it unknown rank grado sconosciuto FALSE FALSE
|
||||
it Gram-negative Gram negativo FALSE FALSE
|
||||
it Gram-positive Gram positivo FALSE FALSE
|
||||
it Bacteria Batteri FALSE FALSE
|
||||
it Fungi Fungo FALSE FALSE
|
||||
it Protozoa Protozoi FALSE FALSE
|
||||
it biogroup biogruppo FALSE FALSE
|
||||
it biotype biotipo FALSE FALSE
|
||||
it vegetative vegetativo FALSE FALSE
|
||||
it ([([ ]*?)group \\1gruppo FALSE FALSE
|
||||
it ([([ ]*?)Group \\1Gruppo FALSE FALSE
|
||||
fr Coagulase-negative Staphylococcus Staphylococcus à coagulase négative FALSE FALSE
|
||||
fr Coagulase-positive Staphylococcus Staphylococcus à coagulase positif FALSE FALSE
|
||||
fr Beta-haemolytic Streptococcus Streptococcus Bêta-hémolytique FALSE FALSE
|
||||
fr unknown Gram-negatives Gram négatifs inconnus FALSE FALSE
|
||||
fr unknown Gram-positives Gram positifs inconnus FALSE FALSE
|
||||
fr unknown name nom inconnu FALSE FALSE
|
||||
fr unknown kingdom règme inconnu FALSE FALSE
|
||||
fr unknown phylum embranchement inconnu FALSE FALSE
|
||||
fr unknown class classe inconnue FALSE FALSE
|
||||
fr unknown order ordre inconnu FALSE FALSE
|
||||
fr unknown family famille inconnue FALSE FALSE
|
||||
fr unknown genus genre inconnu FALSE FALSE
|
||||
fr unknown species espèce inconnue FALSE FALSE
|
||||
fr unknown subspecies sous-espèce inconnue FALSE FALSE
|
||||
fr unknown rank rang inconnu FALSE FALSE
|
||||
fr Gram-negative Gram négatif FALSE FALSE
|
||||
fr Gram-positive Gram positif FALSE FALSE
|
||||
fr Bacteria Bactéries FALSE FALSE
|
||||
fr Fungi Champignons FALSE FALSE
|
||||
fr Protozoa Protozoaires FALSE FALSE
|
||||
fr biogroup biogroupe FALSE FALSE
|
||||
fr vegetative végétatif FALSE FALSE
|
||||
fr ([([ ]*?)group \\1groupe FALSE FALSE
|
||||
fr ([([ ]*?)Group \\1Groupe FALSE FALSE
|
||||
pt Coagulase-negative Staphylococcus Staphylococcus coagulase negativo FALSE FALSE
|
||||
pt Coagulase-positive Staphylococcus Staphylococcus coagulase positivo FALSE FALSE
|
||||
pt Beta-haemolytic Streptococcus Streptococcus Beta-hemolítico FALSE FALSE
|
||||
pt unknown Gram-negatives Gram negativos desconhecidos FALSE FALSE
|
||||
pt unknown Gram-positives Gram positivos desconhecidos FALSE FALSE
|
||||
pt unknown name nome desconhecido FALSE FALSE
|
||||
pt unknown kingdom reino desconhecido FALSE FALSE
|
||||
pt unknown phylum filo desconhecido FALSE FALSE
|
||||
pt unknown class classe desconhecida FALSE FALSE
|
||||
pt unknown order ordem desconhecido FALSE FALSE
|
||||
pt unknown family família desconhecida FALSE FALSE
|
||||
pt unknown genus gênero desconhecido FALSE FALSE
|
||||
pt unknown species espécies desconhecida FALSE FALSE
|
||||
pt unknown subspecies subespécies desconhecida FALSE FALSE
|
||||
pt unknown rank classificação desconhecido FALSE FALSE
|
||||
pt Gram-negative Gram negativo FALSE FALSE
|
||||
pt Gram-positive Gram positivo FALSE FALSE
|
||||
pt Bacteria Bactérias FALSE FALSE
|
||||
pt Fungi Fungos FALSE FALSE
|
||||
pt Protozoa Protozoários FALSE FALSE
|
||||
pt biogroup biogrupo FALSE FALSE
|
||||
pt biotype biótipo FALSE FALSE
|
||||
pt vegetative vegetativo FALSE FALSE
|
||||
pt ([([ ]*?)group \\1grupo FALSE FALSE
|
||||
pt ([([ ]*?)Group \\1Grupo FALSE FALSE
|
||||
|
||||
de clavulanic acid Clavulansäure FALSE TRUE
|
||||
|
||||
nl 4-aminosalicylic acid 4-aminosalicylzuur
|
||||
nl Adefovir dipivoxil Adefovir
|
||||
nl Aldesulfone sodium Aldesulfon
|
||||
nl Amikacin Amikacine
|
||||
nl Amoxicillin Amoxicilline
|
||||
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|
||||
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|
||||
nl Ampicillin Ampicilline
|
||||
nl Ampicillin/beta-lactamase inhibitor Ampicilline/enzymremmer
|
||||
nl Anidulafungin Anidulafungine
|
||||
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|
||||
nl Azithromycin Azitromycine
|
||||
nl Azlocillin Azlocilline
|
||||
nl Bacampicillin Bacampicilline
|
||||
nl Bacitracin Bacitracine
|
||||
nl Benzathine benzylpenicillin Benzylpenicillinebenzathine
|
||||
nl Benzathine phenoxymethylpenicillin Fenoxymethylpenicillinebenzathine
|
||||
nl Benzylpenicillin Benzylpenicilline
|
||||
nl Calcium aminosalicylate Aminosalicylzuur
|
||||
nl Capreomycin Capreomycine
|
||||
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|
||||
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|
||||
nl Caspofungin Caspofungine
|
||||
nl Ce(f|ph)acetrile Cefacetril FALSE
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
nl Ce(f|ph)ixime Cefixim FALSE
|
||||
nl Ce(f|ph)menoxime Cefmenoxim FALSE
|
||||
nl Ce(f|ph)metazole Cefmetazol FALSE
|
||||
nl Ce(f|ph)odizime Cefodizim FALSE
|
||||
nl Ce(f|ph)onicid Cefonicide FALSE
|
||||
nl Ce(f|ph)operazone Cefoperazon FALSE
|
||||
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|
||||
nl Ce(f|ph)otaxime Cefotaxim FALSE
|
||||
nl Ce(f|ph)oxitin Cefoxitine FALSE
|
||||
nl Ce(f|ph)pirome Cefpirom FALSE
|
||||
nl Ce(f|ph)podoxime Cefpodoxim FALSE
|
||||
nl Ce(f|ph)radine Cefradine FALSE
|
||||
nl Ce(f|ph)sulodin Cefsulodine FALSE
|
||||
nl Ce(f|ph)tazidime Ceftazidim FALSE
|
||||
nl Ce(f|ph)tezole Ceftezol FALSE
|
||||
nl Ce(f|ph)tizoxime Ceftizoxim FALSE
|
||||
nl Ce(f|ph)triaxone Ceftriaxon FALSE
|
||||
nl Ce(f|ph)uroxime Cefuroxim FALSE
|
||||
nl Ce(f|ph)uroxime/metronidazole Cefuroxim/andere antibacteriele middelen FALSE
|
||||
nl Chloramphenicol Chlooramfenicol
|
||||
nl Chlortetracycline Chloortetracycline
|
||||
nl Cinoxacin Cinoxacine
|
||||
nl Ciprofloxacin Ciprofloxacine
|
||||
nl Clarithromycin Claritromycine
|
||||
nl Clavulanic acid Clavulaanzuur
|
||||
nl clavulanic acid clavulaanzuur
|
||||
nl Clindamycin Clindamycine
|
||||
nl Clometocillin Clometocilline
|
||||
nl Clotrimazole Clotrimazol
|
||||
nl Cloxacillin Cloxacilline
|
||||
nl Colistin Colistine
|
||||
nl Dapsone Dapson
|
||||
nl Daptomycin Daptomycine
|
||||
nl Dibekacin Dibekacine
|
||||
nl Dicloxacillin Dicloxacilline
|
||||
nl Dirithromycin Diritromycine
|
||||
nl Econazole Econazol
|
||||
nl Enoxacin Enoxacine
|
||||
nl Epicillin Epicilline
|
||||
nl Erythromycin Erytromycine
|
||||
nl Ethambutol/isoniazid Ethambutol/isoniazide
|
||||
nl Fleroxacin Fleroxacine
|
||||
nl Flucloxacillin Flucloxacilline
|
||||
nl Fluconazole Fluconazol
|
||||
nl Flucytosine Fluorocytosine
|
||||
nl Flurithromycin Fluritromycine
|
||||
nl Fosfomycin Fosfomycine
|
||||
nl Fusidic acid Fusidinezuur
|
||||
nl Gatifloxacin Gatifloxacine
|
||||
nl Gemifloxacin Gemifloxacine
|
||||
nl Gentamicin Gentamicine
|
||||
nl Grepafloxacin Grepafloxacine
|
||||
nl Hachimycin Hachimycine
|
||||
nl Hetacillin Hetacilline
|
||||
nl Imipenem/cilastatin Imipenem/enzymremmer
|
||||
nl Inosine pranobex Inosiplex
|
||||
nl Isepamicin Isepamicine
|
||||
nl Isoconazole Isoconazol
|
||||
nl Isoniazid Isoniazide
|
||||
nl Itraconazole Itraconazol
|
||||
nl Josamycin Josamycine
|
||||
nl Kanamycin Kanamycine
|
||||
nl Ketoconazole Ketoconazol
|
||||
nl Levofloxacin Levofloxacine
|
||||
nl Lincomycin Lincomycine
|
||||
nl Lomefloxacin Lomefloxacine
|
||||
nl Lysozyme Lysozym
|
||||
nl Mandelic acid Amandelzuur
|
||||
nl Metampicillin Metampicilline
|
||||
nl Meticillin Meticilline
|
||||
nl Metisazone Metisazon
|
||||
nl Metronidazole Metronidazol
|
||||
nl Mezlocillin Mezlocilline
|
||||
nl Micafungin Micafungine
|
||||
nl Miconazole Miconazol
|
||||
nl Midecamycin Midecamycine
|
||||
nl Miocamycin Miocamycine
|
||||
nl Moxifloxacin Moxifloxacine
|
||||
nl Mupirocin Mupirocine
|
||||
nl Nalidixic acid Nalidixinezuur
|
||||
nl Neomycin Neomycine
|
||||
nl Netilmicin Netilmicine
|
||||
nl Nitrofurantoin Nitrofurantoine
|
||||
nl Norfloxacin Norfloxacine
|
||||
nl Novobiocin Novobiocine
|
||||
nl Nystatin Nystatine
|
||||
nl Ofloxacin Ofloxacine
|
||||
nl Oleandomycin Oleandomycine
|
||||
nl Ornidazole Ornidazol
|
||||
nl Oxacillin Oxacilline
|
||||
nl Oxolinic acid Oxolinezuur
|
||||
nl Oxytetracycline Oxytetracycline
|
||||
nl Pazufloxacin Pazufloxacine
|
||||
nl Pefloxacin Pefloxacine
|
||||
nl Penamecillin Penamecilline
|
||||
nl Penicillin Penicilline
|
||||
nl Pheneticillin Feneticilline
|
||||
nl Phenoxymethylpenicillin Fenoxymethylpenicilline
|
||||
nl Pipemidic acid Pipemidinezuur
|
||||
nl Piperacillin Piperacilline
|
||||
nl Piperacillin/beta-lactamase inhibitor Piperacilline/enzymremmer
|
||||
nl Piromidic acid Piromidinezuur
|
||||
nl Pivampicillin Pivampicilline
|
||||
nl Polymyxin B Polymyxine B
|
||||
nl Posaconazole Posaconazol
|
||||
nl Pristinamycin Pristinamycine
|
||||
nl Procaine benzylpenicillin Benzylpenicillineprocaine
|
||||
nl Propicillin Propicilline
|
||||
nl Prulifloxacin Prulifloxacine
|
||||
nl Quinupristin/dalfopristin Quinupristine/dalfopristine
|
||||
nl Ribostamycin Ribostamycine
|
||||
nl Rifabutin Rifabutine
|
||||
nl Rifampicin Rifampicine
|
||||
nl Rifampicin/pyrazinamide/ethambutol/isoniazid Rifampicine/pyrazinamide/ethambutol/isoniazide
|
||||
nl Rifampicin/pyrazinamide/isoniazid Rifampicine/pyrazinamide/isoniazide
|
||||
nl Rifampicin/isoniazid Rifampicine/isoniazide
|
||||
nl Rifamycin Rifamycine
|
||||
nl Rifaximin Rifaximine
|
||||
nl Rokitamycin Rokitamycine
|
||||
nl Rosoxacin Rosoxacine
|
||||
nl Roxithromycin Roxitromycine
|
||||
nl Rufloxacin Rufloxacine
|
||||
nl Sisomicin Sisomicine
|
||||
nl Sodium aminosalicylate Aminosalicylzuur
|
||||
nl Sparfloxacin Sparfloxacine
|
||||
nl Spectinomycin Spectinomycine
|
||||
nl Spiramycin Spiramycine
|
||||
nl Spiramycin/metronidazole Spiramycine/metronidazol
|
||||
nl Staphylococcus immunoglobulin Stafylokokkenimmunoglobuline
|
||||
nl Streptoduocin Streptoduocine
|
||||
nl Streptomycin Streptomycine
|
||||
nl Streptomycin/isoniazid Streptomycine/isoniazide
|
||||
nl Sulbenicillin Sulbenicilline
|
||||
nl Sulfadiazine/tetroxoprim Sulfadiazine/tetroxoprim
|
||||
nl Sulfadiazine/trimethoprim Sulfadiazine/trimethoprim
|
||||
nl Sulfadimidine/trimethoprim Sulfadimidine/trimethoprim
|
||||
nl Sulfafurazole Sulfafurazol
|
||||
nl Sulfaisodimidine Sulfisomidine
|
||||
nl Sulfalene Sulfaleen
|
||||
nl Sulfamazone Sulfamazon
|
||||
nl Sulfamerazine/trimethoprim Sulfamerazine/trimethoprim
|
||||
nl Sulfamethizole Sulfamethizol
|
||||
nl Sulfamethoxazole Sulfamethoxazol
|
||||
nl Sulfamethoxazole/trimethoprim Sulfamethoxazol/trimethoprim
|
||||
nl Sulfametoxydiazine Sulfamethoxydiazine
|
||||
nl Sulfametrole/trimethoprim Sulfametrol/trimethoprim
|
||||
nl Sulfamoxole Sulfamoxol
|
||||
nl Sulfamoxole/trimethoprim Sulfamoxol/trimethoprim
|
||||
nl Sulfaperin Sulfaperine
|
||||
nl Sulfaphenazole Sulfafenazol
|
||||
nl Sulfathiazole Sulfathiazol
|
||||
nl Sulfathiourea Sulfathioureum
|
||||
nl Sultamicillin Sultamicilline
|
||||
nl Talampicillin Talampicilline
|
||||
nl Teicoplanin Teicoplanine
|
||||
nl Telithromycin Telitromycine
|
||||
nl Temafloxacin Temafloxacine
|
||||
nl Temocillin Temocilline
|
||||
nl Tenofovir disoproxil Tenofovir
|
||||
nl Terizidone Terizidon
|
||||
nl Thiamphenicol Thiamfenicol
|
||||
nl Thioacetazone/isoniazid Thioacetazon/isoniazide
|
||||
nl Ticarcillin Ticarcilline
|
||||
nl Ticarcillin/beta-lactamase inhibitor Ticarcilline/enzymremmer
|
||||
nl Ticarcillin/clavulanic acid Ticarcilline/clavulaanzuur
|
||||
nl Tinidazole Tinidazol
|
||||
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|
||||
nl Trimethoprim/sulfamethoxazole Cotrimoxazol
|
||||
nl Troleandomycin Troleandomycine
|
||||
nl Trovafloxacin Trovafloxacine
|
||||
nl Vancomycin Vancomycine
|
||||
nl Voriconazole Voriconazol
|
||||
nl Aminoglycosides Aminoglycosiden TRUE FALSE
|
||||
nl Amphenicols Amfenicolen TRUE FALSE
|
||||
nl Antifungals/antimycotics Antifungica/antimycotica TRUE FALSE
|
||||
nl Antimycobacterials Antimycobacteriele middelen TRUE FALSE
|
||||
nl Beta-lactams/penicillins Beta-lactams/penicillines TRUE FALSE
|
||||
nl Cephalosporins (1st gen.) Cefalosporines (1e gen.) TRUE FALSE
|
||||
nl Cephalosporins (2nd gen.) Cefalosporines (2e gen.) TRUE FALSE
|
||||
nl Cephalosporins (3rd gen.) Cefalosporines (3e gen.) TRUE FALSE
|
||||
nl Cephalosporins (4th gen.) Cefalosporines (4e gen.) TRUE FALSE
|
||||
nl Cephalosporins (5th gen.) Cefalosporines (5e gen.) TRUE FALSE
|
||||
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|
||||
nl Cephalosporins Cefalosporines TRUE FALSE
|
||||
nl Glycopeptides Glycopeptiden TRUE FALSE
|
||||
nl Macrolides/lincosamides Macroliden/lincosamiden TRUE FALSE
|
||||
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|
||||
nl Polymyxins Polymyxines TRUE FALSE
|
||||
nl Quinolones Quinolonen TRUE FALSE
|
||||
|
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||||
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<h1>License</h1>
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<pre>GNU GENERAL PUBLIC LICENSE
|
||||
Version 2, June 1991
|
||||
|
||||
Copyright (C) 1989, 1991 Free Software Foundation, Inc., <http://fsf.org/>
|
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51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
|
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Everyone is permitted to copy and distribute verbatim copies
|
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of this license document, but changing it is not allowed.
|
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|
||||
A SUMMARY OF THIS LICENSE BY THE ORIGINAL AUTHORS OF THE AMR R PACKAGE
|
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|
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This R package, with package name 'AMR':
|
||||
- May be used for commercial purposes
|
||||
- May be used for private purposes
|
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- May NOT be used for patent purposes
|
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- May be modified, although:
|
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- Modifications MUST be released under the same license when distributing the package
|
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- Changes made to the code MUST be documented
|
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- May be distributed, although:
|
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- Source code MUST be made available when the package is distributed
|
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|
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- Comes with a LIMITATION of liability
|
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- Comes with NO warranty
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END OF THE SUMMARY
|
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GNU GENERAL PUBLIC LICENSE
|
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TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
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0. This License applies to any program or other work which contains
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Apply EUCAST rules
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Get properties of a microorganism
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||||
Get properties of an antibiotic
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Other: benchmarks
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Source Code
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</header><div class="row">
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<div class="col-md-9 contents">
|
||||
<div class="page-header toc-ignore">
|
||||
<h1>How to apply EUCAST rules</h1>
|
||||
<h4 class="author">Matthijs S. Berends</h4>
|
||||
|
||||
<h4 class="date">13 October 2019</h4>
|
||||
|
||||
|
||||
<div class="hidden name"><code>EUCAST.Rmd</code></div>
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
<div id="introduction" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#introduction" class="anchor"></a>Introduction</h2>
|
||||
<p>What are EUCAST rules? The European Committee on Antimicrobial Susceptibility Testing (EUCAST) states <a href="http://www.eucast.org/expert_rules_and_intrinsic_resistance/">on their website</a>:</p>
|
||||
<blockquote>
|
||||
<p><em>EUCAST expert rules are a tabulated collection of expert knowledge on intrinsic resistances, exceptional resistance phenotypes and interpretive rules that may be applied to antimicrobial susceptibility testing in order to reduce errors and make appropriate recommendations for reporting particular resistances.</em></p>
|
||||
</blockquote>
|
||||
<p>In Europe, a lot of medical microbiological laboratories already apply these rules (<a href="https://www.eurosurveillance.org/content/10.2807/1560-7917.ES2015.20.2.21008">Brown <em>et al.</em>, 2015</a>). Our package features their latest insights on intrinsic resistance and exceptional phenotypes (version 9.0, 2019). Moreover, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function we use for this purpose can also apply additional rules, like forcing <help title="ATC: J01CA01">ampicillin</help> = R in isolates when <help title="ATC: J01CR02">amoxicillin/clavulanic acid</help> = R.</p>
|
||||
<p><em>(more will be available soon)</em></p>
|
||||
<div id="benefit-for-empiric-therapy-success-estimation" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#benefit-for-empiric-therapy-success-estimation" class="anchor"></a>Benefit for empiric therapy success estimation</h3>
|
||||
<p><em>(will be available soon)</em></p>
|
||||
</div>
|
||||
</div>
|
||||
<div id="examples" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#examples" class="anchor"></a>Examples</h2>
|
||||
<p><em>(will be available soon)</em></p>
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<a href="#tocnav" class="anchor"></a>Contents</h2>
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<li><a href="#introduction">Introduction</a></li>
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<li><a href="#examples">Examples</a></li>
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||||
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||||
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||||
|
||||
<footer><div class="copyright">
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||||
<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/">Alex W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/">Corinna Glasner</a>.</p>
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|
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|
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<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.4.1.</p>
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