mirror of
https://github.com/msberends/AMR.git
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Compare commits
23
Commits
v1.7.1
..
4e1efd902c
@@ -23,6 +23,8 @@
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
# This GitHub Actions file runs without ANY dependency, so works on all versions of R since R-3.0.
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
@@ -32,9 +34,9 @@ on:
|
||||
branches:
|
||||
- master
|
||||
schedule:
|
||||
# run a schedule everyday at 3 AM.
|
||||
# run a schedule everyday at 1 AM.
|
||||
# this is to check that all dependencies are still available (see R/zzz.R)
|
||||
- cron: '0 3 * * *'
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||||
- cron: '0 1 * * *'
|
||||
|
||||
name: R-code-check
|
||||
|
||||
@@ -55,25 +57,33 @@ jobs:
|
||||
- {os: windows-latest, r: 'devel', allowfail: true}
|
||||
- {os: ubuntu-20.04, r: 'devel', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
|
||||
# these are the current release of R
|
||||
- {os: macOS-latest, r: 'release', allowfail: false}
|
||||
- {os: windows-latest, r: 'release', allowfail: false}
|
||||
- {os: ubuntu-20.04, r: 'release', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
|
||||
# these are the previous release of R
|
||||
- {os: macOS-latest, r: 'oldrel', allowfail: false}
|
||||
- {os: windows-latest, r: 'oldrel', allowfail: false}
|
||||
- {os: ubuntu-20.04, r: 'oldrel', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
|
||||
# test against all released versions of R >= 3.0, we support them all!
|
||||
# test all systems against all released versions of R >= 3.0, we support them all!
|
||||
- {os: macOS-latest, r: '4.1', allowfail: false}
|
||||
- {os: windows-latest, r: '4.1', allowfail: false}
|
||||
- {os: ubuntu-20.04, r: '4.1', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
- {os: macOS-latest, r: '4.0', allowfail: false}
|
||||
- {os: windows-latest, r: '4.0', allowfail: false}
|
||||
- {os: ubuntu-20.04, r: '4.0', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
- {os: macOS-latest, r: '3.6', allowfail: false}
|
||||
- {os: windows-latest, r: '3.6', allowfail: true}
|
||||
- {os: ubuntu-20.04, r: '3.6', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
- {os: macOS-latest, r: '3.5', allowfail: false}
|
||||
- {os: windows-latest, r: '3.5', allowfail: false}
|
||||
- {os: ubuntu-20.04, r: '3.5', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
- {os: macOS-latest, r: '3.4', allowfail: false}
|
||||
- {os: windows-latest, r: '3.4', allowfail: false}
|
||||
- {os: ubuntu-20.04, r: '3.4', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
- {os: macOS-latest, r: '3.3', allowfail: false}
|
||||
- {os: windows-latest, r: '3.3', allowfail: false}
|
||||
- {os: ubuntu-20.04, r: '3.3', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
- {os: macOS-latest, r: '3.2', allowfail: false}
|
||||
- {os: windows-latest, r: '3.2', allowfail: false}
|
||||
- {os: ubuntu-20.04, r: '3.2', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
# - {os: macOS-latest, r: '3.1', allowfail: false}
|
||||
# - {os: windows-latest, r: '3.1', allowfail: false}
|
||||
- {os: ubuntu-20.04, r: '3.1', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
# - {os: macOS-latest, r: '3.0', allowfail: false}
|
||||
# - {os: windows-latest, r: '3.0', allowfail: false}
|
||||
- {os: ubuntu-20.04, r: '3.0', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
|
||||
|
||||
env:
|
||||
@@ -94,15 +104,20 @@ jobs:
|
||||
# we don't want to depend on the sysreqs pkg here, as it requires quite a recent R version
|
||||
# as of May 2021: https://sysreqs.r-hub.io/pkg/AMR,R,cleaner,curl,dplyr,ggplot2,ggtext,knitr,microbenchmark,pillar,readxl,rmarkdown,rstudioapi,rvest,skimr,tidyr,tinytest,xml2,backports,crayon,rlang,vctrs,evaluate,highr,markdown,stringr,yaml,xfun,cli,ellipsis,fansi,lifecycle,utf8,glue,mime,magrittr,stringi,generics,R6,tibble,tidyselect,pkgconfig,purrr,digest,gtable,isoband,MASS,mgcv,scales,withr,nlme,Matrix,farver,labeling,munsell,RColorBrewer,viridisLite,lattice,colorspace,gridtext,Rcpp,RCurl,png,jpeg,bitops,cellranger,progress,rematch,hms,prettyunits,htmltools,jsonlite,tinytex,base64enc,httr,selectr,openssl,askpass,sys,repr,cpp11
|
||||
run: |
|
||||
sudo apt install -y libssl-dev pandoc pandoc-citeproc libxml2-dev libicu-dev libcurl4-openssl-dev libpng-dev
|
||||
sudo apt install -y libssl-dev pandoc pandoc-citeproc libxml2-dev libicu-dev libcurl4-openssl-dev libpng-dev libudunits2-dev
|
||||
|
||||
- name: Query dependencies
|
||||
# this will change every day (i.e. at scheduled night run of GitHub Action), so it will cache dependency updates
|
||||
run: |
|
||||
writeLines(paste0(format(Sys.Date(), "%Y%m%d"), sprintf("-R-%i.%i", getRversion()$major, getRversion()$minor)), ".github/daily-R-bundle")
|
||||
shell: Rscript {0}
|
||||
|
||||
- name: Restore cached R packages
|
||||
# this step will add the step 'Post Restore cached R packages' on a succesful run
|
||||
if: runner.os != 'Windows'
|
||||
uses: actions/cache@v1
|
||||
uses: actions/cache@v2
|
||||
with:
|
||||
path: ${{ env.R_LIBS_USER }}
|
||||
key: ${{ matrix.config.os }}-r-${{ matrix.config.r }}-v4
|
||||
key: ${{ matrix.config.os }}-${{ hashFiles('.github/daily-R-bundle') }}-v4
|
||||
|
||||
- name: Unpack AMR and install R dependencies
|
||||
if: always()
|
||||
@@ -156,5 +171,5 @@ jobs:
|
||||
if: always()
|
||||
uses: actions/upload-artifact@v2
|
||||
with:
|
||||
name: artifacts-${{ matrix.config.os }}-r${{ matrix.config.r }}
|
||||
name: artifacts-r-${{ matrix.config.r }}-${{ matrix.config.os }}
|
||||
path: AMR.Rcheck
|
||||
|
||||
@@ -48,12 +48,18 @@ jobs:
|
||||
|
||||
- uses: r-lib/actions/setup-pandoc@master
|
||||
|
||||
- name: Query dependencies
|
||||
# this will change once a week, so it will cache dependency updates
|
||||
run: |
|
||||
writeLines(paste(format(Sys.Date(), "week %V %Y"), sprintf("R-%i.%i", getRversion()$major, getRversion()$minor)), ".github/week-R-version")
|
||||
shell: Rscript {0}
|
||||
|
||||
- name: Restore cached R packages
|
||||
# this step will add the step 'Post Restore cached R packages' on a succesful run
|
||||
uses: actions/cache@v1
|
||||
uses: actions/cache@v2
|
||||
with:
|
||||
path: ${{ env.R_LIBS_USER }}
|
||||
key: macOS-latest-r-release-v5-codecovr
|
||||
key: ${{ matrix.config.os }}-${{ hashFiles('.github/week-R-version') }}-v4
|
||||
|
||||
- name: Unpack AMR and install R dependencies
|
||||
run: |
|
||||
@@ -68,26 +74,14 @@ jobs:
|
||||
as.data.frame(utils::installed.packages())[, "Version", drop = FALSE]
|
||||
shell: Rscript {0}
|
||||
|
||||
# - name: Test coverage
|
||||
# env:
|
||||
# CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
|
||||
# run: |
|
||||
# library(AMR)
|
||||
# library(tinytest)
|
||||
# library(covr)
|
||||
# source_files <- list.files("R", pattern = ".R$", full.names = TRUE)
|
||||
# test_files <- list.files("inst/tinytest", full.names = TRUE)
|
||||
# cov <- file_coverage(source_files = source_files, test_files = test_files, parent_env = asNamespace("AMR"), line_exclusions = list("R/atc_online.R", "R/mo_source.R", "R/translate.R", "R/resistance_predict.R", "R/aa_helper_functions.R", "R/aa_helper_pm_functions.R", "R/zzz.R"))
|
||||
# attr(cov, which = "package") <- list(path = ".") # until https://github.com/r-lib/covr/issues/478 is solved
|
||||
# codecov(coverage = cov, quiet = FALSE)
|
||||
# shell: Rscript {0}
|
||||
|
||||
- name: Test coverage
|
||||
env:
|
||||
CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
|
||||
R_RUN_TINYTEST: true
|
||||
run: |
|
||||
install.packages("covr", repos = "https://cran.rstudio.com/")
|
||||
library(AMR)
|
||||
library(tinytest)
|
||||
covr::codecov(line_exclusions = list("R/atc_online.R", "R/mo_source.R", "R/translate.R", "R/resistance_predict.R", "R/aa_helper_functions.R", "R/aa_helper_pm_functions.R", "R/zzz.R"))
|
||||
x <- covr::codecov(line_exclusions = list("R/atc_online.R", "R/mo_source.R", "R/translate.R", "R/resistance_predict.R", "R/aa_helper_functions.R", "R/aa_helper_pm_functions.R", "R/zzz.R"))
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||||
print(x)
|
||||
shell: Rscript {0}
|
||||
|
||||
@@ -52,7 +52,7 @@ jobs:
|
||||
shell: Rscript {0}
|
||||
|
||||
- name: Cache R packages
|
||||
uses: actions/cache@v1
|
||||
uses: actions/cache@v2
|
||||
with:
|
||||
path: ${{ env.R_LIBS_USER }}
|
||||
key: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-${{ hashFiles('.github/depends.Rds') }}
|
||||
|
||||
+4
-3
@@ -1,6 +1,6 @@
|
||||
Package: AMR
|
||||
Version: 1.7.1
|
||||
Date: 2021-06-03
|
||||
Version: 1.7.1.9022
|
||||
Date: 2021-07-23
|
||||
Title: Antimicrobial Resistance Data Analysis
|
||||
Authors@R: c(
|
||||
person(role = c("aut", "cre"),
|
||||
@@ -57,9 +57,10 @@ Suggests:
|
||||
skimr,
|
||||
tidyr,
|
||||
tinytest,
|
||||
vctrs,
|
||||
xml2
|
||||
VignetteBuilder: knitr,rmarkdown
|
||||
URL: https://msberends.github.io/AMR/, https://github.com/msberends/AMR
|
||||
URL: https://github.com/msberends/AMR, https://msberends.github.io/AMR
|
||||
BugReports: https://github.com/msberends/AMR/issues
|
||||
License: GPL-2 | file LICENSE
|
||||
Encoding: UTF-8
|
||||
|
||||
@@ -120,7 +120,11 @@ S3method(print,rsi)
|
||||
S3method(prod,mic)
|
||||
S3method(quantile,mic)
|
||||
S3method(range,mic)
|
||||
S3method(rep,ab)
|
||||
S3method(rep,disk)
|
||||
S3method(rep,mic)
|
||||
S3method(rep,mo)
|
||||
S3method(rep,rsi)
|
||||
S3method(round,mic)
|
||||
S3method(sign,mic)
|
||||
S3method(signif,mic)
|
||||
@@ -170,6 +174,7 @@ export(age)
|
||||
export(age_groups)
|
||||
export(all_antimicrobials)
|
||||
export(aminoglycosides)
|
||||
export(aminopenicillins)
|
||||
export(anti_join_microorganisms)
|
||||
export(antimicrobials_equal)
|
||||
export(as.ab)
|
||||
@@ -255,6 +260,8 @@ export(kurtosis)
|
||||
export(labels_rsi_count)
|
||||
export(left_join_microorganisms)
|
||||
export(like)
|
||||
export(lincosamides)
|
||||
export(lipoglycopeptides)
|
||||
export(macrolides)
|
||||
export(mdr_cmi2012)
|
||||
export(mdr_tb)
|
||||
@@ -297,12 +304,14 @@ export(oxazolidinones)
|
||||
export(p_symbol)
|
||||
export(pca)
|
||||
export(penicillins)
|
||||
export(polymyxins)
|
||||
export(proportion_I)
|
||||
export(proportion_IR)
|
||||
export(proportion_R)
|
||||
export(proportion_S)
|
||||
export(proportion_SI)
|
||||
export(proportion_df)
|
||||
export(quinolones)
|
||||
export(random_disk)
|
||||
export(random_mic)
|
||||
export(random_rsi)
|
||||
@@ -316,9 +325,11 @@ export(scale_y_percent)
|
||||
export(semi_join_microorganisms)
|
||||
export(set_mo_source)
|
||||
export(skewness)
|
||||
export(streptogramins)
|
||||
export(susceptibility)
|
||||
export(tetracyclines)
|
||||
export(theme_rsi)
|
||||
export(ureidopenicillins)
|
||||
importFrom(graphics,arrows)
|
||||
importFrom(graphics,axis)
|
||||
importFrom(graphics,barplot)
|
||||
|
||||
@@ -1,7 +1,31 @@
|
||||
# `AMR` 1.7.1
|
||||
# `AMR` 1.7.1.9022
|
||||
## <small>Last updated: 23 July 2021</small>
|
||||
|
||||
### Changed
|
||||
* Previously implemented `ggplot2::ggplot()` generics for classes `<mic>`, `<disk>`, `<rsi>` and `<resistance_predict>` did not follow the `ggplot2` logic, and were replaced with `autoplot()` generics.
|
||||
* Antibiotic class selectors (see `ab_class()`)
|
||||
* They now also work in R-3.0 and R-3.1, supporting every version of R since 2013
|
||||
* Added more selectors: `aminopenicillins()`, `lincosamides()`, `lipoglycopeptides()`, `polymyxins()`, `quinolones()`, `streptogramins()` and `ureidopenicillins()`
|
||||
* Fix for using selectors multiple times in one call (e.g., using them in `dplyr::filter()` and immediately after in `dplyr::select()`)
|
||||
* Added argument `only_treatable`, which defaults to `TRUE` and will exclude drugs that are only for laboratory tests and not for treating patients (such as imipenem/EDTA and gentamicin-high)
|
||||
* Fix for duplicate ATC codes in the `antibiotics` data set
|
||||
* Fix to prevent introducing `NA`s for old MO codes when running `as.mo()` on them
|
||||
* Added more informative error messages when any of the `proportion_*()` and `count_*()` functions fail
|
||||
* When printing a tibble with any old MO code, a warning will be thrown that old codes should be updated using `as.mo()`
|
||||
* Improved automatic column selector when `col_*` arguments are left blank, e.g. in `first_isolate()`
|
||||
* The right input types for `random_mic()`, `random_disk()` and `random_rsi()` are now enforced
|
||||
* `as.rsi()` can now correct for textual input (such as "Susceptible", "Resistant") in Dutch, English, French, German, Italian, Portuguese and Spanish
|
||||
* When warnings are thrown because of too few isolates in any `count_*()`, `proportion_*()` function (or `resistant()` or `susceptible()`), the `dplyr` group will be shown, if available
|
||||
* `ab_name()` gained argument `snake_case`, which is useful for column renaming
|
||||
* Fix for legends created with `scale_rsi_colours()` when using `ggplot2` v3.3.4 or higher (this is ggplot2 bug 4511, soon to be fixed)
|
||||
* Fix for minor translation errors
|
||||
* Fix for the MIC interpretation of *Morganellaceae* (such as *Morganella* and *Proteus*) when using the EUCAST 2021 guideline
|
||||
* Improved algorithm for generating random MICs with `random_mic()`
|
||||
* Improved plot legends for MICs and disk diffusion values
|
||||
|
||||
# AMR 1.7.1
|
||||
|
||||
### Breaking change
|
||||
* Support for CLSI 2020 guideline for interpreting MICs and disk diffusion values (using `as.rsi()`)
|
||||
* All antibiotic class selectors (such as `carbapenems()`, `aminoglycosides()`) can now be used for filtering as well, making all their accompanying `filter_*()` functions redundant (such as `filter_carbapenems()`, `filter_aminoglycosides()`). These functions are now deprecated and will be removed in a next release. Examples of how the selectors can be used for filtering:
|
||||
```r
|
||||
# select columns with results for carbapenems
|
||||
@@ -21,6 +45,7 @@
|
||||
```
|
||||
|
||||
### New
|
||||
* Support for CLSI 2020 guideline for interpreting MICs and disk diffusion values (using `as.rsi()`)
|
||||
* Function `custom_eucast_rules()` that brings support for custom AMR rules in `eucast_rules()`
|
||||
* Function `italicise_taxonomy()` to make taxonomic names within a string italic, with support for markdown and ANSI
|
||||
* Support for all four methods to determine first isolates as summarised by Hindler *et al.* (doi: [10.1086/511864](https://doi.org/10.1086/511864)): isolate-based, patient-based, episode-based and phenotype-based. The last method is now the default.
|
||||
@@ -72,7 +97,7 @@
|
||||
* All unit tests are now processed by the `tinytest` package, instead of the `testthat` package. The `testthat` package unfortunately requires tons of dependencies that are also heavy and only usable for recent R versions, disallowing developers to test a package under any R 3.* version. On the contrary, the `tinytest` package is very lightweight and dependency-free.
|
||||
|
||||
|
||||
# `AMR` 1.6.0
|
||||
# AMR 1.6.0
|
||||
|
||||
### New
|
||||
* Support for EUCAST Clinical Breakpoints v11.0 (2021), effective in the `eucast_rules()` function and in `as.rsi()` to interpret MIC and disk diffusion values. This is now the default guideline in this package.
|
||||
@@ -166,7 +191,7 @@
|
||||
* Loading the package (i.e., `library(AMR)`) now is ~50 times faster than before, in costs of package size (which increased by ~3 MB)
|
||||
|
||||
|
||||
# `AMR` 1.5.0
|
||||
# AMR 1.5.0
|
||||
|
||||
### New
|
||||
* Functions `get_episode()` and `is_new_episode()` to determine (patient) episodes which are not necessarily based on microorganisms. The `get_episode()` function returns the index number of the episode per group, while the `is_new_episode()` function returns values `TRUE`/`FALSE` to indicate whether an item in a vector is the start of a new episode. They also support `dplyr`s grouping (i.e. using `group_by()`):
|
||||
@@ -243,7 +268,7 @@
|
||||
* Added CodeFactor as a continuous code review to this package: <https://www.codefactor.io/repository/github/msberends/amr/>
|
||||
* Added Dr. Rogier Schade as contributor
|
||||
|
||||
# `AMR` 1.4.0
|
||||
# AMR 1.4.0
|
||||
|
||||
### New
|
||||
* Support for 'EUCAST Expert Rules' / 'EUCAST Intrinsic Resistance and Unusual Phenotypes' version 3.2 of May 2020. With this addition to the previously implemented version 3.1 of 2016, the `eucast_rules()` function can now correct for more than 180 different antibiotics and the `mdro()` function can determine multidrug resistance based on more than 150 different antibiotics. All previously implemented versions of the EUCAST rules are now maintained and kept available in this package. The `eucast_rules()` function consequently gained the arguments `version_breakpoints` (at the moment defaults to v10.0, 2020) and `version_expertrules` (at the moment defaults to v3.2, 2020). The `example_isolates` data set now also reflects the change from v3.1 to v3.2. The `mdro()` function now accepts `guideline == "EUCAST3.1"` and `guideline == "EUCAST3.2"`.
|
||||
@@ -315,7 +340,7 @@
|
||||
* Removed unnecessary references to the `base` package
|
||||
* Added packages that could be useful for some functions to the `Suggests` field of the `DESCRIPTION` file
|
||||
|
||||
# `AMR` 1.3.0
|
||||
# AMR 1.3.0
|
||||
|
||||
### New
|
||||
* Function `ab_from_text()` to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses `as.ab()` internally
|
||||
@@ -368,7 +393,7 @@
|
||||
### Other
|
||||
* Moved primary location of this project from GitLab to [GitHub](https://github.com/msberends/AMR), giving us native support for automated syntax checking without being dependent on external services such as AppVeyor and Travis CI.
|
||||
|
||||
# `AMR` 1.2.0
|
||||
# AMR 1.2.0
|
||||
|
||||
### Breaking
|
||||
* Removed code dependency on all other R packages, making this package fully independent of the development process of others. This is a major code change, but will probably not be noticeable by most users.
|
||||
@@ -406,7 +431,7 @@
|
||||
* Removed previously deprecated function `p.symbol()` - it was replaced with `p_symbol()`
|
||||
* Removed function `read.4d()`, that was only useful for reading data from an old test database.
|
||||
|
||||
# `AMR` 1.1.0
|
||||
# AMR 1.1.0
|
||||
|
||||
### New
|
||||
* Support for easy principal component analysis for AMR, using the new `pca()` function
|
||||
@@ -428,7 +453,7 @@
|
||||
* Support for the upcoming `dplyr` version 1.0.0
|
||||
* More robust assigning for classes `rsi` and `mic`
|
||||
|
||||
# `AMR` 1.0.1
|
||||
# AMR 1.0.1
|
||||
|
||||
### Changed
|
||||
* Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline
|
||||
@@ -444,7 +469,7 @@
|
||||
* Added `uti` (as abbreviation of urinary tract infections) as argument to `as.rsi()`, so interpretation of MIC values and disk zones can be made dependent on isolates specifically from UTIs
|
||||
* Info printing in functions `eucast_rules()`, `first_isolate()`, `mdro()` and `resistance_predict()` will now at default only print when R is in an interactive mode (i.e. not in RMarkdown)
|
||||
|
||||
# `AMR` 1.0.0
|
||||
# AMR 1.0.0
|
||||
|
||||
This software is now out of beta and considered stable. Nonetheless, this package will be developed continually.
|
||||
|
||||
@@ -492,7 +517,7 @@ This software is now out of beta and considered stable. Nonetheless, this packag
|
||||
* Full support for the upcoming R 4.0
|
||||
* Removed unnecessary `AMR::` calls
|
||||
|
||||
# `AMR` 0.9.0
|
||||
# AMR 0.9.0
|
||||
|
||||
### Breaking
|
||||
* Adopted Adeolu *et al.* (2016), [PMID 27620848](https:/pubmed.ncbi.nlm.nih.gov/27620848/) for the `microorganisms` data set, which means that the new order Enterobacterales now consists of a part of the existing family Enterobacteriaceae, but that this family has been split into other families as well (like *Morganellaceae* and *Yersiniaceae*). Although published in 2016, this information is not yet in the Catalogue of Life version of 2019. All MDRO determinations with `mdro()` will now use the Enterobacterales order for all guidelines before 2016 that were dependent on the Enterobacteriaceae family.
|
||||
@@ -558,7 +583,7 @@ This software is now out of beta and considered stable. Nonetheless, this packag
|
||||
* Change dependency on `clean` to `cleaner`, as this package was renamed accordingly upon CRAN request
|
||||
* Added Dr. Sofia Ny as contributor
|
||||
|
||||
# `AMR` 0.8.0
|
||||
# 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 argument `include_unknown`:
|
||||
@@ -687,7 +712,7 @@ This software is now out of beta and considered stable. Nonetheless, this packag
|
||||
* 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
|
||||
# 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:
|
||||
@@ -748,7 +773,7 @@ This software is now out of beta and considered stable. Nonetheless, this packag
|
||||
#### Other
|
||||
* Fixed a note thrown by CRAN tests
|
||||
|
||||
# `AMR` 0.7.0
|
||||
# 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.
|
||||
@@ -806,13 +831,13 @@ This software is now out of beta and considered stable. Nonetheless, this packag
|
||||
#### 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
|
||||
# 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
|
||||
# AMR 0.6.0
|
||||
|
||||
**New website!**
|
||||
|
||||
@@ -1005,7 +1030,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
|
||||
#### Other
|
||||
* Updated licence text to emphasise GPL 2.0 and that this is an R package.
|
||||
|
||||
# `AMR` 0.5.0
|
||||
# AMR 0.5.0
|
||||
|
||||
#### New
|
||||
* Repository moved to GitLab
|
||||
@@ -1088,7 +1113,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
|
||||
* Updated vignettes to comply with README
|
||||
|
||||
|
||||
# `AMR` 0.4.0
|
||||
# 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.
|
||||
@@ -1199,7 +1224,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
|
||||
#### Other
|
||||
* More unit tests to ensure better integrity of functions
|
||||
|
||||
# `AMR` 0.3.0
|
||||
# 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.
|
||||
@@ -1269,7 +1294,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
|
||||
* Windows: https://ci.appveyor.com/project/msberends/amr
|
||||
* Added thesis advisors to DESCRIPTION file
|
||||
|
||||
# `AMR` 0.2.0
|
||||
# AMR 0.2.0
|
||||
|
||||
#### New
|
||||
* Full support for Windows, Linux and macOS
|
||||
@@ -1304,7 +1329,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
|
||||
* 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
|
||||
# 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
|
||||
@@ -1312,6 +1337,6 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
|
||||
* Renamed 'Daily Defined Dose' to 'Defined Daily Dose'
|
||||
* Added barplots for `rsi` and `mic` classes
|
||||
|
||||
# `AMR` 0.1.0
|
||||
# AMR 0.1.0
|
||||
|
||||
* First submission to CRAN.
|
||||
|
||||
+83
-114
@@ -135,7 +135,6 @@ check_dataset_integrity <- function() {
|
||||
" the AMR package from working correctly: ",
|
||||
vector_and(overwritten, quotes = "'"),
|
||||
".\nPlease rename your object", plural[3], ".", call = FALSE)
|
||||
remember_thrown_message("dataset_overwritten")
|
||||
}
|
||||
}
|
||||
# check if other packages did not overwrite our data sets
|
||||
@@ -170,65 +169,73 @@ search_type_in_df <- function(x, type, info = TRUE) {
|
||||
|
||||
# remove attributes from other packages
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
||||
colnames(x) <- trimws(colnames(x))
|
||||
colnames_formatted <- tolower(generalise_antibiotic_name(colnames(x)))
|
||||
|
||||
# -- mo
|
||||
if (type == "mo") {
|
||||
if (any(vapply(FUN.VALUE = logical(1), x, is.mo))) {
|
||||
found <- sort(colnames(x)[vapply(FUN.VALUE = logical(1), x, is.mo)])[1]
|
||||
} else if ("mo" %in% colnames(x) &
|
||||
suppressWarnings(
|
||||
all(x$mo %in% c(NA, microorganisms$mo)))) {
|
||||
# take first <mo> column
|
||||
found <- colnames(x)[vapply(FUN.VALUE = logical(1), x, is.mo)]
|
||||
} else if ("mo" %in% colnames_formatted &
|
||||
suppressWarnings(all(x$mo %in% c(NA, microorganisms$mo)))) {
|
||||
found <- "mo"
|
||||
} else if (any(colnames(x) %like% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$")) {
|
||||
found <- sort(colnames(x)[colnames(x) %like% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$"])[1]
|
||||
} else if (any(colnames(x) %like% "^(microorganism|organism|bacteria|ba[ck]terie)")) {
|
||||
found <- sort(colnames(x)[colnames(x) %like% "^(microorganism|organism|bacteria|ba[ck]terie)"])[1]
|
||||
} else if (any(colnames(x) %like% "species")) {
|
||||
found <- sort(colnames(x)[colnames(x) %like% "species"])[1]
|
||||
} else if (any(colnames_formatted %like_case% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$")) {
|
||||
found <- sort(colnames(x)[colnames_formatted %like_case% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$"])
|
||||
} else if (any(colnames_formatted %like_case% "^(microorganism|organism|bacteria|ba[ck]terie)")) {
|
||||
found <- sort(colnames(x)[colnames_formatted %like_case% "^(microorganism|organism|bacteria|ba[ck]terie)"])
|
||||
} else if (any(colnames_formatted %like_case% "species")) {
|
||||
found <- sort(colnames(x)[colnames_formatted %like_case% "species"])
|
||||
}
|
||||
|
||||
}
|
||||
# -- key antibiotics
|
||||
if (type %in% c("keyantibiotics", "keyantimicrobials")) {
|
||||
if (any(colnames(x) %like% "^key.*(ab|antibiotics|antimicrobials)")) {
|
||||
found <- sort(colnames(x)[colnames(x) %like% "^key.*(ab|antibiotics|antimicrobials)"])[1]
|
||||
if (any(colnames_formatted %like_case% "^key.*(ab|antibiotics|antimicrobials)")) {
|
||||
found <- sort(colnames(x)[colnames_formatted %like_case% "^key.*(ab|antibiotics|antimicrobials)"])
|
||||
}
|
||||
}
|
||||
# -- date
|
||||
if (type == "date") {
|
||||
if (any(colnames(x) %like% "^(specimen date|specimen_date|spec_date)")) {
|
||||
if (any(colnames_formatted %like_case% "^(specimen date|specimen_date|spec_date)")) {
|
||||
# WHONET support
|
||||
found <- sort(colnames(x)[colnames(x) %like% "^(specimen date|specimen_date|spec_date)"])[1]
|
||||
found <- sort(colnames(x)[colnames_formatted %like_case% "^(specimen date|specimen_date|spec_date)"])
|
||||
if (!any(class(pm_pull(x, found)) %in% c("Date", "POSIXct"))) {
|
||||
stop(font_red(paste0("Found column '", font_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 if (any(vapply(FUN.VALUE = logical(1), x, function(x) inherits(x, c("Date", "POSIXct"))))) {
|
||||
found <- sort(colnames(x)[vapply(FUN.VALUE = logical(1), x, function(x) inherits(x, c("Date", "POSIXct")))])[1]
|
||||
# take first <Date> column
|
||||
found <- colnames(x)[vapply(FUN.VALUE = logical(1), x, function(x) inherits(x, c("Date", "POSIXct")))]
|
||||
}
|
||||
}
|
||||
# -- patient id
|
||||
if (type == "patient_id") {
|
||||
if (any(colnames(x) %like% "^(identification |patient|patid)")) {
|
||||
found <- sort(colnames(x)[colnames(x) %like% "^(identification |patient|patid)"])[1]
|
||||
crit1 <- colnames_formatted %like_case% "^(patient|patid)"
|
||||
if (any(crit1)) {
|
||||
found <- colnames(x)[crit1]
|
||||
} else {
|
||||
crit2 <- colnames_formatted %like_case% "(identification |patient|pat.*id)"
|
||||
if (any(crit2)) {
|
||||
found <- colnames(x)[crit2]
|
||||
}
|
||||
}
|
||||
}
|
||||
# -- specimen
|
||||
if (type == "specimen") {
|
||||
if (any(colnames(x) %like% "(specimen type|spec_type)")) {
|
||||
found <- sort(colnames(x)[colnames(x) %like% "(specimen type|spec_type)"])[1]
|
||||
} else if (any(colnames(x) %like% "^(specimen)")) {
|
||||
found <- sort(colnames(x)[colnames(x) %like% "^(specimen)"])[1]
|
||||
if (any(colnames_formatted %like_case% "(specimen type|spec_type)")) {
|
||||
found <- sort(colnames(x)[colnames_formatted %like_case% "(specimen type|spec_type)"])
|
||||
} else if (any(colnames_formatted %like_case% "^(specimen)")) {
|
||||
found <- sort(colnames(x)[colnames_formatted %like_case% "^(specimen)"])
|
||||
}
|
||||
}
|
||||
# -- UTI (urinary tract infection)
|
||||
if (type == "uti") {
|
||||
if (any(colnames(x) == "uti")) {
|
||||
found <- colnames(x)[colnames(x) == "uti"][1]
|
||||
} else if (any(colnames(x) %like% "(urine|urinary)")) {
|
||||
found <- sort(colnames(x)[colnames(x) %like% "(urine|urinary)"])[1]
|
||||
if (any(colnames_formatted == "uti")) {
|
||||
found <- colnames(x)[colnames_formatted == "uti"]
|
||||
} else if (any(colnames_formatted %like_case% "(urine|urinary)")) {
|
||||
found <- sort(colnames(x)[colnames_formatted %like_case% "(urine|urinary)"])
|
||||
}
|
||||
if (!is.null(found)) {
|
||||
# this column should contain logicals
|
||||
@@ -241,14 +248,15 @@ search_type_in_df <- function(x, type, info = TRUE) {
|
||||
}
|
||||
}
|
||||
|
||||
found <- found[1]
|
||||
|
||||
if (!is.null(found) & info == TRUE) {
|
||||
if (message_not_thrown_before(fn = paste0("search_", type))) {
|
||||
msg <- paste0("Using column '", font_bold(found), "' as input for `col_", type, "`.")
|
||||
if (type %in% c("keyantibiotics", "specimen")) {
|
||||
if (type %in% c("keyantibiotics", "keyantimicrobials", "specimen")) {
|
||||
msg <- paste(msg, "Use", font_bold(paste0("col_", type), "= FALSE"), "to prevent this.")
|
||||
}
|
||||
message_(msg)
|
||||
remember_thrown_message(fn = paste0("search_", type))
|
||||
}
|
||||
}
|
||||
found
|
||||
@@ -390,6 +398,9 @@ word_wrap <- function(...,
|
||||
# format backticks
|
||||
msg <- gsub("(`.+?`)", font_grey_bg("\\1"), msg)
|
||||
|
||||
# clean introduced whitespace between fullstops
|
||||
msg <- gsub("[.] +[.]", "..", msg)
|
||||
|
||||
msg
|
||||
}
|
||||
|
||||
@@ -506,7 +517,7 @@ dataset_UTF8_to_ASCII <- function(df) {
|
||||
|
||||
# for eucast_rules() and mdro(), creates markdown output with URLs and names
|
||||
create_eucast_ab_documentation <- function() {
|
||||
x <- trimws(unique(toupper(unlist(strsplit(eucast_rules_file$then_change_these_antibiotics, ",")))))
|
||||
x <- trimws(unique(toupper(unlist(strsplit(EUCAST_RULES_DF$then_change_these_antibiotics, ",")))))
|
||||
ab <- character()
|
||||
for (val in x) {
|
||||
if (val %in% ls(envir = asNamespace("AMR"))) {
|
||||
@@ -696,7 +707,7 @@ meet_criteria <- function(object,
|
||||
ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
|
||||
"be a finite number",
|
||||
"all be finite numbers"),
|
||||
" (i.e., not be infinite)",
|
||||
" (i.e. not be infinite)",
|
||||
call = call_depth)
|
||||
}
|
||||
if (!is.null(contains_column_class)) {
|
||||
@@ -714,11 +725,6 @@ meet_criteria <- function(object,
|
||||
}
|
||||
|
||||
get_current_data <- function(arg_name, call) {
|
||||
# check if retrieved before, then get it from package environment
|
||||
if (identical(unique_call_id(entire_session = FALSE), pkg_env$get_current_data.call)) {
|
||||
return(pkg_env$get_current_data.out)
|
||||
}
|
||||
|
||||
# try dplyr::cur_data_all() first to support dplyr groups
|
||||
# only useful for e.g. dplyr::filter(), dplyr::mutate() and dplyr::summarise()
|
||||
# not useful (throws error) with e.g. dplyr::select() - but that will be caught later in this function
|
||||
@@ -726,72 +732,32 @@ get_current_data <- function(arg_name, call) {
|
||||
if (!is.null(cur_data_all)) {
|
||||
out <- tryCatch(cur_data_all(), error = function(e) NULL)
|
||||
if (is.data.frame(out)) {
|
||||
out <- structure(out, type = "dplyr_cur_data_all")
|
||||
pkg_env$get_current_data.call <- unique_call_id(entire_session = FALSE)
|
||||
pkg_env$get_current_data.out <- out
|
||||
return(out)
|
||||
return(structure(out, type = "dplyr_cur_data_all"))
|
||||
}
|
||||
}
|
||||
|
||||
if (getRversion() < "3.2") {
|
||||
# R-3.0 and R-3.1 do not have an `x` element in the call stack, rendering this function useless
|
||||
if (is.na(arg_name)) {
|
||||
# like in carbapenems() etc.
|
||||
warning_("this function can only be used in R >= 3.2", call = call)
|
||||
return(data.frame())
|
||||
} else {
|
||||
# mimic a default R error, e.g. for example_isolates[which(mo_name() %like% "^ent"), ]
|
||||
stop_("argument `", arg_name, "` is missing with no default", call = call)
|
||||
}
|
||||
}
|
||||
# try a manual (base R) method, by going over all underlying environments with sys.frames()
|
||||
for (env in sys.frames()) {
|
||||
if (!is.null(env$`.Generic`)) {
|
||||
# don't check `".Generic" %in% names(env)`, because in R < 3.2, `names(env)` is always NULL
|
||||
|
||||
# try a (base R) method, by going over the complete system call stack with sys.frames()
|
||||
not_set <- TRUE
|
||||
source <- "base_R"
|
||||
frms <- lapply(sys.frames(), function(el) {
|
||||
if (not_set == TRUE && ".Generic" %in% names(el)) {
|
||||
if (tryCatch(".data" %in% names(el) && is.data.frame(el$`.data`), error = function(e) FALSE)) {
|
||||
# - - - -
|
||||
# dplyr
|
||||
# - - - -
|
||||
# an element `.data` will be in the system call stack when using dplyr::select()
|
||||
# [but not when using dplyr::filter(), dplyr::mutate() or dplyr::summarise()]
|
||||
not_set <<- FALSE
|
||||
source <<- "dplyr_selector"
|
||||
el$`.data`
|
||||
} else if (tryCatch(any(c("x", "xx") %in% names(el)), error = function(e) FALSE)) {
|
||||
# - - - -
|
||||
# base R
|
||||
# - - - -
|
||||
# an element `x` will be in this environment for only cols, e.g. `example_isolates[, carbapenems()]`
|
||||
# an element `xx` will be in this environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]`
|
||||
if (tryCatch(is.data.frame(el$xx), error = function(e) FALSE)) {
|
||||
not_set <<- FALSE
|
||||
el$xx
|
||||
} else if (tryCatch(is.data.frame(el$x))) {
|
||||
not_set <<- FALSE
|
||||
el$x
|
||||
} else {
|
||||
NULL
|
||||
}
|
||||
} else {
|
||||
NULL
|
||||
if (!is.null(env$`.data`) && is.data.frame(env$`.data`)) {
|
||||
# an element `.data` will be in the environment when using `dplyr::select()`
|
||||
# (but not when using `dplyr::filter()`, `dplyr::mutate()` or `dplyr::summarise()`)
|
||||
return(structure(env$`.data`, type = "dplyr_selector"))
|
||||
|
||||
} else if (!is.null(env$xx) && is.data.frame(env$xx)) {
|
||||
# an element `xx` will be in the environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]`
|
||||
return(structure(env$xx, type = "base_R"))
|
||||
|
||||
} else if (!is.null(env$x) && is.data.frame(env$x)) {
|
||||
# an element `x` will be in the environment for only cols, e.g. `example_isolates[, carbapenems()]`
|
||||
return(structure(env$x, type = "base_R"))
|
||||
}
|
||||
} else {
|
||||
NULL
|
||||
}
|
||||
})
|
||||
|
||||
# lookup the matched frame and return its value: a data.frame
|
||||
vars_df <- tryCatch(frms[[which(!vapply(FUN.VALUE = logical(1), frms, is.null))]], error = function(e) NULL)
|
||||
if (is.data.frame(vars_df)) {
|
||||
out <- structure(vars_df, type = source)
|
||||
pkg_env$get_current_data.call <- unique_call_id(entire_session = FALSE)
|
||||
pkg_env$get_current_data.out <- out
|
||||
return(out)
|
||||
}
|
||||
|
||||
# nothing worked, so:
|
||||
# no data.frame found, so an error must be returned:
|
||||
if (is.na(arg_name)) {
|
||||
if (isTRUE(is.numeric(call))) {
|
||||
fn <- as.character(sys.call(call + 1)[1])
|
||||
@@ -803,10 +769,11 @@ get_current_data <- function(arg_name, call) {
|
||||
} else {
|
||||
examples <- ""
|
||||
}
|
||||
stop_("this function must be used inside valid dplyr selection verbs or inside a data.frame call",
|
||||
stop_("this function must be used inside a `dplyr` verb or `data.frame` call",
|
||||
examples,
|
||||
call = call)
|
||||
} else {
|
||||
# mimic a base R error that the argument is missing
|
||||
stop_("argument `", arg_name, "` is missing with no default", call = call)
|
||||
}
|
||||
}
|
||||
@@ -821,19 +788,19 @@ get_current_column <- function() {
|
||||
}
|
||||
}
|
||||
|
||||
# cur_column() doesn't always work (only allowed for conditions set by dplyr), but it's probably still possible:
|
||||
frms <- lapply(sys.frames(), function(el) {
|
||||
if ("i" %in% names(el)) {
|
||||
if ("tibble_vars" %in% names(el)) {
|
||||
# cur_column() doesn't always work (only allowed for certain conditions set by dplyr), but it's probably still possible:
|
||||
frms <- lapply(sys.frames(), function(env) {
|
||||
if (!is.null(env$i)) {
|
||||
if (!is.null(env$tibble_vars)) {
|
||||
# for mutate_if()
|
||||
el$tibble_vars[el$i]
|
||||
env$tibble_vars[env$i]
|
||||
} else {
|
||||
# for mutate(across())
|
||||
df <- tryCatch(get_current_data(NA, 0), error = function(e) NULL)
|
||||
if (is.data.frame(df)) {
|
||||
colnames(df)[el$i]
|
||||
colnames(df)[env$i]
|
||||
} else {
|
||||
el$i
|
||||
env$i
|
||||
}
|
||||
}
|
||||
} else {
|
||||
@@ -851,7 +818,7 @@ get_current_column <- function() {
|
||||
}
|
||||
|
||||
is_null_or_grouped_tbl <- function(x) {
|
||||
# attribute "grouped_df" might change at one point, so only set in one place; here.
|
||||
# class "grouped_df" might change at one point, so only set in one place; here.
|
||||
is.null(x) || inherits(x, "grouped_df")
|
||||
}
|
||||
|
||||
@@ -860,7 +827,7 @@ unique_call_id <- function(entire_session = FALSE) {
|
||||
c(envir = "session",
|
||||
call = "session")
|
||||
} else {
|
||||
# combination of environment ID (like "0x7fed4ee8c848")
|
||||
# combination of environment ID (such as "0x7fed4ee8c848")
|
||||
# and highest system call
|
||||
call <- paste0(deparse(sys.calls()[[1]]), collapse = "")
|
||||
if (!interactive() || call %like% "run_test_dir|test_all|tinytest|test_package|testthat") {
|
||||
@@ -872,16 +839,18 @@ unique_call_id <- function(entire_session = FALSE) {
|
||||
}
|
||||
}
|
||||
|
||||
remember_thrown_message <- function(fn, entire_session = FALSE) {
|
||||
message_not_thrown_before <- function(fn, entire_session = FALSE) {
|
||||
# this is to prevent that messages/notes will be printed for every dplyr group
|
||||
# e.g. this would show a msg 4 times: example_isolates %>% group_by(hospital_id) %>% filter(mo_is_gram_negative())
|
||||
assign(x = paste0("thrown_msg.", fn),
|
||||
value = unique_call_id(entire_session = entire_session),
|
||||
envir = pkg_env)
|
||||
}
|
||||
|
||||
message_not_thrown_before <- function(fn, entire_session = FALSE) {
|
||||
is.null(pkg_env[[paste0("thrown_msg.", fn)]]) || !identical(pkg_env[[paste0("thrown_msg.", fn)]], unique_call_id(entire_session))
|
||||
test_out <- is.null(pkg_env[[paste0("thrown_msg.", fn)]]) || !identical(pkg_env[[paste0("thrown_msg.", fn)]],
|
||||
unique_call_id(entire_session = entire_session))
|
||||
if (isTRUE(test_out)) {
|
||||
# message was not thrown before - remember this so on the next run it will return FALSE:
|
||||
assign(x = paste0("thrown_msg.", fn),
|
||||
value = unique_call_id(entire_session = entire_session),
|
||||
envir = pkg_env)
|
||||
}
|
||||
test_out
|
||||
}
|
||||
|
||||
has_colour <- function() {
|
||||
@@ -980,8 +949,8 @@ font_grey_bg <- function(..., collapse = " ") {
|
||||
# similar to HTML #444444
|
||||
try_colour(..., before = "\033[48;5;238m", after = "\033[49m", collapse = collapse)
|
||||
} else {
|
||||
# similar to HTML #eeeeee
|
||||
try_colour(..., before = "\033[48;5;254m", after = "\033[49m", collapse = collapse)
|
||||
# similar to HTML #f0f0f0
|
||||
try_colour(..., before = "\033[48;5;255m", after = "\033[49m", collapse = collapse)
|
||||
}
|
||||
}
|
||||
font_green_bg <- function(..., collapse = " ") {
|
||||
|
||||
@@ -325,9 +325,9 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
|
||||
function(y) {
|
||||
for (i in seq_len(length(y))) {
|
||||
for (lang in LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED != "en"]) {
|
||||
y[i] <- ifelse(tolower(y[i]) %in% tolower(translations_file[, lang, drop = TRUE]),
|
||||
translations_file[which(tolower(translations_file[, lang, drop = TRUE]) == tolower(y[i]) &
|
||||
!isFALSE(translations_file$fixed)), "pattern"],
|
||||
y[i] <- ifelse(tolower(y[i]) %in% tolower(TRANSLATIONS[, lang, drop = TRUE]),
|
||||
TRANSLATIONS[which(tolower(TRANSLATIONS[, lang, drop = TRUE]) == tolower(y[i]) &
|
||||
!isFALSE(TRANSLATIONS$fixed)), "pattern"],
|
||||
y[i])
|
||||
}
|
||||
}
|
||||
@@ -580,6 +580,15 @@ unique.ab <- function(x, incomparables = FALSE, ...) {
|
||||
y
|
||||
}
|
||||
|
||||
#' @method rep ab
|
||||
#' @export
|
||||
#' @noRd
|
||||
rep.ab <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
|
||||
generalise_antibiotic_name <- function(x) {
|
||||
x <- toupper(x)
|
||||
# remove suffices
|
||||
|
||||
+167
-100
@@ -25,18 +25,19 @@
|
||||
|
||||
#' Antibiotic Class Selectors
|
||||
#'
|
||||
#' These functions help to filter and select columns with antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. \strong{\Sexpr{ifelse(getRversion() < "3.2", paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
|
||||
#' These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.
|
||||
#' @inheritSection lifecycle Stable Lifecycle
|
||||
#' @param ab_class an antimicrobial class, such as `"carbapenems"`. The columns `group`, `atc_group1` and `atc_group2` of the [antibiotics] data set will be searched (case-insensitive) for this value.
|
||||
#' @param only_rsi_columns a [logical] to indicate whether only columns of class `<rsi>` must be selected (defaults to `FALSE`), see [as.rsi()]
|
||||
#' @details \strong{\Sexpr{ifelse(getRversion() < "3.2", paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
|
||||
#' @param only_treatable a [logical] to indicate whether agents that are only for laboratory tests should be excluded (defaults to `TRUE`), such as gentamicin-high (`GEH`) and imipenem/EDTA (`IPE`)
|
||||
#' @details
|
||||
#' These functions can be used in data set calls for selecting columns and filtering rows. They are heavily inspired by the [Tidyverse selection helpers][tidyselect::language] such as [`everything()`][tidyselect::everything()], but also work in base \R and not only in `dplyr` verbs. Nonetheless, they are very convenient to use with `dplyr` functions such as [`select()`][dplyr::select()], [`filter()`][dplyr::filter()] and [`summarise()`][dplyr::summarise()], see *Examples*.
|
||||
#'
|
||||
#' All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) according to the [antibiotics] data set. This means that a selector such as [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc. Use the [ab_class()] function to filter/select on a manually defined antibiotic class.
|
||||
#'
|
||||
#' These functions can be used in data set calls for selecting columns and filtering rows, see *Examples*. They support base R, but work more convenient in dplyr functions such as [`select()`][dplyr::select()], [`filter()`][dplyr::filter()] and [`summarise()`][dplyr::summarise()].
|
||||
#' @section Full list of supported agents:
|
||||
#'
|
||||
#' All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) in the [antibiotics] data set. This means that a selector like e.g. [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
|
||||
#'
|
||||
#' The group of betalactams consists of all carbapenems, cephalosporins and penicillins.
|
||||
#' `r paste0("* ", sapply(c("AMINOGLYCOSIDES", "AMINOPENICILLINS", "BETALACTAMS", "CARBAPENEMS", "CEPHALOSPORINS", "CEPHALOSPORINS_1ST", "CEPHALOSPORINS_2ND", "CEPHALOSPORINS_3RD", "CEPHALOSPORINS_4TH", "CEPHALOSPORINS_5TH", "FLUOROQUINOLONES", "GLYCOPEPTIDES", "LINCOSAMIDES", "LIPOGLYCOPEPTIDES", "MACROLIDES", "OXAZOLIDINONES", "PENICILLINS", "POLYMYXINS", "STREPTOGRAMINS", "QUINOLONES", "TETRACYCLINES", "UREIDOPENICILLINS"), function(x) paste0("``", tolower(x), "()`` can select ", vector_and(paste0(ab_name(eval(parse(text = x), envir = asNamespace("AMR")), language = NULL, tolower = TRUE), " (", eval(parse(text = x), envir = asNamespace("AMR")), ")"), quotes = FALSE))), "\n", collapse = "")`
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @name antibiotic_class_selectors
|
||||
#' @export
|
||||
@@ -46,7 +47,7 @@
|
||||
#' # `example_isolates` is a data set available in the AMR package.
|
||||
#' # See ?example_isolates.
|
||||
#'
|
||||
#' # Base R ------------------------------------------------------------------
|
||||
#' # base R ------------------------------------------------------------------
|
||||
#'
|
||||
#' # select columns 'IPM' (imipenem) and 'MEM' (meropenem)
|
||||
#' example_isolates[, carbapenems()]
|
||||
@@ -104,7 +105,6 @@
|
||||
#' example_isolates %>%
|
||||
#' select(mo, ab_class("mycobact"))
|
||||
#'
|
||||
#'
|
||||
#' # get bug/drug combinations for only macrolides in Gram-positives:
|
||||
#' example_isolates %>%
|
||||
#' filter(mo_is_gram_positive()) %>%
|
||||
@@ -112,178 +112,257 @@
|
||||
#' bug_drug_combinations() %>%
|
||||
#' format()
|
||||
#'
|
||||
#'
|
||||
#' data.frame(some_column = "some_value",
|
||||
#' J01CA01 = "S") %>% # ATC code of ampicillin
|
||||
#' select(penicillins()) # only the 'J01CA01' column will be selected
|
||||
#'
|
||||
#'
|
||||
#' # with dplyr 1.0.0 and higher (that adds 'across()'), this is all equal:
|
||||
#' # (though the row names on the first are more correct)
|
||||
#' example_isolates[carbapenems() == "R", ]
|
||||
#' example_isolates %>% filter(carbapenems() == "R")
|
||||
#' example_isolates %>% filter(across(carbapenems(), ~.x == "R"))
|
||||
#' }
|
||||
#' }
|
||||
ab_class <- function(ab_class,
|
||||
only_rsi_columns = FALSE) {
|
||||
ab_selector(ab_class, function_name = "ab_class", only_rsi_columns = only_rsi_columns)
|
||||
only_rsi_columns = FALSE,
|
||||
only_treatable = TRUE) {
|
||||
meet_criteria(ab_class, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
|
||||
ab_selector(NULL, only_rsi_columns = only_rsi_columns, ab_class = ab_class, only_treatable = only_treatable)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
aminoglycosides <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("aminoglycoside", function_name = "aminoglycosides", only_rsi_columns = only_rsi_columns)
|
||||
aminoglycosides <- function(only_rsi_columns = FALSE, only_treatable = TRUE) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
|
||||
ab_selector("aminoglycosides", only_rsi_columns = only_rsi_columns, only_treatable = only_treatable)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
betalactams <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("carbapenem|cephalosporin|penicillin", function_name = "betalactams", only_rsi_columns = only_rsi_columns)
|
||||
aminopenicillins <- function(only_rsi_columns = FALSE) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("aminopenicillins", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
carbapenems <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("carbapenem", function_name = "carbapenems", only_rsi_columns = only_rsi_columns)
|
||||
betalactams <- function(only_rsi_columns = FALSE, only_treatable = TRUE) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
|
||||
ab_selector("betalactams", only_rsi_columns = only_rsi_columns, only_treatable = only_treatable)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
carbapenems <- function(only_rsi_columns = FALSE, only_treatable = TRUE) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
|
||||
ab_selector("carbapenems", only_rsi_columns = only_rsi_columns, only_treatable = only_treatable)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("cephalosporin", function_name = "cephalosporins", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("cephalosporins", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins_1st <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("cephalosporins.*1", function_name = "cephalosporins_1st", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("cephalosporins_1st", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins_2nd <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("cephalosporins.*2", function_name = "cephalosporins_2nd", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("cephalosporins_2nd", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins_3rd <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("cephalosporins.*3", function_name = "cephalosporins_3rd", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("cephalosporins_3rd", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins_4th <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("cephalosporins.*4", function_name = "cephalosporins_4th", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("cephalosporins_4th", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
cephalosporins_5th <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("cephalosporins.*5", function_name = "cephalosporins_5th", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("cephalosporins_5th", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
fluoroquinolones <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("fluoroquinolone", function_name = "fluoroquinolones", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("fluoroquinolones", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
glycopeptides <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("glycopeptide", function_name = "glycopeptides", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("glycopeptides", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
lincosamides <- function(only_rsi_columns = FALSE) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("lincosamides", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
lipoglycopeptides <- function(only_rsi_columns = FALSE) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("lipoglycopeptides", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
macrolides <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("macrolide", function_name = "macrolides", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("macrolides", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
oxazolidinones <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("oxazolidinone", function_name = "oxazolidinones", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("oxazolidinones", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
penicillins <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("penicillin", function_name = "penicillins", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("penicillins", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
polymyxins <- function(only_rsi_columns = FALSE, only_treatable = TRUE) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
|
||||
ab_selector("polymyxins", only_rsi_columns = only_rsi_columns, only_treatable = only_treatable)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
streptogramins <- function(only_rsi_columns = FALSE) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("streptogramins", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
quinolones <- function(only_rsi_columns = FALSE) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("quinolones", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
tetracyclines <- function(only_rsi_columns = FALSE) {
|
||||
ab_selector("tetracycline", function_name = "tetracyclines", only_rsi_columns = only_rsi_columns)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("tetracyclines", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
ab_selector <- function(ab_class,
|
||||
function_name,
|
||||
only_rsi_columns) {
|
||||
meet_criteria(ab_class, allow_class = "character", has_length = 1, .call_depth = 1)
|
||||
meet_criteria(function_name, allow_class = "character", has_length = 1, .call_depth = 1)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1, .call_depth = 1)
|
||||
#' @rdname antibiotic_class_selectors
|
||||
#' @export
|
||||
ureidopenicillins <- function(only_rsi_columns = FALSE) {
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
ab_selector("ureidopenicillins", only_rsi_columns = only_rsi_columns)
|
||||
}
|
||||
|
||||
if (getRversion() < "3.2") {
|
||||
warning_("antibiotic class selectors such as ", function_name,
|
||||
"() require R version 3.2 or later - you have ", R.version.string,
|
||||
call = FALSE)
|
||||
return(NULL)
|
||||
}
|
||||
|
||||
# to improve speed, get_current_data() and get_column_abx() only run once when e.g. in a select or group call
|
||||
ab_selector <- function(function_name,
|
||||
only_rsi_columns,
|
||||
only_treatable = FALSE,
|
||||
ab_class = NULL) {
|
||||
# get_current_data() has to run each time, for cases where e.g., filter() and select() are used in same call
|
||||
# but it only takes a couple of milliseconds
|
||||
vars_df <- get_current_data(arg_name = NA, call = -3)
|
||||
# to improve speed, get_column_abx() will only run once when e.g. in a select or group call
|
||||
ab_in_data <- get_column_abx(vars_df, info = FALSE, only_rsi_columns = only_rsi_columns, sort = FALSE)
|
||||
|
||||
# untreatable drugs
|
||||
untreatable <- antibiotics[which(antibiotics$name %like% "-high|EDTA|polysorbate"), "ab", drop = TRUE]
|
||||
if (only_treatable == TRUE & any(untreatable %in% names(ab_in_data))) {
|
||||
if (message_not_thrown_before(paste0("ab_class.untreatable.", function_name), entire_session = TRUE)) {
|
||||
warning_("Some agents in `", function_name, "()` were ignored since they cannot be used for treating patients: ",
|
||||
vector_and(ab_name(names(ab_in_data)[names(ab_in_data) %in% untreatable],
|
||||
language = NULL,
|
||||
tolower = TRUE),
|
||||
quotes = FALSE,
|
||||
sort = TRUE), ". They can be included using `", function_name, "(only_treatable = FALSE)`. ",
|
||||
"This warning will be shown once per session.",
|
||||
call = FALSE)
|
||||
}
|
||||
ab_in_data <- ab_in_data[!names(ab_in_data) %in% untreatable]
|
||||
}
|
||||
|
||||
if (length(ab_in_data) == 0) {
|
||||
message_("No antimicrobial agents found.")
|
||||
message_("No antimicrobial agents found in the data.")
|
||||
return(NULL)
|
||||
}
|
||||
|
||||
ab_reference <- subset(antibiotics,
|
||||
group %like% ab_class |
|
||||
atc_group1 %like% ab_class |
|
||||
atc_group2 %like% ab_class)
|
||||
ab_group <- find_ab_group(ab_class)
|
||||
if (ab_group == "") {
|
||||
ab_group <- paste0("'", ab_class, "'")
|
||||
examples <- ""
|
||||
if (is.null(ab_class)) {
|
||||
# their upper case equivalent are vectors with class <ab>, created in data-raw/_internals.R
|
||||
abx <- get(toupper(function_name), envir = asNamespace("AMR"))
|
||||
ab_group <- function_name
|
||||
examples <- paste0(" (such as ", vector_or(ab_name(sample(abx, size = min(2, length(abx)), replace = FALSE),
|
||||
tolower = TRUE,
|
||||
language = NULL),
|
||||
quotes = FALSE), ")")
|
||||
} else {
|
||||
# this for the 'manual' ab_class() function
|
||||
abx <- subset(AB_lookup,
|
||||
group %like% ab_class |
|
||||
atc_group1 %like% ab_class |
|
||||
atc_group2 %like% ab_class)$ab
|
||||
ab_group <- find_ab_group(ab_class)
|
||||
function_name <- "ab_class"
|
||||
examples <- paste0(" (such as ", find_ab_names(ab_class, 2), ")")
|
||||
}
|
||||
# get the columns with a group names in the chosen ab class
|
||||
agents <- ab_in_data[names(ab_in_data) %in% ab_reference$ab]
|
||||
|
||||
if (message_not_thrown_before(function_name)) {
|
||||
# get the columns with a group names in the chosen ab class
|
||||
agents <- ab_in_data[names(ab_in_data) %in% abx]
|
||||
|
||||
if (message_not_thrown_before(paste0(function_name, ".", paste(sort(agents), collapse = "|")))) {
|
||||
if (length(agents) == 0) {
|
||||
message_("No antimicrobial agents of class ", ab_group, " found", examples, ".")
|
||||
message_("No antimicrobial agents of class '", ab_group, "' found", examples, ".")
|
||||
} else {
|
||||
agents_formatted <- paste0("'", font_bold(agents, collapse = NULL), "'")
|
||||
agents_names <- ab_name(names(agents), tolower = TRUE, language = NULL)
|
||||
need_name <- tolower(gsub("[^a-zA-Z]", "", agents)) != tolower(gsub("[^a-zA-Z]", "", agents_names))
|
||||
agents_formatted[need_name] <- paste0(agents_formatted[need_name],
|
||||
" (", agents_names[need_name], ")")
|
||||
message_("For `", function_name, "(", ifelse(function_name == "ab_class", paste0("\"", ab_class, "\""), ""), ")` using ",
|
||||
ifelse(length(agents) == 1, "column: ", "columns: "),
|
||||
vector_and(agents_formatted, quotes = FALSE))
|
||||
need_name <- generalise_antibiotic_name(agents) != generalise_antibiotic_name(agents_names)
|
||||
agents_formatted[need_name] <- paste0(agents_formatted[need_name], " (", agents_names[need_name], ")")
|
||||
message_("For `", function_name, "(",
|
||||
ifelse(function_name == "ab_class",
|
||||
paste0("\"", ab_class, "\""),
|
||||
""),
|
||||
")` using ",
|
||||
ifelse(length(agents) == 1, "column ", "columns "),
|
||||
vector_and(agents_formatted, quotes = FALSE, sort = FALSE))
|
||||
}
|
||||
remember_thrown_message(function_name)
|
||||
}
|
||||
|
||||
if (!is.null(attributes(vars_df)$type) &&
|
||||
attributes(vars_df)$type %in% c("dplyr_cur_data_all", "base_R") &&
|
||||
!any(as.character(sys.calls()) %like% paste0("(across|if_any|if_all)\\((c\\()?[a-z(), ]*", function_name))) {
|
||||
structure(unname(agents),
|
||||
class = c("ab_selector", "character"))
|
||||
} else {
|
||||
# don't return with "ab_selector" class if method is a dplyr selector,
|
||||
# dplyr::select() will complain:
|
||||
# > Subscript has the wrong type `ab_selector`.
|
||||
# > It must be numeric or character.
|
||||
unname(agents)
|
||||
}
|
||||
structure(unname(agents),
|
||||
class = c("ab_selector", "character"))
|
||||
}
|
||||
|
||||
#' @method c ab_selector
|
||||
@@ -321,7 +400,6 @@ all_any_ab_selector <- function(type, ..., na.rm = TRUE) {
|
||||
#' @export
|
||||
#' @noRd
|
||||
all.ab_selector <- function(..., na.rm = FALSE) {
|
||||
# this is all() for
|
||||
all_any_ab_selector("all", ..., na.rm = na.rm)
|
||||
}
|
||||
|
||||
@@ -367,7 +445,6 @@ any.ab_selector_any_all <- function(..., na.rm = FALSE) {
|
||||
`==.ab_selector` <- function(e1, e2) {
|
||||
calls <- as.character(match.call())
|
||||
fn_name <- calls[2]
|
||||
# keep only the ... in c(...)
|
||||
fn_name <- gsub("^(c\\()(.*)(\\))$", "\\2", fn_name)
|
||||
if (is_any(fn_name)) {
|
||||
type <- "any"
|
||||
@@ -390,7 +467,6 @@ any.ab_selector_any_all <- function(..., na.rm = FALSE) {
|
||||
`!=.ab_selector` <- function(e1, e2) {
|
||||
calls <- as.character(match.call())
|
||||
fn_name <- calls[2]
|
||||
# keep only the ... in c(...)
|
||||
fn_name <- gsub("^(c\\()(.*)(\\))$", "\\2", fn_name)
|
||||
if (is_any(fn_name)) {
|
||||
type <- "any"
|
||||
@@ -423,28 +499,16 @@ is_all <- function(el1) {
|
||||
|
||||
|
||||
find_ab_group <- function(ab_class) {
|
||||
ab_class[ab_class == "carbapenem|cephalosporin|penicillin"] <- "betalactam"
|
||||
ab_class <- gsub("[^a-zA-Z0-9]", ".*", ab_class)
|
||||
ifelse(ab_class %in% c("aminoglycoside",
|
||||
"betalactam",
|
||||
"carbapenem",
|
||||
"cephalosporin",
|
||||
"fluoroquinolone",
|
||||
"glycopeptide",
|
||||
"macrolide",
|
||||
"oxazolidinone",
|
||||
"tetracycline"),
|
||||
paste0(ab_class, "s"),
|
||||
antibiotics %pm>%
|
||||
subset(group %like% ab_class |
|
||||
atc_group1 %like% ab_class |
|
||||
atc_group2 %like% ab_class) %pm>%
|
||||
pm_pull(group) %pm>%
|
||||
unique() %pm>%
|
||||
tolower() %pm>%
|
||||
sort() %pm>%
|
||||
paste(collapse = "/")
|
||||
)
|
||||
AB_lookup %pm>%
|
||||
subset(group %like% ab_class |
|
||||
atc_group1 %like% ab_class |
|
||||
atc_group2 %like% ab_class) %pm>%
|
||||
pm_pull(group) %pm>%
|
||||
unique() %pm>%
|
||||
tolower() %pm>%
|
||||
sort() %pm>%
|
||||
paste(collapse = "/")
|
||||
}
|
||||
|
||||
find_ab_names <- function(ab_group, n = 3) {
|
||||
@@ -462,6 +526,9 @@ find_ab_names <- function(ab_group, n = 3) {
|
||||
antibiotics$atc_group2 %like% ab_group) &
|
||||
antibiotics$ab %unlike% "[0-9]$"), ]$name
|
||||
}
|
||||
if (length(drugs) == 0) {
|
||||
return("??")
|
||||
}
|
||||
vector_or(ab_name(sample(drugs, size = min(n, length(drugs)), replace = FALSE),
|
||||
tolower = TRUE,
|
||||
language = NULL),
|
||||
|
||||
+6
-1
@@ -29,6 +29,7 @@
|
||||
#' @inheritSection lifecycle Stable Lifecycle
|
||||
#' @param x any (vector of) text that can be coerced to a valid antibiotic code with [as.ab()]
|
||||
#' @param tolower a [logical] to indicate whether the first [character] of every output should be transformed to a lower case [character]. This will lead to e.g. "polymyxin B" and not "polymyxin b".
|
||||
#' @param snake_case a [logical] to indicate whether the names should be returned in so-called [snake case](https://en.wikipedia.org/wiki/Snake_case): in lower case and all spaces/slashes replaced with an underscore (`_`). This is useful for column renaming.
|
||||
#' @param property one of the column names of one of the [antibiotics] data set
|
||||
#' @param language language of the returned text, defaults to system language (see [get_locale()]) and can also be set with `getOption("AMR_locale")`. Use `language = NULL` or `language = ""` to prevent translation.
|
||||
#' @param administration way of administration, either `"oral"` or `"iv"`
|
||||
@@ -88,10 +89,11 @@
|
||||
#' ab_atc("cephtriaxone")
|
||||
#' ab_atc("cephthriaxone")
|
||||
#' ab_atc("seephthriaaksone")
|
||||
ab_name <- function(x, language = get_locale(), tolower = FALSE, ...) {
|
||||
ab_name <- function(x, language = get_locale(), tolower = FALSE, snake_case = FALSE, ...) {
|
||||
meet_criteria(x, allow_NA = TRUE)
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(tolower, allow_class = "logical", has_length = 1)
|
||||
meet_criteria(snake_case, allow_class = "logical", has_length = 1)
|
||||
|
||||
x <- translate_AMR(ab_validate(x = x, property = "name", ...), language = language, only_affect_ab_names = TRUE)
|
||||
if (tolower == TRUE) {
|
||||
@@ -99,6 +101,9 @@ ab_name <- function(x, language = get_locale(), tolower = FALSE, ...) {
|
||||
# as we want "polymyxin B", not "polymyxin b"
|
||||
x <- gsub("^([A-Z])", "\\L\\1", x, perl = TRUE)
|
||||
}
|
||||
if (snake_case == TRUE) {
|
||||
x <- tolower(gsub("[^a-zA-Z0-9]+", "_", x))
|
||||
}
|
||||
x
|
||||
}
|
||||
|
||||
|
||||
@@ -61,7 +61,7 @@
|
||||
#' Matthijs S. Berends \cr
|
||||
#' m.s.berends \[at\] umcg \[dot\] nl \cr
|
||||
#' University of Groningen
|
||||
#' Department of Medical Microbiology and Infection Prevention
|
||||
#' Department of Medical Microbiology and Infection Prevention \cr
|
||||
#' University Medical Center Groningen \cr
|
||||
#' Post Office Box 30001 \cr
|
||||
#' 9700 RB Groningen \cr
|
||||
|
||||
@@ -25,7 +25,7 @@
|
||||
|
||||
#' Determine Bug-Drug Combinations
|
||||
#'
|
||||
#' Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use [format()] on the result to prettify it to a publicable/printable format, see *Examples*.
|
||||
#' Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use [format()] on the result to prettify it to a publishable/printable format, see *Examples*.
|
||||
#' @inheritSection lifecycle Stable Lifecycle
|
||||
#' @inheritParams eucast_rules
|
||||
#' @param combine_IR a [logical] to indicate whether values R and I should be summed
|
||||
@@ -81,7 +81,7 @@ bug_drug_combinations <- function(x,
|
||||
unique_mo <- sort(unique(x[, col_mo, drop = TRUE]))
|
||||
|
||||
# select only groups and antibiotics
|
||||
if (inherits(x.bak, "grouped_df")) {
|
||||
if (is_null_or_grouped_tbl(x.bak)) {
|
||||
data_has_groups <- TRUE
|
||||
groups <- setdiff(names(attributes(x.bak)$groups), ".rows")
|
||||
x <- x[, c(groups, col_mo, colnames(x)[vapply(FUN.VALUE = logical(1), x, is.rsi)]), drop = FALSE]
|
||||
@@ -113,7 +113,7 @@ bug_drug_combinations <- function(x,
|
||||
data.frame(S = m["S", ], I = m["I", ], R = m["R", ], stringsAsFactors = FALSE)
|
||||
})
|
||||
merged <- do.call(rbind, pivot)
|
||||
out_group <- data.frame(mo = unique_mo[i],
|
||||
out_group <- data.frame(mo = rep(unique_mo[i], NROW(merged)),
|
||||
ab = rownames(merged),
|
||||
S = merged$S,
|
||||
I = merged$I,
|
||||
|
||||
@@ -83,6 +83,12 @@
|
||||
#' n2 = n_rsi(CIP), # same - analogous to n_distinct
|
||||
#' total = n()) # NOT the number of tested isolates!
|
||||
#'
|
||||
#' # Number of available isolates for a whole antibiotic class
|
||||
#' # (i.e., in this data set columns GEN, TOB, AMK, KAN)
|
||||
#' example_isolates %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(across(aminoglycosides(), n_rsi))
|
||||
#'
|
||||
#' # Count co-resistance between amoxicillin/clav acid and gentamicin,
|
||||
#' # so we can see that combination therapy does a lot more than mono therapy.
|
||||
#' # Please mind that `susceptibility()` calculates percentages right away instead.
|
||||
@@ -108,81 +114,95 @@
|
||||
#' }
|
||||
#' }
|
||||
count_resistant <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_susceptible <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_R <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_IR <- function(..., only_all_tested = FALSE) {
|
||||
if (message_not_thrown_before("count_IR")) {
|
||||
warning_("Using count_IR() is discouraged; use count_resistant() instead to not consider \"I\" being resistant.", call = FALSE)
|
||||
remember_thrown_message("count_IR")
|
||||
if (message_not_thrown_before("count_IR", entire_session = TRUE)) {
|
||||
message_("Using `count_IR()` is discouraged; use `count_resistant()` instead to not consider \"I\" being resistant. This note will be shown once for this session.", as_note = FALSE)
|
||||
}
|
||||
rsi_calc(...,
|
||||
ab_result = c("I", "R"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("I", "R"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_I <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = "I",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "I",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_SI <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_S <- function(..., only_all_tested = FALSE) {
|
||||
if (message_not_thrown_before("count_S")) {
|
||||
warning_("Using count_S() is discouraged; use count_susceptible() instead to also consider \"I\" being susceptible.", call = FALSE)
|
||||
remember_thrown_message("count_S")
|
||||
if (message_not_thrown_before("count_S", entire_session = TRUE)) {
|
||||
message_("Using `count_S()` is discouraged; use `count_susceptible()` instead to also consider \"I\" being susceptible. This note will be shown once for this session.", as_note = FALSE)
|
||||
}
|
||||
rsi_calc(...,
|
||||
ab_result = "S",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "S",
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
#' @export
|
||||
count_all <- function(..., only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I", "R"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I", "R"),
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = TRUE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname count
|
||||
@@ -196,11 +216,13 @@ count_df <- function(data,
|
||||
language = get_locale(),
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE) {
|
||||
rsi_calc_df(type = "count",
|
||||
data = data,
|
||||
translate_ab = translate_ab,
|
||||
language = language,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR,
|
||||
combine_SI_missing = missing(combine_SI))
|
||||
tryCatch(
|
||||
rsi_calc_df(type = "count",
|
||||
data = data,
|
||||
translate_ab = translate_ab,
|
||||
language = language,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR,
|
||||
combine_SI_missing = missing(combine_SI)),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
@@ -195,6 +195,15 @@ unique.disk <- function(x, incomparables = FALSE, ...) {
|
||||
y
|
||||
}
|
||||
|
||||
#' @method rep disk
|
||||
#' @export
|
||||
#' @noRd
|
||||
rep.disk <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
get_skimmers.disk <- function(column) {
|
||||
skimr::sfl(
|
||||
|
||||
+3
-4
@@ -55,7 +55,7 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
|
||||
#' @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. Using Verbose mode takes a lot more time.
|
||||
#' @param version_breakpoints the version number to use for the EUCAST Clinical Breakpoints guideline. Can be either `r vector_or(names(EUCAST_VERSION_BREAKPOINTS), reverse = TRUE)`.
|
||||
#' @param version_expertrules the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be either `r vector_or(names(EUCAST_VERSION_EXPERT_RULES), reverse = TRUE)`.
|
||||
#' @param ampc_cephalosporin_resistance a [character] value that should be applied to cefotaxime, ceftriaxone and ceftazidime for AmpC de-repressed cephalosporin-resistant mutants, defaults to `NA`. Currently only works when `version_expertrules` is `3.2`; '*EUCAST Expert Rules v3.2 on Enterobacterales*' states that results of cefotaxime, ceftriaxone and ceftazidime should be reported with a note, or results should be suppressed (emptied) for these three agents. A value of `NA` (the default) for this argument will remove results for these three agents, while e.g. a value of `"R"` will make the results for these agents resistant. Use `NULL` or `FALSE` to not alter results for these three agents of AmpC de-repressed cephalosporin-resistant mutants. Using `TRUE` is equal to using `"R"`. \cr For *EUCAST Expert Rules* v3.2, this rule applies to: `r vector_and(gsub("[^a-zA-Z ]+", "", unlist(strsplit(eucast_rules_file[which(eucast_rules_file$reference.version == 3.2 & eucast_rules_file$reference.rule %like% "ampc"), "this_value"][1], "|", fixed = TRUE))), quotes = "*")`.
|
||||
#' @param ampc_cephalosporin_resistance a [character] value that should be applied to cefotaxime, ceftriaxone and ceftazidime for AmpC de-repressed cephalosporin-resistant mutants, defaults to `NA`. Currently only works when `version_expertrules` is `3.2`; '*EUCAST Expert Rules v3.2 on Enterobacterales*' states that results of cefotaxime, ceftriaxone and ceftazidime should be reported with a note, or results should be suppressed (emptied) for these three agents. A value of `NA` (the default) for this argument will remove results for these three agents, while e.g. a value of `"R"` will make the results for these agents resistant. Use `NULL` or `FALSE` to not alter results for these three agents of AmpC de-repressed cephalosporin-resistant mutants. Using `TRUE` is equal to using `"R"`. \cr For *EUCAST Expert Rules* v3.2, this rule applies to: `r vector_and(gsub("[^a-zA-Z ]+", "", unlist(strsplit(EUCAST_RULES_DF[which(EUCAST_RULES_DF$reference.version == 3.2 & EUCAST_RULES_DF$reference.rule %like% "ampc"), "this_value"][1], "|", fixed = TRUE))), quotes = "*")`.
|
||||
#' @param ... column name of an antibiotic, see section *Antibiotics* below
|
||||
#' @param ab any (vector of) text that can be coerced to a valid antibiotic code with [as.ab()]
|
||||
#' @param administration route of administration, either `r vector_or(dosage$administration)`
|
||||
@@ -561,11 +561,11 @@ eucast_rules <- function(x,
|
||||
# Official EUCAST rules ---------------------------------------------------
|
||||
eucast_notification_shown <- FALSE
|
||||
if (!is.null(list(...)$eucast_rules_df)) {
|
||||
# this allows: eucast_rules(x, eucast_rules_df = AMR:::eucast_rules_file %>% filter(is.na(have_these_values)))
|
||||
# this allows: eucast_rules(x, eucast_rules_df = AMR:::EUCAST_RULES_DF %>% filter(is.na(have_these_values)))
|
||||
eucast_rules_df <- list(...)$eucast_rules_df
|
||||
} else {
|
||||
# otherwise internal data file, created in data-raw/_internals.R
|
||||
eucast_rules_df <- eucast_rules_file
|
||||
eucast_rules_df <- EUCAST_RULES_DF
|
||||
}
|
||||
|
||||
# filter on user-set guideline versions ----
|
||||
@@ -1072,7 +1072,6 @@ eucast_dosage <- function(ab, administration = "iv", version_breakpoints = 11.0)
|
||||
message_("Dosages for antimicrobial drugs, as meant for ",
|
||||
format_eucast_version_nr(version_breakpoints, markdown = FALSE), ". ",
|
||||
font_red("This note will be shown once per session."))
|
||||
remember_thrown_message(paste0("eucast_dosage_v", gsub("[^0-9]", "", version_breakpoints)), entire_session = TRUE)
|
||||
}
|
||||
|
||||
ab <- as.ab(ab)
|
||||
|
||||
+1
-8
@@ -131,11 +131,8 @@
|
||||
#' # `example_isolates` is a data set available in the AMR package.
|
||||
#' # See ?example_isolates.
|
||||
#'
|
||||
#' example_isolates[first_isolate(example_isolates), ]
|
||||
#' \donttest{
|
||||
#' # faster way, only works in R 3.2 and later:
|
||||
#' example_isolates[first_isolate(), ]
|
||||
#'
|
||||
#' \donttest{
|
||||
#' # get all first Gram-negatives
|
||||
#' example_isolates[which(first_isolate() & mo_is_gram_negative()), ]
|
||||
#'
|
||||
@@ -267,7 +264,6 @@ first_isolate <- function(x = NULL,
|
||||
"")),
|
||||
as_note = FALSE,
|
||||
add_fn = font_black)
|
||||
remember_thrown_message("first_isolate.method")
|
||||
}
|
||||
|
||||
# try to find columns based on type
|
||||
@@ -367,7 +363,6 @@ first_isolate <- function(x = NULL,
|
||||
message_("Excluding test codes: ", toString(paste0("'", testcodes_exclude, "'")),
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
remember_thrown_message("first_isolate.excludingtestcodes")
|
||||
}
|
||||
|
||||
if (is.null(col_specimen)) {
|
||||
@@ -381,7 +376,6 @@ first_isolate <- function(x = NULL,
|
||||
message_("Excluding other than specimen group '", specimen_group, "'",
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
remember_thrown_message("first_isolate.excludingspecimen")
|
||||
}
|
||||
}
|
||||
if (!is.null(col_keyantimicrobials)) {
|
||||
@@ -477,7 +471,6 @@ first_isolate <- function(x = NULL,
|
||||
add_fn = font_black,
|
||||
as_note = FALSE)
|
||||
}
|
||||
remember_thrown_message("first_isolate.type")
|
||||
}
|
||||
type_param <- type
|
||||
|
||||
|
||||
+12
-8
@@ -370,7 +370,6 @@ scale_rsi_colours <- function(...,
|
||||
aesthetics = "fill") {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(aesthetics, allow_class = "character", is_in = c("alpha", "colour", "color", "fill", "linetype", "shape", "size"))
|
||||
|
||||
# behaviour until AMR pkg v1.5.0 and also when coming from ggplot_rsi()
|
||||
if ("colours" %in% names(list(...))) {
|
||||
original_cols <- c(S = "#3CAEA3",
|
||||
@@ -379,22 +378,25 @@ scale_rsi_colours <- function(...,
|
||||
IR = "#ED553B",
|
||||
R = "#ED553B")
|
||||
colours <- replace(original_cols, names(list(...)$colours), list(...)$colours)
|
||||
return(ggplot2::scale_fill_manual(values = colours))
|
||||
# limits = force is needed in ggplot2 3.3.4 and 3.3.5, see here;
|
||||
# https://github.com/tidyverse/ggplot2/issues/4511#issuecomment-866185530
|
||||
return(ggplot2::scale_fill_manual(values = colours, limits = force))
|
||||
}
|
||||
if (identical(unlist(list(...)), FALSE)) {
|
||||
return(invisible())
|
||||
}
|
||||
|
||||
names_susceptible <- c("S", "SI", "IS", "S+I", "I+S", "susceptible", "Susceptible",
|
||||
unique(translations_file[which(translations_file$pattern == "Susceptible"),
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible"),
|
||||
"replacement", drop = TRUE]))
|
||||
names_incr_exposure <- c("I", "intermediate", "increased exposure", "incr. exposure", "Increased exposure", "Incr. exposure",
|
||||
unique(translations_file[which(translations_file$pattern == "Intermediate"),
|
||||
names_incr_exposure <- c("I", "intermediate", "increased exposure", "incr. exposure",
|
||||
"Increased exposure", "Incr. exposure", "Susceptible, incr. exp.",
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Intermediate"),
|
||||
"replacement", drop = TRUE]),
|
||||
unique(translations_file[which(translations_file$pattern == "Incr. exposure"),
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible, incr. exp."),
|
||||
"replacement", drop = TRUE]))
|
||||
names_resistant <- c("R", "IR", "RI", "R+I", "I+R", "resistant", "Resistant",
|
||||
unique(translations_file[which(translations_file$pattern == "Resistant"),
|
||||
unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Resistant"),
|
||||
"replacement", drop = TRUE]))
|
||||
|
||||
susceptible <- rep("#3CAEA3", length(names_susceptible))
|
||||
@@ -411,7 +413,9 @@ scale_rsi_colours <- function(...,
|
||||
dots[dots == "I"] <- "#F6D55C"
|
||||
dots[dots == "R"] <- "#ED553B"
|
||||
cols <- replace(original_cols, names(dots), dots)
|
||||
ggplot2::scale_discrete_manual(aesthetics = aesthetics, values = cols)
|
||||
# limits = force is needed in ggplot2 3.3.4 and 3.3.5, see here;
|
||||
# https://github.com/tidyverse/ggplot2/issues/4511#issuecomment-866185530
|
||||
ggplot2::scale_discrete_manual(aesthetics = aesthetics, values = cols, limits = force)
|
||||
}
|
||||
|
||||
#' @rdname ggplot_rsi
|
||||
|
||||
+53
-27
@@ -97,16 +97,39 @@ guess_ab_col <- function(x = NULL, search_string = NULL, verbose = FALSE, only_r
|
||||
}
|
||||
|
||||
get_column_abx <- function(x,
|
||||
...,
|
||||
soft_dependencies = NULL,
|
||||
hard_dependencies = NULL,
|
||||
verbose = FALSE,
|
||||
info = TRUE,
|
||||
only_rsi_columns = FALSE,
|
||||
sort = TRUE,
|
||||
...) {
|
||||
reuse_previous_result = TRUE) {
|
||||
|
||||
# check if retrieved before, then get it from package environment
|
||||
if (identical(unique_call_id(entire_session = FALSE), pkg_env$get_column_abx.call)) {
|
||||
if (isTRUE(reuse_previous_result) && identical(unique_call_id(entire_session = FALSE), pkg_env$get_column_abx.call)) {
|
||||
# so within the same call, within the same environment, we got here again.
|
||||
# but we could've come from another function within the same call, so now only check the columns that changed
|
||||
|
||||
# first remove the columns that are not existing anymore
|
||||
previous <- pkg_env$get_column_abx.out
|
||||
current <- previous[previous %in% colnames(x)]
|
||||
|
||||
# then compare columns in current call with columns in original call
|
||||
new_cols <- colnames(x)[!colnames(x) %in% pkg_env$get_column_abx.checked_cols]
|
||||
if (length(new_cols) > 0) {
|
||||
# these columns did not exist in the last call, so add them
|
||||
new_cols_rsi <- get_column_abx(x[, new_cols, drop = FALSE], reuse_previous_result = FALSE, info = FALSE, sort = FALSE)
|
||||
current <- c(current, new_cols_rsi)
|
||||
# order according to columns in current call
|
||||
current <- current[match(colnames(x)[colnames(x) %in% current], current)]
|
||||
}
|
||||
|
||||
# update pkg environment to improve speed on next run
|
||||
pkg_env$get_column_abx.out <- current
|
||||
pkg_env$get_column_abx.checked_cols <- colnames(x)
|
||||
|
||||
# and return right values
|
||||
return(pkg_env$get_column_abx.out)
|
||||
}
|
||||
|
||||
@@ -123,6 +146,7 @@ get_column_abx <- function(x,
|
||||
}
|
||||
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
||||
x.bak <- x
|
||||
if (only_rsi_columns == TRUE) {
|
||||
x <- x[, which(is.rsi(x)), drop = FALSE]
|
||||
}
|
||||
@@ -163,8 +187,8 @@ get_column_abx <- function(x,
|
||||
abcode = suppressWarnings(as.ab(colnames(x), info = FALSE)),
|
||||
stringsAsFactors = FALSE)
|
||||
df_trans <- df_trans[!is.na(df_trans$abcode), , drop = FALSE]
|
||||
x <- as.character(df_trans$colnames)
|
||||
names(x) <- df_trans$abcode
|
||||
out <- as.character(df_trans$colnames)
|
||||
names(out) <- df_trans$abcode
|
||||
|
||||
# add from self-defined dots (...):
|
||||
# such as get_column_abx(example_isolates %>% rename(thisone = AMX), amox = "thisone")
|
||||
@@ -177,33 +201,34 @@ get_column_abx <- function(x,
|
||||
immediate = TRUE)
|
||||
}
|
||||
# turn all NULLs to NAs
|
||||
dots <- unlist(lapply(dots, function(x) if (is.null(x)) NA else x))
|
||||
dots <- unlist(lapply(dots, function(dot) if (is.null(dot)) NA else dot))
|
||||
names(dots) <- newnames
|
||||
dots <- dots[!is.na(names(dots))]
|
||||
# merge, but overwrite automatically determined ones by 'dots'
|
||||
x <- c(x[!x %in% dots & !names(x) %in% names(dots)], dots)
|
||||
out <- c(out[!out %in% dots & !names(out) %in% names(dots)], dots)
|
||||
# delete NAs, this will make e.g. eucast_rules(... TMP = NULL) work to prevent TMP from being used
|
||||
x <- x[!is.na(x)]
|
||||
out <- out[!is.na(out)]
|
||||
}
|
||||
|
||||
if (length(x) == 0) {
|
||||
if (length(out) == 0) {
|
||||
if (info == TRUE) {
|
||||
message_("No columns found.")
|
||||
}
|
||||
pkg_env$get_column_abx.call <- unique_call_id(entire_session = FALSE)
|
||||
pkg_env$get_column_abx.out <- x
|
||||
return(x)
|
||||
pkg_env$get_column_abx.checked_cols <- colnames(x.bak)
|
||||
pkg_env$get_column_abx.out <- out
|
||||
return(out)
|
||||
}
|
||||
|
||||
# sort on name
|
||||
if (sort == TRUE) {
|
||||
x <- x[order(names(x), x)]
|
||||
out <- out[order(names(out), out)]
|
||||
}
|
||||
duplicates <- c(x[duplicated(x)], x[duplicated(names(x))])
|
||||
duplicates <- c(out[duplicated(out)], out[duplicated(names(out))])
|
||||
duplicates <- duplicates[unique(names(duplicates))]
|
||||
x <- c(x[!names(x) %in% names(duplicates)], duplicates)
|
||||
out <- c(out[!names(out) %in% names(duplicates)], duplicates)
|
||||
if (sort == TRUE) {
|
||||
x <- x[order(names(x), x)]
|
||||
out <- out[order(names(out), out)]
|
||||
}
|
||||
|
||||
# succeeded with auto-guessing
|
||||
@@ -211,14 +236,14 @@ get_column_abx <- function(x,
|
||||
message_(" OK.", add_fn = list(font_green, font_bold), as_note = FALSE)
|
||||
}
|
||||
|
||||
for (i in seq_len(length(x))) {
|
||||
if (info == TRUE & verbose == TRUE & !names(x[i]) %in% names(duplicates)) {
|
||||
message_("Using column '", font_bold(x[i]), "' as input for ", names(x)[i],
|
||||
" (", ab_name(names(x)[i], tolower = TRUE, language = NULL), ").")
|
||||
for (i in seq_len(length(out))) {
|
||||
if (info == TRUE & verbose == TRUE & !names(out[i]) %in% names(duplicates)) {
|
||||
message_("Using column '", font_bold(out[i]), "' as input for ", names(out)[i],
|
||||
" (", ab_name(names(out)[i], tolower = TRUE, language = NULL), ").")
|
||||
}
|
||||
if (info == TRUE & names(x[i]) %in% names(duplicates)) {
|
||||
warning_(paste0("Using column '", font_bold(x[i]), "' as input for ", names(x)[i],
|
||||
" (", ab_name(names(x)[i], tolower = TRUE, language = NULL),
|
||||
if (info == TRUE & names(out[i]) %in% names(duplicates)) {
|
||||
warning_(paste0("Using column '", font_bold(out[i]), "' as input for ", names(out)[i],
|
||||
" (", ab_name(names(out)[i], tolower = TRUE, language = NULL),
|
||||
"), although it was matched for multiple antibiotics or columns."),
|
||||
add_fn = font_red,
|
||||
call = FALSE,
|
||||
@@ -228,18 +253,18 @@ get_column_abx <- function(x,
|
||||
|
||||
if (!is.null(hard_dependencies)) {
|
||||
hard_dependencies <- unique(hard_dependencies)
|
||||
if (!all(hard_dependencies %in% names(x))) {
|
||||
if (!all(hard_dependencies %in% names(out))) {
|
||||
# missing a hard dependency will return NA and consequently the data will not be analysed
|
||||
missing <- hard_dependencies[!hard_dependencies %in% names(x)]
|
||||
missing <- hard_dependencies[!hard_dependencies %in% names(out)]
|
||||
generate_warning_abs_missing(missing, any = FALSE)
|
||||
return(NA)
|
||||
}
|
||||
}
|
||||
if (!is.null(soft_dependencies)) {
|
||||
soft_dependencies <- unique(soft_dependencies)
|
||||
if (info == TRUE & !all(soft_dependencies %in% names(x))) {
|
||||
if (info == TRUE & !all(soft_dependencies %in% names(out))) {
|
||||
# missing a soft dependency may lower the reliability
|
||||
missing <- soft_dependencies[!soft_dependencies %in% names(x)]
|
||||
missing <- soft_dependencies[!soft_dependencies %in% names(out)]
|
||||
missing_msg <- vector_and(paste0(ab_name(missing, tolower = TRUE, language = NULL),
|
||||
" (", font_bold(missing, collapse = NULL), ")"),
|
||||
quotes = FALSE)
|
||||
@@ -249,8 +274,9 @@ get_column_abx <- function(x,
|
||||
}
|
||||
|
||||
pkg_env$get_column_abx.call <- unique_call_id(entire_session = FALSE)
|
||||
pkg_env$get_column_abx.out <- x
|
||||
x
|
||||
pkg_env$get_column_abx.checked_cols <- colnames(x.bak)
|
||||
pkg_env$get_column_abx.out <- out
|
||||
out
|
||||
}
|
||||
|
||||
generate_warning_abs_missing <- function(missing, any = FALSE) {
|
||||
|
||||
@@ -44,11 +44,11 @@
|
||||
#' cat(italicise_taxonomy("An overview of S. aureus isolates", type = "ansi"))
|
||||
#'
|
||||
#' # since ggplot2 supports no markdown (yet), use
|
||||
#' # italicise_taxonomy() and the `ggtext` pkg for titles:
|
||||
#' # italicise_taxonomy() and the `ggtext` package for titles:
|
||||
#' \donttest{
|
||||
#' if (require("ggplot2") && require("ggtext")) {
|
||||
#' ggplot(example_isolates$AMC,
|
||||
#' title = italicise_taxonomy("Amoxi/clav in E. coli")) +
|
||||
#' autoplot(example_isolates$AMC,
|
||||
#' title = italicise_taxonomy("Amoxi/clav in E. coli")) +
|
||||
#' theme(plot.title = ggtext::element_markdown())
|
||||
#' }
|
||||
#' }
|
||||
|
||||
@@ -36,7 +36,7 @@
|
||||
#' @param ... ignored, only in place to allow future extensions
|
||||
#' @details **Note:** As opposed to the `join()` functions of `dplyr`, [character] vectors are supported and at default existing columns will get a suffix `"2"` and the newly joined columns will not get a suffix.
|
||||
#'
|
||||
#' If the `dplyr` package is installed, their join functions will be used. Otherwise, the much slower [merge()] and [interaction()] functions from base R will be used.
|
||||
#' If the `dplyr` package is installed, their join functions will be used. Otherwise, the much slower [merge()] and [interaction()] functions from base \R will be used.
|
||||
#' @inheritSection AMR Read more on Our Website!
|
||||
#' @return a [data.frame]
|
||||
#' @export
|
||||
|
||||
@@ -177,7 +177,6 @@ key_antimicrobials <- function(x = NULL,
|
||||
paste0("Only using ", values_new_length, " out of ", values_old_length, " defined columns ")),
|
||||
"as key antimicrobials for ", name, "s. See ?key_antimicrobials.",
|
||||
call = FALSE)
|
||||
remember_thrown_message(paste0("key_antimicrobials.", name))
|
||||
}
|
||||
|
||||
generate_antimcrobials_string(x[which(filter), c(universal, values), drop = FALSE])
|
||||
|
||||
@@ -187,12 +187,8 @@ mdro <- function(x = NULL,
|
||||
check_dataset_integrity()
|
||||
|
||||
info.bak <- info
|
||||
if (message_not_thrown_before("mdro")) {
|
||||
remember_thrown_message("mdro")
|
||||
} else {
|
||||
# don't thrown info's more than once per call
|
||||
info <- FALSE
|
||||
}
|
||||
# don't thrown info's more than once per call
|
||||
info <- message_not_thrown_before("mdro")
|
||||
|
||||
if (interactive() & verbose == TRUE & info == TRUE) {
|
||||
txt <- paste0("WARNING: In Verbose mode, the mdro() function does not return the MDRO results, but instead returns a data set in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.",
|
||||
@@ -1416,7 +1412,6 @@ mdro <- function(x = NULL,
|
||||
if (message_not_thrown_before("mdro.availability")) {
|
||||
warning_("NA introduced for isolates where the available percentage of antimicrobial classes was below ",
|
||||
percentage(pct_required_classes), " (set with `pct_required_classes`)", call = FALSE)
|
||||
remember_thrown_message("mdro.availability")
|
||||
}
|
||||
# set these -1s to NA
|
||||
x[which(x$MDRO == -1), "MDRO"] <- NA_integer_
|
||||
|
||||
@@ -320,6 +320,15 @@ unique.mic <- function(x, incomparables = FALSE, ...) {
|
||||
y
|
||||
}
|
||||
|
||||
#' @method rep mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
rep.mic <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
|
||||
#' @method sort mic
|
||||
#' @export
|
||||
#' @noRd
|
||||
@@ -337,7 +346,7 @@ sort.mic <- function(x, decreasing = FALSE, ...) {
|
||||
#' @export
|
||||
#' @noRd
|
||||
hist.mic <- function(x, ...) {
|
||||
warning_("Use `plot()` or `ggplot()` for optimal plotting of MIC values", call = FALSE)
|
||||
warning_("Use `plot()` or ggplot2's `autoplot()` for optimal plotting of MIC values", call = FALSE)
|
||||
hist(log2(x))
|
||||
}
|
||||
|
||||
|
||||
@@ -469,7 +469,7 @@ exec_as.mo <- function(x,
|
||||
x <- strip_whitespace(x, dyslexia_mode)
|
||||
# translate 'unknown' names back to English
|
||||
if (any(x %like% "unbekannt|onbekend|desconocid|sconosciut|iconnu|desconhecid", na.rm = TRUE)) {
|
||||
trns <- subset(translations_file, pattern %like% "unknown" | affect_mo_name == TRUE)
|
||||
trns <- subset(TRANSLATIONS, pattern %like% "unknown")
|
||||
langs <- LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED != "en"]
|
||||
for (l in langs) {
|
||||
for (i in seq_len(nrow(trns))) {
|
||||
@@ -1664,16 +1664,23 @@ pillar_shaft.mo <- function(x, ...) {
|
||||
out[is.na(x)] <- font_na(" NA")
|
||||
out[x == "UNKNOWN"] <- font_na(" UNKNOWN")
|
||||
|
||||
if (!all(x[!is.na(x)] %in% MO_lookup$mo)) {
|
||||
df <- tryCatch(get_current_data(arg_name = "x", call = 0),
|
||||
error = function(e) NULL)
|
||||
if (!is.null(df)) {
|
||||
mo_cols <- vapply(FUN.VALUE = logical(1), df, is.mo)
|
||||
} else {
|
||||
mo_cols <- NULL
|
||||
}
|
||||
|
||||
if (!all(x[!is.na(x)] %in% MO_lookup$mo) |
|
||||
(!is.null(df) && !all(unlist(df[, which(mo_cols), drop = FALSE]) %in% MO_lookup$mo))) {
|
||||
# markup old mo codes
|
||||
out[!x %in% MO_lookup$mo] <- font_italic(font_na(x[!x %in% MO_lookup$mo],
|
||||
collapse = NULL),
|
||||
collapse = NULL)
|
||||
# throw a warning with the affected column name
|
||||
mo <- tryCatch(search_type_in_df(get_current_data(arg_name = "x", call = 0), type = "mo", info = FALSE),
|
||||
error = function(e) NULL)
|
||||
if (!is.null(mo)) {
|
||||
col <- paste0("Column '", mo, "'")
|
||||
# throw a warning with the affected column name(s)
|
||||
if (!is.null(mo_cols)) {
|
||||
col <- paste0("Column ", vector_or(colnames(df)[mo_cols], quotes = TRUE, sort = FALSE))
|
||||
} else {
|
||||
col <- "The data"
|
||||
}
|
||||
@@ -2039,12 +2046,12 @@ parse_and_convert <- function(x) {
|
||||
x <- as.data.frame(x, stringsAsFactors = FALSE)[[1]]
|
||||
}
|
||||
}
|
||||
x[is.null(x)] <- NA
|
||||
parsed <- iconv(x, to = "UTF-8")
|
||||
parsed <- iconv(as.character(x), to = "UTF-8")
|
||||
parsed[is.na(parsed) & !is.na(x)] <- iconv(x[is.na(parsed) & !is.na(x)], from = "Latin1", to = "ASCII//TRANSLIT")
|
||||
parsed <- gsub('"', "", parsed, fixed = TRUE)
|
||||
parsed <- gsub(" +", " ", parsed, perl = TRUE)
|
||||
parsed <- trimws(parsed)
|
||||
parsed
|
||||
}, error = function(e) stop(e$message, call. = FALSE)) # this will also be thrown when running `as.mo(no_existing_object)`
|
||||
parsed
|
||||
}
|
||||
|
||||
+14
-13
@@ -52,7 +52,7 @@
|
||||
#'
|
||||
#' The function [mo_url()] will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.
|
||||
#'
|
||||
#' SNOMED codes - [mo_snomed()] - are from the `r SNOMED_VERSION$current_source`. See the [microorganisms] data set for more info.
|
||||
#' SNOMED codes - [mo_snomed()] - are from the `r SNOMED_VERSION$current_source`. See *Source* and the [microorganisms] data set for more info.
|
||||
#' @inheritSection mo_matching_score Matching Score for Microorganisms
|
||||
#' @inheritSection catalogue_of_life Catalogue of Life
|
||||
#' @inheritSection as.mo Source
|
||||
@@ -65,7 +65,7 @@
|
||||
#' - A [numeric] in case of [mo_snomed()]
|
||||
#' - A [character] in all other cases
|
||||
#' @export
|
||||
#' @seealso [microorganisms]
|
||||
#' @seealso Data set [microorganisms]
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @inheritSection AMR Read more on Our Website!
|
||||
#' @examples
|
||||
@@ -225,6 +225,8 @@ mo_shortname <- function(x, language = get_locale(), ...) {
|
||||
translate_AMR(shortnames, language = language, only_unknown = FALSE, only_affect_mo_names = TRUE)
|
||||
}
|
||||
|
||||
|
||||
|
||||
#' @rdname mo_property
|
||||
#' @export
|
||||
mo_subspecies <- function(x, language = get_locale(), ...) {
|
||||
@@ -479,7 +481,6 @@ mo_is_intrinsic_resistant <- function(x, ab, language = get_locale(), ...) {
|
||||
message_("Determining intrinsic resistance based on ",
|
||||
format_eucast_version_nr(3.2, markdown = FALSE), ". ",
|
||||
font_red("This note will be shown once per session."))
|
||||
remember_thrown_message("intrinsic_resistant_version", entire_session = TRUE)
|
||||
}
|
||||
|
||||
# runs against internal vector: INTRINSIC_R (see zzz.R)
|
||||
@@ -723,16 +724,17 @@ mo_validate <- function(x, property, language, ...) {
|
||||
|
||||
if (tryCatch(all(x[!is.na(x)] %in% MO_lookup$mo) & !has_Becker_or_Lancefield, error = function(e) FALSE)) {
|
||||
# special case for mo_* functions where class is already <mo>
|
||||
return(MO_lookup[match(x, MO_lookup$mo), property, drop = TRUE])
|
||||
}
|
||||
x <- MO_lookup[match(x, MO_lookup$mo), property, drop = TRUE]
|
||||
|
||||
# try to catch an error when inputting an invalid argument
|
||||
# so the 'call.' can be set to FALSE
|
||||
tryCatch(x[1L] %in% MO_lookup[1, property, drop = TRUE],
|
||||
error = function(e) stop(e$message, call. = FALSE))
|
||||
} else {
|
||||
# try to catch an error when inputting an invalid argument
|
||||
# so the 'call.' can be set to FALSE
|
||||
tryCatch(x[1L] %in% MO_lookup[1, property, drop = TRUE],
|
||||
error = function(e) stop(e$message, call. = FALSE))
|
||||
|
||||
if (!all(x[!is.na(x)] %in% MO_lookup[, property, drop = TRUE]) | has_Becker_or_Lancefield) {
|
||||
x <- exec_as.mo(x, property = property, language = language, ...)
|
||||
if (!all(x[!is.na(x)] %in% MO_lookup[, property, drop = TRUE]) | has_Becker_or_Lancefield) {
|
||||
x <- exec_as.mo(x, property = property, language = language, ...)
|
||||
}
|
||||
}
|
||||
|
||||
if (property == "mo") {
|
||||
@@ -754,8 +756,7 @@ find_mo_col <- function(fn) {
|
||||
}, silent = TRUE)
|
||||
if (!is.null(df) && !is.null(mo) && is.data.frame(df)) {
|
||||
if (message_not_thrown_before(fn = fn)) {
|
||||
message_("Using column '", font_bold(mo), "' as input for ", fn, "()")
|
||||
remember_thrown_message(fn = fn)
|
||||
message_("Using column '", font_bold(mo), "' as input for `", fn, "()`")
|
||||
}
|
||||
return(df[, mo, drop = TRUE])
|
||||
} else {
|
||||
|
||||
@@ -25,16 +25,15 @@
|
||||
|
||||
#' Plotting for Classes `rsi`, `mic` and `disk`
|
||||
#'
|
||||
#' Functions to plot classes `rsi`, `mic` and `disk`, with support for base R and `ggplot2`.
|
||||
#' @inheritSection lifecycle Stable Lifecycle
|
||||
#' Functions to plot classes `rsi`, `mic` and `disk`, with support for base \R and `ggplot2`.
|
||||
#' @inheritSection lifecycle Maturing Lifecycle
|
||||
#' @inheritSection AMR Read more on Our Website!
|
||||
#' @param x,data MIC values created with [as.mic()] or disk diffusion values created with [as.disk()]
|
||||
#' @param mapping aesthetic mappings to use for [`ggplot()`][ggplot2::ggplot()]
|
||||
#' @param main,title title of the plot
|
||||
#' @param xlab,ylab axis title
|
||||
#' @param x,object values created with [as.mic()], [as.disk()] or [as.rsi()]
|
||||
#' @param mo any (vector of) text that can be coerced to a valid microorganism code with [as.mo()]
|
||||
#' @param ab any (vector of) text that can be coerced to a valid antimicrobial code with [as.ab()]
|
||||
#' @param guideline interpretation guideline to use, defaults to the latest included EUCAST guideline, see *Details*
|
||||
#' @param main,title title of the plot
|
||||
#' @param xlab,ylab axis title
|
||||
#' @param colours_RSI colours to use for filling in the bars, must be a vector of three values (in the order R, S and I). The default colours are colour-blind friendly.
|
||||
#' @param language language to be used to translate 'Susceptible', 'Increased exposure'/'Intermediate' and 'Resistant', defaults to system language (see [get_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Use `language = NULL` or `language = ""` to prevent translation.
|
||||
#' @param expand a [logical] to indicate whether the range on the x axis should be expanded between the lowest and highest value. For MIC values, intermediate values will be factors of 2 starting from the highest MIC value. For disk diameters, the whole diameter range will be filled.
|
||||
@@ -46,7 +45,7 @@
|
||||
#' Simply using `"CLSI"` or `"EUCAST"` as input will automatically select the latest version of that guideline.
|
||||
#' @name plot
|
||||
#' @rdname plot
|
||||
#' @return The `ggplot` functions return a [`ggplot`][ggplot2::ggplot()] model that is extendible with any `ggplot2` function.
|
||||
#' @return The `autoplot()` functions return a [`ggplot`][ggplot2::ggplot()] model that is extendible with any `ggplot2` function.
|
||||
#' @param ... arguments passed on to [as.rsi()]
|
||||
#' @examples
|
||||
#' some_mic_values <- random_mic(size = 100)
|
||||
@@ -63,9 +62,9 @@
|
||||
#'
|
||||
#' \donttest{
|
||||
#' if (require("ggplot2")) {
|
||||
#' ggplot(some_mic_values)
|
||||
#' ggplot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
|
||||
#' ggplot(some_rsi_values)
|
||||
#' autoplot(some_mic_values)
|
||||
#' autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
|
||||
#' autoplot(some_rsi_values)
|
||||
#' }
|
||||
#' }
|
||||
NULL
|
||||
@@ -75,22 +74,22 @@ NULL
|
||||
#' @export
|
||||
#' @rdname plot
|
||||
plot.mic <- function(x,
|
||||
main = paste("MIC values of", deparse(substitute(x))),
|
||||
ylab = "Frequency",
|
||||
xlab = "Minimum Inhibitory Concentration (mg/L)",
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
guideline = "EUCAST",
|
||||
main = paste("MIC values of", deparse(substitute(x))),
|
||||
ylab = "Frequency",
|
||||
xlab = "Minimum Inhibitory Concentration (mg/L)",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(guideline, allow_class = "character", has_length = 1)
|
||||
meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(expand, allow_class = "logical", has_length = 1)
|
||||
@@ -161,12 +160,12 @@ plot.mic <- function(x,
|
||||
#' @export
|
||||
#' @noRd
|
||||
barplot.mic <- function(height,
|
||||
main = paste("MIC values of", deparse(substitute(height))),
|
||||
ylab = "Frequency",
|
||||
xlab = "Minimum Inhibitory Concentration (mg/L)",
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
guideline = "EUCAST",
|
||||
main = paste("MIC values of", deparse(substitute(height))),
|
||||
ylab = "Frequency",
|
||||
xlab = "Minimum Inhibitory Concentration (mg/L)",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_locale(),
|
||||
expand = TRUE,
|
||||
@@ -202,28 +201,27 @@ barplot.mic <- function(height,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @method ggplot mic
|
||||
#' @method autoplot mic
|
||||
#' @rdname plot
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
ggplot.mic <- function(data,
|
||||
mapping = NULL,
|
||||
title = paste("MIC values of", deparse(substitute(data))),
|
||||
ylab = "Frequency",
|
||||
xlab = "Minimum Inhibitory Concentration (mg/L)",
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
guideline = "EUCAST",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
autoplot.mic <- function(object,
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
guideline = "EUCAST",
|
||||
title = paste("MIC values of", deparse(substitute(object))),
|
||||
ylab = "Frequency",
|
||||
xlab = "Minimum Inhibitory Concentration (mg/L)",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
|
||||
meet_criteria(guideline, allow_class = "character", has_length = 1)
|
||||
meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(xlab, allow_class = "character", has_length = 1)
|
||||
meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
|
||||
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(expand, allow_class = "logical", has_length = 1)
|
||||
@@ -243,7 +241,7 @@ ggplot.mic <- function(data,
|
||||
title <- gsub(" +", " ", paste0(title, collapse = " "))
|
||||
}
|
||||
|
||||
x <- plot_prepare_table(data, expand = expand)
|
||||
x <- plot_prepare_table(object, expand = expand)
|
||||
cols_sub <- plot_colours_subtitle_guideline(x = x,
|
||||
mo = mo,
|
||||
ab = ab,
|
||||
@@ -262,22 +260,20 @@ ggplot.mic <- function(data,
|
||||
levels = translate_AMR(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
|
||||
language = language),
|
||||
ordered = TRUE)
|
||||
if (!is.null(mapping)) {
|
||||
p <- ggplot2::ggplot(df, mapping = mapping)
|
||||
} else {
|
||||
p <- ggplot2::ggplot(df)
|
||||
}
|
||||
p <- ggplot2::ggplot(df)
|
||||
|
||||
if (any(colours_RSI %in% cols_sub$cols)) {
|
||||
vals <- c("Resistant" = colours_RSI[1],
|
||||
"Susceptible" = colours_RSI[2],
|
||||
"Incr. exposure" = colours_RSI[3],
|
||||
"Susceptible, incr. exp." = colours_RSI[3],
|
||||
"Intermediate" = colours_RSI[3])
|
||||
names(vals) <- translate_AMR(names(vals), language = language)
|
||||
p <- p +
|
||||
ggplot2::geom_col(ggplot2::aes(x = mic, y = count, fill = cols)) +
|
||||
# limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
|
||||
ggplot2::scale_fill_manual(values = vals,
|
||||
name = NULL)
|
||||
name = NULL,
|
||||
limits = force)
|
||||
} else {
|
||||
p <- p +
|
||||
ggplot2::geom_col(ggplot2::aes(x = mic, y = count))
|
||||
@@ -287,6 +283,7 @@ ggplot.mic <- function(data,
|
||||
ggplot2::labs(title = title, x = xlab, y = ylab, subtitle = cols_sub$sub)
|
||||
}
|
||||
|
||||
|
||||
#' @method plot disk
|
||||
#' @export
|
||||
#' @importFrom graphics barplot axis mtext legend
|
||||
@@ -420,21 +417,20 @@ barplot.disk <- function(height,
|
||||
...)
|
||||
}
|
||||
|
||||
#' @method ggplot disk
|
||||
#' @method autoplot disk
|
||||
#' @rdname plot
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
ggplot.disk <- function(data,
|
||||
mapping = NULL,
|
||||
title = paste("Disk zones of", deparse(substitute(data))),
|
||||
ylab = "Frequency",
|
||||
xlab = "Disk diffusion diameter (mm)",
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
guideline = "EUCAST",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
autoplot.disk <- function(object,
|
||||
mo = NULL,
|
||||
ab = NULL,
|
||||
title = paste("Disk zones of", deparse(substitute(object))),
|
||||
ylab = "Frequency",
|
||||
xlab = "Disk diffusion diameter (mm)",
|
||||
guideline = "EUCAST",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_locale(),
|
||||
expand = TRUE,
|
||||
...) {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
@@ -461,7 +457,7 @@ ggplot.disk <- function(data,
|
||||
title <- gsub(" +", " ", paste0(title, collapse = " "))
|
||||
}
|
||||
|
||||
x <- plot_prepare_table(data, expand = expand)
|
||||
x <- plot_prepare_table(object, expand = expand)
|
||||
cols_sub <- plot_colours_subtitle_guideline(x = x,
|
||||
mo = mo,
|
||||
ab = ab,
|
||||
@@ -481,22 +477,20 @@ ggplot.disk <- function(data,
|
||||
levels = translate_AMR(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
|
||||
language = language),
|
||||
ordered = TRUE)
|
||||
if (!is.null(mapping)) {
|
||||
p <- ggplot2::ggplot(df, mapping = mapping)
|
||||
} else {
|
||||
p <- ggplot2::ggplot(df)
|
||||
}
|
||||
p <- ggplot2::ggplot(df)
|
||||
|
||||
if (any(colours_RSI %in% cols_sub$cols)) {
|
||||
vals <- c("Resistant" = colours_RSI[1],
|
||||
"Susceptible" = colours_RSI[2],
|
||||
"Incr. exposure" = colours_RSI[3],
|
||||
"Susceptible, incr. exp." = colours_RSI[3],
|
||||
"Intermediate" = colours_RSI[3])
|
||||
names(vals) <- translate_AMR(names(vals), language = language)
|
||||
p <- p +
|
||||
ggplot2::geom_col(ggplot2::aes(x = disk, y = count, fill = cols)) +
|
||||
# limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
|
||||
ggplot2::scale_fill_manual(values = vals,
|
||||
name = NULL)
|
||||
name = NULL,
|
||||
limits = force)
|
||||
} else {
|
||||
p <- p +
|
||||
ggplot2::geom_col(ggplot2::aes(x = disk, y = count))
|
||||
@@ -604,17 +598,16 @@ barplot.rsi <- function(height,
|
||||
axis(2, seq(0, max(x)))
|
||||
}
|
||||
|
||||
#' @method ggplot rsi
|
||||
#' @method autoplot rsi
|
||||
#' @rdname plot
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
ggplot.rsi <- function(data,
|
||||
mapping = NULL,
|
||||
title = paste("Resistance Overview of", deparse(substitute(data))),
|
||||
xlab = "Antimicrobial Interpretation",
|
||||
ylab = "Frequency",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_locale(),
|
||||
...) {
|
||||
autoplot.rsi <- function(object,
|
||||
title = paste("Resistance Overview of", deparse(substitute(object))),
|
||||
xlab = "Antimicrobial Interpretation",
|
||||
ylab = "Frequency",
|
||||
colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
|
||||
language = get_locale(),
|
||||
...) {
|
||||
stop_ifnot_installed("ggplot2")
|
||||
meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
|
||||
meet_criteria(ylab, allow_class = "character", has_length = 1)
|
||||
@@ -640,19 +633,15 @@ ggplot.rsi <- function(data,
|
||||
colours_RSI <- rep(colours_RSI, 3)
|
||||
}
|
||||
|
||||
df <- as.data.frame(table(data), stringsAsFactors = TRUE)
|
||||
df <- as.data.frame(table(object), stringsAsFactors = TRUE)
|
||||
colnames(df) <- c("rsi", "count")
|
||||
if (!is.null(mapping)) {
|
||||
p <- ggplot2::ggplot(df, mapping = mapping)
|
||||
} else {
|
||||
p <- ggplot2::ggplot(df)
|
||||
}
|
||||
|
||||
p +
|
||||
ggplot2::ggplot(df) +
|
||||
ggplot2::geom_col(ggplot2::aes(x = rsi, y = count, fill = rsi)) +
|
||||
# limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
|
||||
ggplot2::scale_fill_manual(values = c("R" = colours_RSI[1],
|
||||
"S" = colours_RSI[2],
|
||||
"I" = colours_RSI[3])) +
|
||||
"I" = colours_RSI[3]),
|
||||
limits = force) +
|
||||
ggplot2::labs(title = title, x = xlab, y = ylab) +
|
||||
ggplot2::theme(legend.position = "none")
|
||||
}
|
||||
@@ -663,6 +652,7 @@ plot_prepare_table <- function(x, expand) {
|
||||
if (is.mic(x)) {
|
||||
if (expand == TRUE) {
|
||||
# expand range for MIC by adding factors of 2 from lowest to highest so all MICs in between also print
|
||||
valid_lvls <- levels(x)
|
||||
extra_range <- max(x) / 2
|
||||
while (min(extra_range) / 2 > min(x)) {
|
||||
extra_range <- c(min(extra_range) / 2, extra_range)
|
||||
@@ -671,7 +661,7 @@ plot_prepare_table <- function(x, expand) {
|
||||
extra_range <- rep(0, length(extra_range))
|
||||
names(extra_range) <- nms
|
||||
x <- table(droplevels(x, as.mic = FALSE))
|
||||
extra_range <- extra_range[!names(extra_range) %in% names(x)]
|
||||
extra_range <- extra_range[!names(extra_range) %in% names(x) & names(extra_range) %in% valid_lvls]
|
||||
x <- as.table(c(x, extra_range))
|
||||
} else {
|
||||
x <- table(droplevels(x, as.mic = FALSE))
|
||||
@@ -696,7 +686,7 @@ plot_prepare_table <- function(x, expand) {
|
||||
plot_name_of_I <- function(guideline) {
|
||||
if (guideline %unlike% "CLSI" && as.double(gsub("[^0-9]+", "", guideline)) >= 2019) {
|
||||
# interpretation since 2019
|
||||
"Incr. exposure"
|
||||
"Susceptible, incr. exp."
|
||||
} else {
|
||||
# interpretation until 2019
|
||||
"Intermediate"
|
||||
|
||||
+67
-51
@@ -167,12 +167,14 @@ resistance <- 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)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
@@ -181,12 +183,14 @@ susceptibility <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
@@ -195,12 +199,14 @@ proportion_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)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "R",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
@@ -209,12 +215,14 @@ proportion_IR <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = c("I", "R"),
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("I", "R"),
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
@@ -223,12 +231,14 @@ proportion_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)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "I",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
@@ -237,12 +247,14 @@ proportion_SI <- function(...,
|
||||
minimum = 30,
|
||||
as_percent = FALSE,
|
||||
only_all_tested = FALSE) {
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = c("S", "I"),
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
@@ -251,12 +263,14 @@ proportion_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)
|
||||
tryCatch(
|
||||
rsi_calc(...,
|
||||
ab_result = "S",
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
only_all_tested = only_all_tested,
|
||||
only_count = FALSE),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
#' @rdname proportion
|
||||
@@ -268,13 +282,15 @@ proportion_df <- function(data,
|
||||
as_percent = FALSE,
|
||||
combine_SI = TRUE,
|
||||
combine_IR = FALSE) {
|
||||
rsi_calc_df(type = "proportion",
|
||||
data = data,
|
||||
translate_ab = translate_ab,
|
||||
language = language,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR,
|
||||
combine_SI_missing = missing(combine_SI))
|
||||
tryCatch(
|
||||
rsi_calc_df(type = "proportion",
|
||||
data = data,
|
||||
translate_ab = translate_ab,
|
||||
language = language,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent,
|
||||
combine_SI = combine_SI,
|
||||
combine_IR = combine_IR,
|
||||
combine_SI_missing = missing(combine_SI)),
|
||||
error = function(e) stop_(e$message, call = -5))
|
||||
}
|
||||
|
||||
+35
-19
@@ -27,12 +27,12 @@
|
||||
#'
|
||||
#' These functions can be used for generating random MIC values and disk diffusion diameters, for AMR data analysis practice. By providing a microorganism and antimicrobial agent, the generated results will reflect reality as much as possible.
|
||||
#' @inheritSection lifecycle Stable Lifecycle
|
||||
#' @param size desired size of the returned vector
|
||||
#' @param size desired size of the returned vector. If used in a [data.frame] call or `dplyr` verb, will get the current (group) size if left blank.
|
||||
#' @param mo any [character] that can be coerced to a valid microorganism code with [as.mo()]
|
||||
#' @param ab any [character] that can be coerced to a valid antimicrobial agent code with [as.ab()]
|
||||
#' @param prob_RSI a vector of length 3: the probabilities for R (1st value), S (2nd value) and I (3rd value)
|
||||
#' @param ... ignored, only in place to allow future extensions
|
||||
#' @details The base R function [sample()] is used for generating values.
|
||||
#' @details The base \R function [sample()] is used for generating values.
|
||||
#'
|
||||
#' Generated values are based on the latest EUCAST guideline implemented in the [rsi_translation] data set. To create specific generated values per bug or drug, set the `mo` and/or `ab` argument.
|
||||
#' @return class `<mic>` for [random_mic()] (see [as.mic()]) and class `<disk>` for [random_disk()] (see [as.disk()])
|
||||
@@ -55,19 +55,36 @@
|
||||
#' random_disk(100, "Klebsiella pneumoniae", "ampicillin") # range 11-17
|
||||
#' random_disk(100, "Streptococcus pneumoniae", "ampicillin") # range 12-27
|
||||
#' }
|
||||
random_mic <- function(size, mo = NULL, ab = NULL, ...) {
|
||||
random_mic <- function(size = NULL, mo = NULL, ab = NULL, ...) {
|
||||
meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE, allow_NULL = TRUE)
|
||||
meet_criteria(mo, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
if (is.null(size)) {
|
||||
size <- NROW(get_current_data(arg_name = "size", call = -3))
|
||||
}
|
||||
random_exec("MIC", size = size, mo = mo, ab = ab)
|
||||
}
|
||||
|
||||
#' @rdname random
|
||||
#' @export
|
||||
random_disk <- function(size, mo = NULL, ab = NULL, ...) {
|
||||
random_disk <- function(size = NULL, mo = NULL, ab = NULL, ...) {
|
||||
meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE, allow_NULL = TRUE)
|
||||
meet_criteria(mo, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
if (is.null(size)) {
|
||||
size <- NROW(get_current_data(arg_name = "size", call = -3))
|
||||
}
|
||||
random_exec("DISK", size = size, mo = mo, ab = ab)
|
||||
}
|
||||
|
||||
#' @rdname random
|
||||
#' @export
|
||||
random_rsi <- function(size, prob_RSI = c(0.33, 0.33, 0.33), ...) {
|
||||
random_rsi <- function(size = NULL, prob_RSI = c(0.33, 0.33, 0.33), ...) {
|
||||
meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE, allow_NULL = TRUE)
|
||||
meet_criteria(prob_RSI, allow_class = c("numeric", "integer"), has_length = 3)
|
||||
if (is.null(size)) {
|
||||
size <- NROW(get_current_data(arg_name = "size", call = -3))
|
||||
}
|
||||
sample(as.rsi(c("R", "S", "I")), size = size, replace = TRUE, prob = prob_RSI)
|
||||
}
|
||||
|
||||
@@ -105,21 +122,20 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) {
|
||||
}
|
||||
|
||||
if (type == "MIC") {
|
||||
# all valid MIC levels
|
||||
valid_range <- as.mic(levels(as.mic(1)))
|
||||
set_range_max <- max(df$breakpoint_R)
|
||||
if (log(set_range_max, 2) %% 1 == 0) {
|
||||
# return powers of 2
|
||||
valid_range <- unique(as.double(valid_range))
|
||||
# add 1-3 higher MIC levels to set_range_max
|
||||
set_range_max <- 2 ^ (log(set_range_max, 2) + sample(c(1:3), 1))
|
||||
set_range <- as.mic(valid_range[log(valid_range, 2) %% 1 == 0 & valid_range <= set_range_max])
|
||||
} else {
|
||||
# no power of 2, return factors of 2 to left and right side
|
||||
valid_mics <- suppressWarnings(as.mic(set_range_max / (2 ^ c(-3:3))))
|
||||
set_range <- valid_mics[!is.na(valid_mics)]
|
||||
# set range
|
||||
mic_range <- c(0.001, 0.002, 0.005, 0.010, 0.025, 0.0625, 0.125, 0.250, 0.5, 1, 2, 4, 8, 16, 32, 64, 128, 256)
|
||||
|
||||
# get highest/lowest +/- random 1 to 3 higher factors of two
|
||||
max_range <- mic_range[min(length(mic_range),
|
||||
which(mic_range == max(df$breakpoint_R)) + sample(c(1:3), 1))]
|
||||
min_range <- mic_range[max(1,
|
||||
which(mic_range == min(df$breakpoint_S)) - sample(c(1:3), 1))]
|
||||
|
||||
mic_range_new <- mic_range[mic_range <= max_range & mic_range >= min_range]
|
||||
if (length(mic_range_new) == 0) {
|
||||
mic_range_new <- mic_range
|
||||
}
|
||||
out <- as.mic(sample(set_range, size = size, replace = TRUE))
|
||||
out <- as.mic(sample(mic_range_new, size = size, replace = TRUE))
|
||||
# 50% chance that lowest will get <= and highest will get >=
|
||||
if (stats::runif(1) > 0.5) {
|
||||
out[out == min(out)] <- paste0("<=", out[out == min(out)])
|
||||
|
||||
+24
-17
@@ -23,10 +23,11 @@
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Predict antimicrobial resistance
|
||||
#' Predict Antimicrobial Resistance
|
||||
#'
|
||||
#' Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns `se_min` and `se_max`. See *Examples* for a real live example.
|
||||
#' @inheritSection lifecycle Stable Lifecycle
|
||||
#' @param object model data to be plotted
|
||||
#' @param col_ab column name of `x` containing antimicrobial interpretations (`"R"`, `"I"` and `"S"`)
|
||||
#' @param col_date column name of the date, will be used to calculate years if this column doesn't consist of years already, defaults to the first column of with a date class
|
||||
#' @param year_min lowest year to use in the prediction model, dafaults to the lowest year in `col_date`
|
||||
@@ -99,9 +100,9 @@
|
||||
#' info = FALSE,
|
||||
#' minimum = 15)
|
||||
#'
|
||||
#' ggplot(data)
|
||||
#' autoplot(data)
|
||||
#'
|
||||
#' ggplot(as.data.frame(data),
|
||||
#' ggplot(data,
|
||||
#' aes(x = year)) +
|
||||
#' geom_col(aes(y = value),
|
||||
#' fill = "grey75") +
|
||||
@@ -351,20 +352,6 @@ plot.resistance_predict <- function(x, main = paste("Resistance Prediction of",
|
||||
col = "grey40")
|
||||
}
|
||||
|
||||
|
||||
#' @method ggplot resistance_predict
|
||||
#' @rdname resistance_predict
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
ggplot.resistance_predict <- function(x,
|
||||
main = paste("Resistance Prediction of", x_name),
|
||||
ribbon = TRUE,
|
||||
...) {
|
||||
x_name <- paste0(ab_name(attributes(x)$ab), " (", attributes(x)$ab, ")")
|
||||
meet_criteria(main, allow_class = "character", has_length = 1)
|
||||
meet_criteria(ribbon, allow_class = "logical", has_length = 1)
|
||||
ggplot_rsi_predict(x = x, main = main, ribbon = ribbon, ...)
|
||||
}
|
||||
|
||||
#' @rdname resistance_predict
|
||||
#' @export
|
||||
ggplot_rsi_predict <- function(x,
|
||||
@@ -407,3 +394,23 @@ ggplot_rsi_predict <- function(x,
|
||||
colour = "grey40")
|
||||
p
|
||||
}
|
||||
|
||||
#' @method autoplot resistance_predict
|
||||
#' @rdname resistance_predict
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
autoplot.resistance_predict <- function(object,
|
||||
main = paste("Resistance Prediction of", x_name),
|
||||
ribbon = TRUE,
|
||||
...) {
|
||||
x_name <- paste0(ab_name(attributes(object)$ab), " (", attributes(object)$ab, ")")
|
||||
meet_criteria(main, allow_class = "character", has_length = 1)
|
||||
meet_criteria(ribbon, allow_class = "logical", has_length = 1)
|
||||
ggplot_rsi_predict(x = object, main = main, ribbon = ribbon, ...)
|
||||
}
|
||||
|
||||
#' @method fortify resistance_predict
|
||||
#' @noRd
|
||||
# will be exported using s3_register() in R/zzz.R
|
||||
fortify.resistance_predict <- function(model, data, ...) {
|
||||
as.data.frame(model)
|
||||
}
|
||||
|
||||
@@ -284,10 +284,25 @@ as.rsi.default <- function(x, ...) {
|
||||
}
|
||||
}
|
||||
|
||||
x <- as.character(unlist(x))
|
||||
# trim leading and trailing spaces, new lines, etc.
|
||||
x <- trimws2(as.character(unlist(x)))
|
||||
x.bak <- x
|
||||
|
||||
na_before <- length(x[is.na(x) | x == ""])
|
||||
|
||||
# correct for translations
|
||||
trans_R <- unlist(TRANSLATIONS[which(TRANSLATIONS$pattern == "Resistant"),
|
||||
LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED %in% colnames(TRANSLATIONS)]])
|
||||
trans_S <- unlist(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible"),
|
||||
LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED %in% colnames(TRANSLATIONS)]])
|
||||
trans_I <- unlist(TRANSLATIONS[which(TRANSLATIONS$pattern %in% c("Incr. exposure", "Susceptible, incr. exp.", "Intermediate")),
|
||||
LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED %in% colnames(TRANSLATIONS)]])
|
||||
x <- gsub(paste0(unique(trans_R[!is.na(trans_R)]), collapse = "|"), "R", x, ignore.case = TRUE)
|
||||
x <- gsub(paste0(unique(trans_S[!is.na(trans_S)]), collapse = "|"), "S", x, ignore.case = TRUE)
|
||||
x <- gsub(paste0(unique(trans_I[!is.na(trans_I)]), collapse = "|"), "I", x, ignore.case = TRUE)
|
||||
# replace all English textual input
|
||||
x[x %like% "([^a-z]|^)res(is(tant)?)?"] <- "R"
|
||||
x[x %like% "([^a-z]|^)sus(cep(tible)?)?"] <- "S"
|
||||
x[x %like% "([^a-z]|^)int(er(mediate)?)?|incr.*exp"] <- "I"
|
||||
# remove all spaces
|
||||
x <- gsub(" +", "", x)
|
||||
# remove all MIC-like values: numbers, operators and periods
|
||||
@@ -349,7 +364,7 @@ as.rsi.mic <- function(x,
|
||||
|
||||
# for dplyr's across()
|
||||
cur_column_dplyr <- import_fn("cur_column", "dplyr", error_on_fail = FALSE)
|
||||
if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", 0)), error = function(e) FALSE)) {
|
||||
if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", call = 0)), error = function(e) FALSE)) {
|
||||
# try to get current column, which will only be available when in across()
|
||||
ab <- tryCatch(cur_column_dplyr(),
|
||||
error = function(e) ab)
|
||||
@@ -395,13 +410,18 @@ as.rsi.mic <- function(x,
|
||||
uti <- rep(uti, length(x))
|
||||
}
|
||||
|
||||
message_("=> Interpreting MIC values of ", ifelse(isTRUE(list(...)$is_data.frame), "column ", ""), "'", font_bold(ab), "' (",
|
||||
ifelse(ab_coerced != ab, paste0(ab_coerced, ", "), ""),
|
||||
ab_name(ab_coerced, tolower = TRUE), ")", mo_var_found,
|
||||
agent_formatted <- paste0("'", font_bold(ab), "'")
|
||||
agent_name <- ab_name(ab_coerced, tolower = TRUE, language = NULL)
|
||||
if (generalise_antibiotic_name(ab) != generalise_antibiotic_name(agent_name)) {
|
||||
agent_formatted <- paste0(agent_formatted, " (", ab_coerced, ", ", agent_name, ")")
|
||||
}
|
||||
message_("=> Interpreting MIC values of ", ifelse(isTRUE(list(...)$is_data.frame), "column ", ""),
|
||||
agent_formatted,
|
||||
mo_var_found,
|
||||
" according to ", ifelse(identical(reference_data, AMR::rsi_translation),
|
||||
font_bold(guideline_coerced),
|
||||
"manually defined 'reference_data'"),
|
||||
" ... ",
|
||||
"... ",
|
||||
appendLF = FALSE,
|
||||
as_note = FALSE)
|
||||
|
||||
@@ -438,7 +458,7 @@ as.rsi.disk <- function(x,
|
||||
|
||||
# for dplyr's across()
|
||||
cur_column_dplyr <- import_fn("cur_column", "dplyr", error_on_fail = FALSE)
|
||||
if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", 0)), error = function(e) FALSE)) {
|
||||
if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", call = 0)), error = function(e) FALSE)) {
|
||||
# try to get current column, which will only be available when in across()
|
||||
ab <- tryCatch(cur_column_dplyr(),
|
||||
error = function(e) ab)
|
||||
@@ -484,13 +504,18 @@ as.rsi.disk <- function(x,
|
||||
uti <- rep(uti, length(x))
|
||||
}
|
||||
|
||||
message_("=> Interpreting disk zones of ", ifelse(isTRUE(list(...)$is_data.frame), "column ", ""), "'", font_bold(ab), "' (",
|
||||
ifelse(ab_coerced != ab, paste0(ab_coerced, ", "), ""),
|
||||
ab_name(ab_coerced, tolower = TRUE), ")", mo_var_found,
|
||||
agent_formatted <- paste0("'", font_bold(ab), "'")
|
||||
agent_name <- ab_name(ab_coerced, tolower = TRUE, language = NULL)
|
||||
if (generalise_antibiotic_name(ab) != generalise_antibiotic_name(agent_name)) {
|
||||
agent_formatted <- paste0(agent_formatted, " (", ab_coerced, ", ", agent_name, ")")
|
||||
}
|
||||
message_("=> Interpreting disk zones of ", ifelse(isTRUE(list(...)$is_data.frame), "column ", ""),
|
||||
agent_formatted,
|
||||
mo_var_found,
|
||||
" according to ", ifelse(identical(reference_data, AMR::rsi_translation),
|
||||
font_bold(guideline_coerced),
|
||||
"manually defined 'reference_data'"),
|
||||
" ... ",
|
||||
"... ",
|
||||
appendLF = FALSE,
|
||||
as_note = FALSE)
|
||||
|
||||
@@ -750,7 +775,6 @@ exec_as.rsi <- function(method,
|
||||
if (guideline_coerced != guideline) {
|
||||
if (message_not_thrown_before("as.rsi")) {
|
||||
message_("Using guideline ", font_bold(guideline_coerced), " as input for `guideline`.")
|
||||
remember_thrown_message("as.rsi")
|
||||
}
|
||||
}
|
||||
|
||||
@@ -789,7 +813,6 @@ exec_as.rsi <- function(method,
|
||||
if (guideline_coerced %unlike% "EUCAST") {
|
||||
if (message_not_thrown_before("as.rsi2")) {
|
||||
warning_("Using 'add_intrinsic_resistance' is only useful when using EUCAST guidelines, since the rules for intrinsic resistance are based on EUCAST.", call = FALSE)
|
||||
remember_thrown_message("as.rsi2")
|
||||
}
|
||||
} else {
|
||||
new_rsi[i] <- "R"
|
||||
@@ -854,7 +877,6 @@ exec_as.rsi <- function(method,
|
||||
message_("WARNING.", add_fn = list(font_yellow, font_bold), as_note = FALSE)
|
||||
if (message_not_thrown_before("as.rsi3")) {
|
||||
warning_("Found intrinsic resistance in some bug/drug combinations, although it was not applied.\nUse `as.rsi(..., add_intrinsic_resistance = TRUE)` to apply it.", call = FALSE)
|
||||
remember_thrown_message("as.rsi3")
|
||||
}
|
||||
warned <- TRUE
|
||||
}
|
||||
@@ -1038,6 +1060,15 @@ unique.rsi <- function(x, incomparables = FALSE, ...) {
|
||||
y
|
||||
}
|
||||
|
||||
#' @method rep rsi
|
||||
#' @export
|
||||
#' @noRd
|
||||
rep.rsi <- function(x, ...) {
|
||||
y <- NextMethod()
|
||||
attributes(y) <- attributes(x)
|
||||
y
|
||||
}
|
||||
|
||||
check_reference_data <- function(reference_data) {
|
||||
if (!identical(reference_data, AMR::rsi_translation)) {
|
||||
class_rsi <- vapply(FUN.VALUE = character(1), rsi_translation, function(x) paste0("<", class(x), ">", collapse = " and "))
|
||||
|
||||
+25
-4
@@ -27,7 +27,7 @@ dots2vars <- function(...) {
|
||||
# this function is to give more informative output about
|
||||
# variable names in count_* and proportion_* functions
|
||||
dots <- substitute(list(...))
|
||||
vector_and(as.character(dots)[2:length(dots)], quotes = FALSE)
|
||||
as.character(dots)[2:length(dots)]
|
||||
}
|
||||
|
||||
rsi_calc <- function(...,
|
||||
@@ -152,7 +152,6 @@ rsi_calc <- function(...,
|
||||
" your_data %>% mutate_if(is.rsi.eligible, as.rsi)\n",
|
||||
" your_data %>% mutate(across(where(is.rsi.eligible), as.rsi))",
|
||||
call = FALSE)
|
||||
remember_thrown_message("rsi_calc")
|
||||
}
|
||||
}
|
||||
|
||||
@@ -163,8 +162,30 @@ rsi_calc <- function(...,
|
||||
if (denominator < minimum) {
|
||||
if (data_vars != "") {
|
||||
data_vars <- paste(" for", data_vars)
|
||||
# also add group name if used in dplyr::group_by()
|
||||
cur_group <- import_fn("cur_group", "dplyr", error_on_fail = FALSE)
|
||||
if (!is.null(cur_group)) {
|
||||
group_df <- tryCatch(cur_group(), error = function(e) data.frame())
|
||||
if (NCOL(group_df) > 0) {
|
||||
# transform factors to characters
|
||||
group <- vapply(FUN.VALUE = character(1), group_df, function(x) {
|
||||
if (is.numeric(x)) {
|
||||
format(x)
|
||||
} else if (is.logical(x)) {
|
||||
as.character(x)
|
||||
} else {
|
||||
paste0('"', x, '"')
|
||||
}
|
||||
})
|
||||
data_vars <- paste0(data_vars, " in group: ", paste0(names(group), " = ", group, collapse = ", "))
|
||||
}
|
||||
}
|
||||
}
|
||||
warning_("Introducing NA: only ", denominator, " results available", data_vars, " (`minimum` = ", minimum, ").", call = FALSE)
|
||||
warning_("Introducing NA: ",
|
||||
ifelse(denominator == 0, "no", paste("only", denominator)),
|
||||
" results available",
|
||||
data_vars,
|
||||
" (`minimum` = ", minimum, ").", call = FALSE)
|
||||
fraction <- NA_real_
|
||||
} else {
|
||||
fraction <- numerator / denominator
|
||||
@@ -206,7 +227,7 @@ rsi_calc_df <- function(type, # "proportion", "count" or "both"
|
||||
translate_ab <- get_translate_ab(translate_ab)
|
||||
|
||||
# select only groups and antibiotics
|
||||
if (inherits(data, "grouped_df")) {
|
||||
if (is_null_or_grouped_tbl(data)) {
|
||||
data_has_groups <- TRUE
|
||||
groups <- setdiff(names(attributes(data)$groups), ".rows")
|
||||
data <- data[, c(groups, colnames(data)[vapply(FUN.VALUE = logical(1), data, is.rsi)]), drop = FALSE]
|
||||
|
||||
Binary file not shown.
+1
-1
@@ -136,7 +136,7 @@ translate_AMR <- function(from,
|
||||
return(from)
|
||||
}
|
||||
|
||||
df_trans <- translations_file # internal data file
|
||||
df_trans <- TRANSLATIONS # internal data file
|
||||
from.bak <- from
|
||||
from_unique <- unique(from)
|
||||
from_unique_translated <- from_unique
|
||||
|
||||
@@ -0,0 +1,74 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Data Analysis for R #
|
||||
# #
|
||||
# SOURCE #
|
||||
# https://github.com/msberends/AMR #
|
||||
# #
|
||||
# LICENCE #
|
||||
# (c) 2018-2021 Berends MS, Luz CF et al. #
|
||||
# Developed at the University of Groningen, the Netherlands, in #
|
||||
# collaboration with non-profit organisations Certe Medical #
|
||||
# Diagnostics & Advice, and University Medical Center Groningen. #
|
||||
# #
|
||||
# This R package is free software; you can freely use and distribute #
|
||||
# it for both personal and commercial purposes under the terms of the #
|
||||
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
||||
# the Free Software Foundation. #
|
||||
# We created this package for both routine data analysis and academic #
|
||||
# research and it was publicly released in the hope that it will be #
|
||||
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
||||
# #
|
||||
# Visit our website for the full manual and a complete tutorial about #
|
||||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
# These are all S3 implementations for the vctrs package,
|
||||
# that is used internally by tidyverse packages such as dplyr.
|
||||
# They are to convert AMR-specific classes to bare characters and integers.
|
||||
# All of them will be exported using s3_register() in R/zzz.R when loading the package.
|
||||
|
||||
# S3: ab
|
||||
vec_ptype2.character.ab <- function(x, y, ...) {
|
||||
x
|
||||
}
|
||||
vec_ptype2.ab.character <- function(x, y, ...) {
|
||||
y
|
||||
}
|
||||
vec_cast.character.ab <- function(x, to, ...) {
|
||||
unclass(x)
|
||||
}
|
||||
|
||||
# S3: mo
|
||||
vec_ptype2.character.mo <- function(x, y, ...) {
|
||||
x
|
||||
}
|
||||
vec_ptype2.mo.character <- function(x, y, ...) {
|
||||
y
|
||||
}
|
||||
vec_cast.character.mo <- function(x, to, ...) {
|
||||
unclass(x)
|
||||
}
|
||||
|
||||
# S3: disk
|
||||
vec_ptype2.integer.disk <- function(x, y, ...) {
|
||||
x
|
||||
}
|
||||
vec_ptype2.disk.integer <- function(x, y, ...) {
|
||||
y
|
||||
}
|
||||
vec_cast.integer.disk <- function(x, to, ...) {
|
||||
unclass(x)
|
||||
}
|
||||
|
||||
# S3: ab_selector
|
||||
# see https://github.com/tidyverse/dplyr/issues/5955 why this is required
|
||||
vec_ptype2.character.ab_selector <- function(x, y, ...) {
|
||||
x
|
||||
}
|
||||
vec_ptype2.ab_selector.character <- function(x, y, ...) {
|
||||
y
|
||||
}
|
||||
vec_cast.character.ab_selector <- function(x, to, ...) {
|
||||
unclass(x)
|
||||
}
|
||||
@@ -38,7 +38,7 @@ if (utf8_supported && !is_latex) {
|
||||
pkg_env$info_icon <- "i"
|
||||
}
|
||||
|
||||
.onLoad <- function(libname, pkgname) {
|
||||
.onLoad <- function(...) {
|
||||
# Support for tibble headers (type_sum) and tibble columns content (pillar_shaft)
|
||||
# without the need to depend on other packages. This was suggested by the
|
||||
# developers of the vctrs package:
|
||||
@@ -56,15 +56,29 @@ if (utf8_supported && !is_latex) {
|
||||
# Support for frequency tables from the cleaner package
|
||||
s3_register("cleaner::freq", "mo")
|
||||
s3_register("cleaner::freq", "rsi")
|
||||
# Support from skim() from the skimr package
|
||||
# Support for skim() from the skimr package
|
||||
s3_register("skimr::get_skimmers", "mo")
|
||||
s3_register("skimr::get_skimmers", "rsi")
|
||||
s3_register("skimr::get_skimmers", "mic")
|
||||
s3_register("skimr::get_skimmers", "disk")
|
||||
s3_register("ggplot2::ggplot", "rsi")
|
||||
s3_register("ggplot2::ggplot", "mic")
|
||||
s3_register("ggplot2::ggplot", "disk")
|
||||
s3_register("ggplot2::ggplot", "resistance_predict")
|
||||
# Support for autoplot() from the ggplot2 package
|
||||
s3_register("ggplot2::autoplot", "rsi")
|
||||
s3_register("ggplot2::autoplot", "mic")
|
||||
s3_register("ggplot2::autoplot", "disk")
|
||||
s3_register("ggplot2::autoplot", "resistance_predict")
|
||||
# Support vctrs package for use in e.g. dplyr verbs
|
||||
s3_register("vctrs::vec_ptype2", "ab.character")
|
||||
s3_register("vctrs::vec_ptype2", "character.ab")
|
||||
s3_register("vctrs::vec_cast", "character.ab")
|
||||
s3_register("vctrs::vec_ptype2", "mo.character")
|
||||
s3_register("vctrs::vec_ptype2", "character.mo")
|
||||
s3_register("vctrs::vec_cast", "character.mo")
|
||||
s3_register("vctrs::vec_ptype2", "ab_selector.character")
|
||||
s3_register("vctrs::vec_ptype2", "character.ab_selector")
|
||||
s3_register("vctrs::vec_cast", "character.ab_selector")
|
||||
s3_register("vctrs::vec_ptype2", "disk.integer")
|
||||
s3_register("vctrs::vec_ptype2", "integer.disk")
|
||||
s3_register("vctrs::vec_cast", "integer.disk")
|
||||
|
||||
# if mo source exists, fire it up (see mo_source())
|
||||
try({
|
||||
@@ -75,6 +89,7 @@ if (utf8_supported && !is_latex) {
|
||||
|
||||
|
||||
# reference data - they have additional columns compared to `antibiotics` and `microorganisms` to improve speed
|
||||
# they can't be part of R/sysdata.rda since CRAN thinks it would make the package too large (+3 MB)
|
||||
assign(x = "AB_lookup", value = create_AB_lookup(), envir = asNamespace("AMR"))
|
||||
assign(x = "MO_lookup", value = create_MO_lookup(), envir = asNamespace("AMR"))
|
||||
assign(x = "MO.old_lookup", value = create_MO.old_lookup(), envir = asNamespace("AMR"))
|
||||
@@ -82,7 +97,6 @@ if (utf8_supported && !is_latex) {
|
||||
assign(x = "INTRINSIC_R", value = create_intr_resistance(), envir = asNamespace("AMR"))
|
||||
}
|
||||
|
||||
|
||||
# Helper functions --------------------------------------------------------
|
||||
|
||||
create_AB_lookup <- function() {
|
||||
|
||||
@@ -32,6 +32,7 @@ development:
|
||||
|
||||
news:
|
||||
one_page: true
|
||||
cran_dates: true
|
||||
|
||||
navbar:
|
||||
title: "AMR (for R)"
|
||||
|
||||
Binary file not shown.
@@ -26,7 +26,6 @@
|
||||
# some old R instances have trouble installing tinytest, so we ship it too
|
||||
install.packages("data-raw/tinytest_1.2.4.10.tar.gz")
|
||||
install.packages("data-raw/AMR_latest.tar.gz", dependencies = FALSE)
|
||||
install.packages("covr", repos = "https://cran.rstudio.com/")
|
||||
|
||||
pkg_suggests <- gsub("[^a-zA-Z0-9]+", "", unlist(strsplit(packageDescription("AMR", fields = "Suggests"), ", ?")))
|
||||
cat("Packages listed in Suggests:", paste(pkg_suggests, collapse = ", "), "\n")
|
||||
@@ -37,7 +36,7 @@ if (length(to_install) == 0) {
|
||||
}
|
||||
for (i in seq_len(length(to_install))) {
|
||||
cat("Installing package", to_install[i], "\n")
|
||||
tryCatch(install.packages(to_install[i], repos = "https://cran.rstudio.com/", dependencies = TRUE, quiet = TRUE),
|
||||
tryCatch(install.packages(to_install[i], repos = "https://cran.rstudio.com/", dependencies = TRUE, quiet = FALSE),
|
||||
# message = function(m) invisible(),
|
||||
warning = function(w) message(w$message),
|
||||
error = function(e) message(e$message))
|
||||
|
||||
+18
-9
@@ -34,7 +34,7 @@ old_globalenv <- ls(envir = globalenv())
|
||||
# Save internal data to R/sysdata.rda -------------------------------------
|
||||
|
||||
# See 'data-raw/eucast_rules.tsv' for the EUCAST reference file
|
||||
eucast_rules_file <- utils::read.delim(file = "data-raw/eucast_rules.tsv",
|
||||
EUCAST_RULES_DF <- utils::read.delim(file = "data-raw/eucast_rules.tsv",
|
||||
skip = 10,
|
||||
sep = "\t",
|
||||
stringsAsFactors = FALSE,
|
||||
@@ -54,7 +54,7 @@ eucast_rules_file <- utils::read.delim(file = "data-raw/eucast_rules.tsv",
|
||||
select(-sorting_rule)
|
||||
|
||||
# Translations
|
||||
translations_file <- utils::read.delim(file = "data-raw/translations.tsv",
|
||||
TRANSLATIONS <- utils::read.delim(file = "data-raw/translations.tsv",
|
||||
sep = "\t",
|
||||
stringsAsFactors = FALSE,
|
||||
header = TRUE,
|
||||
@@ -68,7 +68,9 @@ translations_file <- utils::read.delim(file = "data-raw/translations.tsv",
|
||||
quote = "")
|
||||
|
||||
# for checking input in `language` argument in e.g. mo_*() and ab_*() functions
|
||||
LANGUAGES_SUPPORTED <- sort(c("en", colnames(translations_file)[nchar(colnames(translations_file)) == 2]))
|
||||
LANGUAGES_SUPPORTED <- sort(c("en", colnames(TRANSLATIONS)[nchar(colnames(TRANSLATIONS)) == 2]))
|
||||
|
||||
# EXAMPLE_ISOLATES <- readRDS("data-raw/example_isolates.rds")
|
||||
|
||||
# vectors of CoNS and CoPS, improves speed in as.mo()
|
||||
create_species_cons_cops <- function(type = c("CoNS", "CoPS")) {
|
||||
@@ -121,18 +123,21 @@ CEPHALOSPORINS <- antibiotics %>% filter(group %like% "cephalosporin") %>% pull(
|
||||
CEPHALOSPORINS_1ST <- antibiotics %>% filter(group %like% "cephalosporin.*1") %>% pull(ab)
|
||||
CEPHALOSPORINS_2ND <- antibiotics %>% filter(group %like% "cephalosporin.*2") %>% pull(ab)
|
||||
CEPHALOSPORINS_3RD <- antibiotics %>% filter(group %like% "cephalosporin.*3") %>% pull(ab)
|
||||
CEPHALOSPORINS_4TH <- antibiotics %>% filter(group %like% "cephalosporin.*4") %>% pull(ab)
|
||||
CEPHALOSPORINS_5TH <- antibiotics %>% filter(group %like% "cephalosporin.*5") %>% pull(ab)
|
||||
CEPHALOSPORINS_EXCEPT_CAZ <- CEPHALOSPORINS[CEPHALOSPORINS != "CAZ"]
|
||||
FLUOROQUINOLONES <- antibiotics %>% filter(atc_group2 %like% "fluoroquinolone") %>% pull(ab)
|
||||
FLUOROQUINOLONES <- antibiotics %>% filter(atc_group2 %like% "fluoroquinolone" | (group %like% "quinolone" & is.na(atc_group2))) %>% pull(ab)
|
||||
LIPOGLYCOPEPTIDES <- as.ab(c("DAL", "ORI", "TLV")) # dalba/orita/tela
|
||||
GLYCOPEPTIDES <- antibiotics %>% filter(group %like% "glycopeptide") %>% pull(ab)
|
||||
GLYCOPEPTIDES_EXCEPT_LIPO <- GLYCOPEPTIDES[!GLYCOPEPTIDES %in% LIPOGLYCOPEPTIDES]
|
||||
LINCOSAMIDES <- antibiotics %>% filter(atc_group2 %like% "lincosamide") %>% pull(ab) %>% c("PRL")
|
||||
MACROLIDES <- antibiotics %>% filter(atc_group2 %like% "macrolide") %>% pull(ab)
|
||||
LINCOSAMIDES <- antibiotics %>% filter(atc_group2 %like% "lincosamide" | (group %like% "lincosamide" & is.na(atc_group2))) %>% pull(ab)
|
||||
MACROLIDES <- antibiotics %>% filter(atc_group2 %like% "macrolide" | (group %like% "macrolide" & is.na(atc_group2))) %>% pull(ab)
|
||||
OXAZOLIDINONES <- antibiotics %>% filter(group %like% "oxazolidinone") %>% pull(ab)
|
||||
PENICILLINS <- antibiotics %>% filter(group %like% "penicillin") %>% pull(ab)
|
||||
POLYMYXINS <- antibiotics %>% filter(group %like% "polymyxin") %>% pull(ab)
|
||||
QUINOLONES <- antibiotics %>% filter(group %like% "quinolone") %>% pull(ab)
|
||||
STREPTOGRAMINS <- antibiotics %>% filter(atc_group2 %like% "streptogramin") %>% pull(ab)
|
||||
TETRACYCLINES <- antibiotics %>% filter(atc_group2 %like% "tetracycline") %>% pull(ab)
|
||||
TETRACYCLINES <- antibiotics %>% filter(group %like% "tetracycline") %>% pull(ab)
|
||||
TETRACYCLINES_EXCEPT_TGC <- TETRACYCLINES[TETRACYCLINES != "TGC"]
|
||||
UREIDOPENICILLINS <- as.ab(c("PIP", "TZP", "AZL", "MEZ"))
|
||||
BETALACTAMS <- c(PENICILLINS, CEPHALOSPORINS, CARBAPENEMS)
|
||||
@@ -141,9 +146,10 @@ DEFINED_AB_GROUPS <- ls(envir = globalenv())
|
||||
DEFINED_AB_GROUPS <- DEFINED_AB_GROUPS[!DEFINED_AB_GROUPS %in% globalenv_before_ab]
|
||||
|
||||
# Export to package as internal data ----
|
||||
usethis::use_data(eucast_rules_file,
|
||||
translations_file,
|
||||
usethis::use_data(EUCAST_RULES_DF,
|
||||
TRANSLATIONS,
|
||||
LANGUAGES_SUPPORTED,
|
||||
# EXAMPLE_ISOLATES,
|
||||
MO_CONS,
|
||||
MO_COPS,
|
||||
AMINOGLYCOSIDES,
|
||||
@@ -153,6 +159,8 @@ usethis::use_data(eucast_rules_file,
|
||||
CEPHALOSPORINS_1ST,
|
||||
CEPHALOSPORINS_2ND,
|
||||
CEPHALOSPORINS_3RD,
|
||||
CEPHALOSPORINS_4TH,
|
||||
CEPHALOSPORINS_5TH,
|
||||
CEPHALOSPORINS_EXCEPT_CAZ,
|
||||
FLUOROQUINOLONES,
|
||||
LIPOGLYCOPEPTIDES,
|
||||
@@ -163,6 +171,7 @@ usethis::use_data(eucast_rules_file,
|
||||
OXAZOLIDINONES,
|
||||
PENICILLINS,
|
||||
POLYMYXINS,
|
||||
QUINOLONES,
|
||||
STREPTOGRAMINS,
|
||||
TETRACYCLINES,
|
||||
TETRACYCLINES_EXCEPT_TGC,
|
||||
|
||||
+1
-1
@@ -1 +1 @@
|
||||
f6b4a2325c4bf3a8d4da337c8cfa07be
|
||||
3231895277e8e2b157672822c1913639
|
||||
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
+12
-12
@@ -44,7 +44,7 @@
|
||||
"BCZ" 65807 "Bicyclomycin (Bicozamycin)" "Other antibacterials" "" "c(\"aizumycin\", \"bacfeed\", \"bacteron\", \"bicozamicina\", \"bicozamycin\", \"bicozamycine\", \"bicozamycinum\")" "character(0)"
|
||||
"BDP" "J01EA02" 68760 "Brodimoprim" "Trimethoprims" "Sulfonamides and trimethoprim" "Trimethoprim and derivatives" "" "c(\"brodimoprim\", \"brodimoprima\", \"brodimoprime\", \"brodimoprimum\", \"bromdimoprim\", \"hyprim\", \"unitrim\")" 0.2 "g" "character(0)"
|
||||
"BUT" 47472 "Butoconazole" "Antifungals/antimycotics" "" "c(\"butaconazole\", \"butoconazol\", \"butoconazole\", \"butoconazolum\", \"compositenstarke\", \"dahlin\", \"femstat\", \"gynofort\", \"polyfructosanum\")" "character(0)"
|
||||
"CDZ" "J01DD09" 44242317 "Cadazolid" "Cephalosporins (3rd gen.)" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "" "cadazolid" 2 "g" "character(0)"
|
||||
"CDZ" 44242317 "Cadazolid" "Oxazolidinones" "" "cadazolid" "character(0)"
|
||||
"CLA" "J04AA03" "Calcium aminosalicylate" "Antimycobacterials" "Drugs for treatment of tuberculosis" "Aminosalicylic acid and derivatives" "" "" 15 ""
|
||||
"CAP" "J04AB30" 135565060 "Capreomycin" "Antimycobacterials" "Drugs for treatment of tuberculosis" "Antibiotics" "c(\"\", \"capr\")" "" 1 "g" ""
|
||||
"CRB" "J01CA03" 20824 "Carbenicillin" "Beta-lactams/penicillins" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "c(\"bar\", \"carb\", \"cb\")" "c(\"anabactyl\", \"carbenicilina\", \"carbenicillin\", \"carbenicillina\", \"carbenicilline\", \"carbenicillinum\", \"geopen\", \"pyopen\")" 12 "g" "3434-8"
|
||||
@@ -108,8 +108,8 @@
|
||||
"CPT" "J01DI02" 56841980 "Ceftaroline" "Cephalosporins (5th gen.)" "c(\"\", \"cfro\")" "c(\"teflaro\", \"zinforo\")" 1.2 "character(0)"
|
||||
"CPA" "Ceftaroline/avibactam" "Cephalosporins (5th gen.)" "" "" ""
|
||||
"CAZ" "J01DD02" 5481173 "Ceftazidime" "Cephalosporins (3rd gen.)" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"caz\", \"cefta\", \"cfta\", \"cftz\", \"taz\", \"tz\", \"xtz\")" "c(\"ceftazidim\", \"ceftazidima\", \"ceftazidime\", \"ceftazidimum\", \"ceptaz\", \"fortaz\", \"fortum\", \"pentacef\", \"tazicef\", \"tazidime\")" 4 "g" "c(\"21151-6\", \"3449-6\", \"80960-8\")"
|
||||
"CZA" "J01DD52" 90643431 "Ceftazidime/avibactam" "Cephalosporins (3rd gen.)" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"\", \"cfav\")" "c(\"avycaz\", \"zavicefta\")" 6 "g" ""
|
||||
"CCV" "J01DD52" 9575352 "Ceftazidime/clavulanic acid" "Cephalosporins (3rd gen.)" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"czcl\", \"xtzl\")" "" 6 ""
|
||||
"CZA" 90643431 "Ceftazidime/avibactam" "Cephalosporins (3rd gen.)" "c(\"\", \"cfav\")" "c(\"avycaz\", \"zavicefta\")" ""
|
||||
"CCV" "J01DD52" 9575352 "Ceftazidime/clavulanic acid" "Cephalosporins (3rd gen.)" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"czcl\", \"xtzl\")" "" 6 "g" ""
|
||||
"CEM" 6537431 "Cefteram" "Cephalosporins (3rd gen.)" "" "c(\"cefteram\", \"cefterame\", \"cefteramum\", \"ceftetrame\")" "character(0)"
|
||||
"CPL" 5362114 "Cefteram pivoxil" "Cephalosporins (3rd gen.)" "" "c(\"cefteram pivoxil\", \"tomiron\")" "character(0)"
|
||||
"CTL" "J01DB12" 65755 "Ceftezole" "Cephalosporins (1st gen.)" "Other beta-lactam antibacterials" "First-generation cephalosporins" "" "c(\"ceftezol\", \"ceftezole\", \"ceftezolo\", \"ceftezolum\", \"demethylcefazolin\")" 3 "g" "character(0)"
|
||||
@@ -117,9 +117,9 @@
|
||||
"TIO" 6328657 "Ceftiofur" "Cephalosporins (3rd gen.)" "" "c(\"ceftiofur\", \"ceftiofurum\", \"excede\", \"excenel\", \"naxcel\")" "character(0)"
|
||||
"CZX" "J01DD07" 6533629 "Ceftizoxime" "Cephalosporins (3rd gen.)" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"cfzx\", \"ctz\", \"cz\", \"czx\", \"tiz\", \"zox\")" "c(\"cefizox\", \"ceftisomin\", \"ceftix\", \"ceftizoxima\", \"ceftizoxime\", \"ceftizoximum\", \"epocelin\", \"eposerin\")" 4 "g" "c(\"25243-7\", \"3450-4\")"
|
||||
"CZP" 9578661 "Ceftizoxime alapivoxil" "Cephalosporins (3rd gen.)" "" "" ""
|
||||
"BPR" "J01DI01" 135413542 "Ceftobiprole" "Cephalosporins (5th gen.)" "" "ceftobiprole" 1.5 "character(0)"
|
||||
"CFM1" "J01DI01" 135413544 "Ceftobiprole medocaril" "Cephalosporins (5th gen.)" "Other beta-lactam antibacterials" "Other cephalosporins" "" "" 1.5 ""
|
||||
"CEI" "J01DI54" "Ceftolozane/enzyme inhibitor" "Cephalosporins (5th gen.)" "Other beta-lactam antibacterials" "Other cephalosporins" "" "" 3 ""
|
||||
"BPR" 135413542 "Ceftobiprole" "Cephalosporins (5th gen.)" "" "ceftobiprole" "character(0)"
|
||||
"CFM1" "J01DI01" 135413544 "Ceftobiprole medocaril" "Cephalosporins (5th gen.)" "Other beta-lactam antibacterials" "Other cephalosporins and penems" "" "" 1.5 "g" ""
|
||||
"CEI" "J01DI54" "Ceftolozane/enzyme inhibitor" "Cephalosporins (5th gen.)" "Other beta-lactam antibacterials" "Other cephalosporins and penems" "" "" 3 ""
|
||||
"CZT" "Ceftolozane/tazobactam" "Cephalosporins (5th gen.)" "" "" ""
|
||||
"CRO" "J01DD04" 5479530 "Ceftriaxone" "Cephalosporins (3rd gen.)" "Other beta-lactam antibacterials" "Third-generation cephalosporins" "c(\"axo\", \"cax\", \"cftr\", \"cro\", \"ctr\", \"frx\", \"tx\")" "c(\"biotrakson\", \"cefatriaxone\", \"cefatriaxone hydrate\", \"ceftriaxon\", \"ceftriaxona\", \"ceftriaxone\", \"ceftriaxone sodium\", \"ceftriaxonum\", \"ceftriazone\", \"cephtriaxone\", \"longacef\", \"rocefin\", \"rocephalin\", \"rocephin\", \"rocephine\", \"rophex\")" 2 "g" "c(\"25244-5\", \"3451-2\", \"80957-4\")"
|
||||
"CXM" "J01DC02" 5479529 "Cefuroxime" "Cephalosporins (2nd gen.)" "Other beta-lactam antibacterials" "Second-generation cephalosporins" "c(\"cfrx\", \"cfur\", \"cfx\", \"crm\", \"cxm\", \"fur\", \"rox\", \"xm\")" "c(\"biofuroksym\", \"cefuril\", \"cefuroxim\", \"cefuroxime\", \"cefuroximine\", \"cefuroximo\", \"cefuroximum\", \"cephuroxime\", \"kefurox\", \"sharox\", \"zinacef\", \"zinacef danmark\")" 0.5 "g" 3 "g" "c(\"25245-2\", \"3452-0\", \"80608-3\", \"80617-4\")"
|
||||
@@ -173,7 +173,7 @@
|
||||
"DIR" "J01FA13" 6473883 "Dirithromycin" "Macrolides/lincosamides" "Macrolides, lincosamides and streptogramins" "Macrolides" "" "c(\"dirithromycin\", \"dirithromycine\", \"dirithromycinum\", \"diritromicina\", \"divitross\", \"dynabac\", \"noriclan\", \"valodin\")" 0.5 "g" "character(0)"
|
||||
"DOR" "J01DH04" 73303 "Doripenem" "Carbapenems" "Other beta-lactam antibacterials" "Carbapenems" "dori" "c(\"doribax\", \"doripenem\", \"doripenem hydrate\", \"finibax\")" 1.5 "character(0)"
|
||||
"DOX" "J01AA02" 54671203 "Doxycycline" "Tetracyclines" "Tetracyclines" "Tetracyclines" "c(\"dox\", \"doxy\")" "c(\"atridox\", \"azudoxat\", \"deoxymykoin\", \"dossiciclina\", \"doxcycline anhydrous\", \"doxiciclina\", \"doxitard\", \"doxivetin\", \"doxycen\", \"doxychel\", \"doxycin\", \"doxycyclin\", \"doxycycline\", \"doxycycline calcium\", \"doxycycline hyclate\", \"doxycyclinum\", \"doxylin\", \"doxysol\", \"doxytec\", \"doxytetracycline\", \"hydramycin\", \"investin\", \"jenacyclin\", \"liviatin\", \"monodox\", \"oracea\", \"periostat\", \"ronaxan\", \"spanor\", \"supracyclin\", \"vibramycin\", \"vibramycin novum\", \"vibramycine\", \"vibravenos\", \"zenavod\")" 0.1 "g" 0.1 "g" "c(\"10986-8\", \"21250-6\", \"26902-7\")"
|
||||
"ECO" "J01XDXX" 3198 "Econazole" "Antifungals/antimycotics" "econ" "c(\"econazol\", \"econazole\", \"econazolum\", \"ecostatin\", \"ecostatin cream\", \"palavale\", \"pevaryl\", \"spectazole\", \"spectazole cream\")" "character(0)"
|
||||
"ECO" "D01AC03" 3198 "Econazole" "Antifungals/antimycotics" "Antifungals for topical use" "Imidazole and triazole derivatives" "econ" "c(\"econazol\", \"econazole\", \"econazolum\", \"ecostatin\", \"ecostatin cream\", \"palavale\", \"pevaryl\", \"spectazole\", \"spectazole cream\")" "character(0)"
|
||||
"ENX" "J01MA04" 3229 "Enoxacin" "Quinolones" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"enox\")" "c(\"almitil\", \"bactidan\", \"bactidron\", \"comprecin\", \"enofloxacine\", \"enoksetin\", \"enoram\", \"enoxacin\", \"enoxacina\", \"enoxacine\", \"enoxacino\", \"enoxacinum\", \"enoxen\", \"enoxin\", \"enoxor\", \"flumark\", \"penetrex\")" 0.8 "g" "c(\"16816-1\", \"3590-7\")"
|
||||
"ENR" 71188 "Enrofloxacin" "Quinolones" "" "c(\"baytril\", \"enrofloxacin\", \"enrofloxacine\", \"enrofloxacino\", \"enrofloxacinum\")" "character(0)"
|
||||
"ENV" 135565326 "Enviomycin (Tuberactinomycin)" "Antimycobacterials" "" "c(\"enviomicina\", \"enviomycin\", \"enviomycina\", \"enviomycinum\")" "character(0)"
|
||||
@@ -190,7 +190,7 @@
|
||||
"ETI1" "J04AD03" 2761171 "Ethionamide" "Antimycobacterials" "Drugs for treatment of tuberculosis" "Thiocarbamide derivatives" "ethi" "c(\"aethionamidum\", \"aetina\", \"aetiva\", \"amidazin\", \"amidazine\", \"ethatyl\", \"ethimide\", \"ethina\", \"ethinamide\", \"ethionamide\", \"ethionamidum\", \"ethioniamide\", \"ethylisothiamide\", \"ethyonomide\", \"etimid\", \"etiocidan\", \"etionamid\", \"etionamida\", \"etionamide\", \"etioniamid\", \"etionid\", \"etionizin\", \"etionizina\", \"etionizine\", \"fatoliamid\", \"iridocin\", \"iridocin bayer\", \"iridozin\", \"isothin\", \"isotiamida\", \"itiocide\", \"nicotion\", \"nisotin\", \"nizotin\", \"rigenicid\", \"sertinon\", \"teberus\", \"thianid\", \"thianide\",
|
||||
\"thioamide\", \"thiodine\", \"thiomid\", \"thioniden\", \"tianid\", \"tiomid\", \"trecator\", \"trecator sc\", \"trekator\", \"trescatyl\", \"trescazide\", \"tubenamide\", \"tubermin\", \"tuberoid\", \"tuberoson\")" 0.75 "g" "16845-0"
|
||||
"ETO" 6034 "Ethopabate" "Other antibacterials" "" "c(\"amprol plus\", \"ethopabat\", \"ethopabate\", \"ethyl pabate\")" "character(0)"
|
||||
"FAR" "J01DI03" 65894 "Faropenem" "Other antibacterials" "" "c(\"faropenem\", \"faropenem sodium\", \"fropenem\", \"fropenum sodium\")" 0.75 "character(0)"
|
||||
"FAR" "J01DI03" 65894 "Faropenem" "Other antibacterials" "Other beta-lactam antibacterials" "Other cephalosporins and penems" "" "c(\"faropenem\", \"faropenem sodium\", \"fropenem\", \"fropenum sodium\")" 0.75 "g" "character(0)"
|
||||
"FDX" 10034073 "Fidaxomicin" "Other antibacterials" "" "c(\"dificid\", \"dificlir\", \"difimicin\", \"fidaxomicin\", \"lipiarmycin\", \"tiacumicin b\")" "character(0)"
|
||||
"FIN" 11567473 "Finafloxacin" "Quinolones" "" "finafloxacin" "character(0)"
|
||||
"FLA" 46783781 "Flavomycin" "Other antibacterials" "" "moenomycin complex" "character(0)"
|
||||
@@ -309,7 +309,7 @@
|
||||
"NTR" "J01XX07" 19910 "Nitroxoline" "Quinolones" "Other antibacterials" "Other antibacterials" "" "c(\"galinok\", \"isinok\", \"nibiol\", \"nicene forte\", \"nitroxolin\", \"nitroxolina\", \"nitroxoline\", \"nitroxolinum\", \"notroxoline\", \"noxibiol\")" 1 "g" "character(0)"
|
||||
"NOR" "J01MA06" 4539 "Norfloxacin" "Quinolones" "Quinolone antibacterials" "Fluoroquinolones" "c(\"nor\", \"norf\", \"nx\", \"nxn\")" "c(\"baccidal\", \"barazan\", \"chibroxin\", \"chibroxine\", \"chibroxol\", \"fulgram\", \"gonorcin\", \"lexinor\", \"nolicin\", \"noracin\", \"noraxin\", \"norflo\", \"norfloxacin\", \"norfloxacine\", \"norfloxacino\", \"norfloxacinum\", \"norocin\", \"noroxin\", \"noroxine\", \"norxacin\", \"sebercim\", \"uroxacin\", \"utinor\", \"zoroxin\")" 0.8 "g" "3867-9"
|
||||
"NVA" 10419027 "Norvancomycin" "Glycopeptides" "" "norvancomycin" "character(0)"
|
||||
"NOV" "QJ01XX95" 54675769 "Novobiocin" "Other antibacterials" "novo" "c(\"albamix\", \"albamycin\", \"cardelmycin\", \"cathocin\", \"cathomycin\", \"crystallinic acid\", \"inamycin\", \"novobiocin\", \"novobiocina\", \"novobiocine\", \"novobiocinum\", \"robiocina\", \"sirbiocina\", \"spheromycin\", \"stilbiocina\", \"streptonivicin\")" "17378-1"
|
||||
"NOV" 54675769 "Novobiocin" "Other antibacterials" "novo" "c(\"albamix\", \"albamycin\", \"cardelmycin\", \"cathocin\", \"cathomycin\", \"crystallinic acid\", \"inamycin\", \"novobiocin\", \"novobiocina\", \"novobiocine\", \"novobiocinum\", \"robiocina\", \"sirbiocina\", \"spheromycin\", \"stilbiocina\", \"streptonivicin\")" "17378-1"
|
||||
"NYS" "G01AA01" 6433272 "Nystatin" "Antifungals/antimycotics" "nyst" "c(\"biofanal\", \"candex lotion\", \"comycin\", \"diastatin\", \"herniocid\", \"moronal\", \"myconystatin\", \"mycostatin\", \"mycostatin pastilles\", \"mykinac\", \"mykostatyna\", \"nilstat\", \"nistatin\", \"nistatina\", \"nyamyc\", \"nyotran\", \"nyotrantrade mark\", \"nystaform\", \"nystan\", \"nystatin\", \"nystatin a\", \"nystatin g\", \"nystatin lf\", \"nystatine\", \"nystatinum\", \"nystatyna\", \"nystavescent\", \"nystex\", \"nystop\", \"stamycin\", \"terrastatin\", \"zydin e\")" "character(0)"
|
||||
"OFX" "J01MA01" 4583 "Ofloxacin" "Quinolones" "Quinolone antibacterials" "Fluoroquinolones" "c(\"of\", \"ofl\", \"oflo\", \"ofx\")" "c(\"bactocin\", \"danoflox\", \"effexin\", \"exocin\", \"exocine\", \"flobacin\", \"flodemex\", \"flotavid\", \"flovid\", \"floxal\", \"floxil\", \"floxin\", \"floxin otic\", \"floxstat\", \"fugacin\", \"inoflox\", \"kinflocin\", \"kinoxacin\", \"levofloxacin hcl\", \"liflox\", \"loxinter\", \"marfloxacin\", \"medofloxine\", \"mergexin\", \"monoflocet\", \"novecin\", \"nufafloqo\", \"occidal\", \"ocuflox\", \"oflocee\", \"oflocet\", \"oflocin\", \"oflodal\", \"oflodex\", \"oflodura\", \"ofloxacin\", \"ofloxacin otic\", \"ofloxacina\", \"ofloxacine\", \"ofloxacino\", \"ofloxacinum\",
|
||||
\"ofloxin\", \"onexacin\", \"operan\", \"orocin\", \"otonil\", \"oxaldin\", \"pharflox\", \"praxin\", \"puiritol\", \"qinolon\", \"quinolon\", \"quotavil\", \"sinflo\", \"tabrin\", \"taravid\", \"tariflox\", \"tarivid\", \"telbit\", \"tructum\", \"uro tarivid\", \"viotisone\", \"visiren\", \"zanocin\")" 0.4 "g" 0.4 "g" "c(\"25264-3\", \"3877-8\")"
|
||||
@@ -344,7 +344,7 @@
|
||||
"PIS" "Piperacillin/sulbactam" "Beta-lactams/penicillins" "" "" ""
|
||||
"TZP" "J01CR05" 461573 "Piperacillin/tazobactam" "Beta-lactams/penicillins" "Beta-lactam antibacterials, penicillins" "Combinations of penicillins, incl. beta-lactamase inhibitors" "c(\"p/t\", \"piptaz\", \"piptazo\", \"pit\", \"pita\", \"pt\", \"ptc\", \"ptz\", \"tzp\")" "c(\"\", \"tazocel\", \"tazocillin\", \"tazocin\", \"zosyn\")" 14 "g" "character(0)"
|
||||
"PRC" 71978 "Piridicillin" "Beta-lactams/penicillins" "" "piridicillin" "character(0)"
|
||||
"PRL" 157385 "Pirlimycin" "Other antibacterials" "" "c(\"pirlimycin\", \"pirlimycina\", \"pirlimycine\", \"pirlimycinum\", \"pirsue\")" "character(0)"
|
||||
"PRL" 157385 "Pirlimycin" "Macrolides/lincosamides" "" "c(\"pirlimycin\", \"pirlimycina\", \"pirlimycine\", \"pirlimycinum\", \"pirsue\")" "character(0)"
|
||||
"PIR" "J01MB03" 4855 "Piromidic acid" "Quinolones" "Quinolone antibacterials" "Other quinolones" "" "c(\"acide piromidique\", \"acido piromidico\", \"acidum piromidicum\", \"actrun c\", \"bactramyl\", \"enterol\", \"gastrurol\", \"panacid\", \"pirodal\", \"piromidic acid\", \"pyrido\", \"reelon\", \"septural\", \"urisept\", \"uropir\", \"zaomeal\")" 2 "g" "character(0)"
|
||||
"PVM" "J01CA02" 33478 "Pivampicillin" "Beta-lactams/penicillins" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"berocillin\", \"pivaloylampicillin\", \"pivampicilina\", \"pivampicillin\", \"pivampicilline\", \"pivampicillinum\", \"pondocillin\")" 1.05 "g" "character(0)"
|
||||
"PME" "J01CA08" 115163 "Pivmecillinam" "Beta-lactams/penicillins" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"amdinocillin pivoxil\", \"coactabs\", \"hydroxymethyl\", \"pivmecilinamo\", \"pivmecillinam\", \"pivmecillinam hcl\", \"pivmecillinamum\")" 0.6 "g" "character(0)"
|
||||
@@ -368,7 +368,7 @@
|
||||
"RAC" 56052 "Ractopamine" "Other antibacterials" "" "c(\"ractopamina\", \"ractopamine\", \"ractopaminum\")" "character(0)"
|
||||
"RAM" 16132338 "Ramoplanin" "Glycopeptides" "" "ramoplanin" "character(0)"
|
||||
"RZM" 10993211 "Razupenem" "Carbapenems" "" "razupenem" "character(0)"
|
||||
"RTP" "A07AA11" 6918462 "Retapamulin" "Other antibacterials" "Intestinal antiinfectives" "Antibiotics" "" "c(\"altabax\", \"altargo\", \"retapamulin\")" 0.6 "g" "character(0)"
|
||||
"RTP" "D06AX13" 6918462 "Retapamulin" "Other antibacterials" "Antibiotics for topical use" "Other antibiotics for topical use" "" "c(\"altabax\", \"altargo\", \"retapamulin\")" "character(0)"
|
||||
"RBC" "J02AC05" 44631912 "Ribociclib" "Antifungals/antimycotics" "Antimycotics for systemic use" "Triazole derivatives" "ribo" "c(\"kisqali\", \"ribociclib\")" 0.2 0.2 "character(0)"
|
||||
"RST" "J01GB10" 33042 "Ribostamycin" "Aminoglycosides" "Aminoglycoside antibacterials" "Other aminoglycosides" "" "c(\"dekamycin iv\", \"hetangmycin\", \"ribastamin\", \"ribostamicina\", \"ribostamycin\", \"ribostamycine\", \"ribostamycinum\", \"vistamycin\", \"xylostatin\")" 1 "g" "character(0)"
|
||||
"RID1" 16659285 "Ridinilazole" "Other antibacterials" "" "ridinilazole" "character(0)"
|
||||
@@ -500,7 +500,7 @@
|
||||
"TVA" "J01MA13" 62959 "Trovafloxacin" "Quinolones" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"trov\")" "c(\"trovafloxacin\", \"trovan\")" 0.2 "g" 0.2 "g" "character(0)"
|
||||
"TUL" 9832301 "Tulathromycin" "Macrolides/lincosamides" "" "c(\"draxxin\", \"tulathrmycin a\", \"tulathromycin\", \"tulathromycin a\")" "character(0)"
|
||||
"TYL" 5280440 "Tylosin" "Macrolides/lincosamides" "" "c(\"fradizine\", \"tilosina\", \"tylocine\", \"tylosin\", \"tylosin a\", \"tylosine\", \"tylosinum\")" "87587-2"
|
||||
"TYL1" "A07AA11" 6441094 "Tylvalosin" "Other antibacterials" "Intestinal antiinfectives" "Antibiotics" "" "" 0.6 "g" ""
|
||||
"TYL1" 6441094 "Tylvalosin" "Macrolides/lincosamides" "" "" ""
|
||||
"PRU1" 124225 "Ulifloxacin (Prulifloxacin)" "Other antibacterials" "" "ulifloxacin" "character(0)"
|
||||
"VAN" "J01XA01" 14969 "Vancomycin" "Glycopeptides" "Other antibacterials" "Glycopeptide antibacterials" "c(\"va\", \"van\", \"vanc\")" "c(\"vancocin\", \"vancocin hcl\", \"vancoled\", \"vancomicina\", \"vancomycin\", \"vancomycin hcl\", \"vancomycine\", \"vancomycinum\", \"vancor\", \"viomycin derivative\")" 2 "g" "c(\"13586-3\", \"13587-1\", \"20578-1\", \"31012-8\", \"39092-2\", \"39796-8\", \"39797-6\", \"4089-9\", \"4090-7\", \"4091-5\", \"4092-3\", \"50938-0\", \"59381-4\")"
|
||||
"VAM" "Vancomycin-macromethod" "Glycopeptides" "" "" ""
|
||||
|
||||
Binary file not shown.
Binary file not shown.
@@ -0,0 +1,28 @@
|
||||
library(dplyr)
|
||||
example_isolates %>%
|
||||
select(mo, where(is.rsi)) %>%
|
||||
tidyr::pivot_longer(cols = where(is.rsi)) %>%
|
||||
# remove intrisic R
|
||||
filter(!paste(mo, name) %in% AMR:::INTRINSIC_R) %>%
|
||||
mutate(name = as.ab(name),
|
||||
value = ifelse(value == "R", 1, 0),
|
||||
class = ab_group(name)) %>%
|
||||
group_by(mo, class) %>%
|
||||
summarise(n = n(),
|
||||
res = mean(value, na.rm = TRUE)) %>%
|
||||
filter(n > 30, !is.na(res))
|
||||
|
||||
|
||||
|
||||
df <- example_isolates
|
||||
search_mo <- "B_ESCHR_COLI"
|
||||
intrinsic_res <- INTRINSIC_R[INTRINSIC_R %like% search_mo]
|
||||
intrinsic_res <- gsub(".* (.*)", "\\1", intrinsic_res)
|
||||
|
||||
x <- df %>%
|
||||
select(mo, where(is.rsi)) %>%
|
||||
filter(mo == search_mo) %>%
|
||||
# at least 30 results available
|
||||
select(function(x) sum(!is.na(x)) >= 30) %>%
|
||||
# remove intrisic R
|
||||
select(!matches(paste(intrinsic_res, collapse = "|")))
|
||||
+19
-1
@@ -118,7 +118,7 @@ read_EUCAST <- function(sheet, file, guideline_name) {
|
||||
seq(from = 41, to = 49, by = 1),
|
||||
seq(from = 81, to = 89, by = 1))
|
||||
has_superscript <- function(x) {
|
||||
# because due to floating point error 0.1252 is not in:
|
||||
# because due to floating point error, 0.1252 is not in:
|
||||
# seq(from = 0.1251, to = 0.1259, by = 0.0001)
|
||||
sapply(x, function(x) any(near(x, MICs_with_trailing_superscript)))
|
||||
}
|
||||
@@ -242,3 +242,21 @@ for (i in 2:length(sheets_to_analyse)) {
|
||||
guideline_name = guideline_name))
|
||||
, error = function(e) message(e$message))
|
||||
}
|
||||
|
||||
# 2021-07-12 fix for Morganellaceae (check other lines too next time)
|
||||
morg <- rsi_translation %>%
|
||||
as_tibble() %>%
|
||||
filter(ab == "IPM",
|
||||
guideline == "EUCAST 2021",
|
||||
mo == as.mo("Enterobacterales")) %>%
|
||||
mutate(mo = as.mo("Morganellaceae"))
|
||||
morg[which(morg$method == "MIC"), "breakpoint_S"] <- 0.001
|
||||
morg[which(morg$method == "MIC"), "breakpoint_R"] <- 4
|
||||
morg[which(morg$method == "DISK"), "breakpoint_S"] <- 50
|
||||
morg[which(morg$method == "DISK"), "breakpoint_R"] <- 19
|
||||
|
||||
rsi_translation <- rsi_translation %>%
|
||||
bind_rows(morg) %>%
|
||||
bind_rows(morg %>%
|
||||
mutate(guideline = "EUCAST 2020")) %>%
|
||||
arrange(desc(guideline), ab, mo, method)
|
||||
|
||||
@@ -647,6 +647,7 @@ antibiotics <- antibiotics %>%
|
||||
|
||||
|
||||
# update DDDs from WHOCC website
|
||||
# last time checked: 2021-06-23
|
||||
ddd_oral <- double(length = nrow(antibiotics))
|
||||
ddd_iv <- double(length = nrow(antibiotics))
|
||||
progress <- progress_ticker(nrow(antibiotics))
|
||||
@@ -667,7 +668,7 @@ antibiotics$iv_ddd <- ddd_iv
|
||||
# set as data.frame again
|
||||
antibiotics <- as.data.frame(antibiotics, stringsAsFactors = FALSE)
|
||||
class(antibiotics$ab) <- c("ab", "character")
|
||||
antibiotics <- antibiotics %>% dplyr::arrange(name)
|
||||
antibiotics <- dplyr::arrange(antibiotics, name)
|
||||
|
||||
# make all abbreviations and synonyms lower case, unique and alphabetically sorted ----
|
||||
for (i in 1:nrow(antibiotics)) {
|
||||
@@ -683,5 +684,5 @@ for (i in 1:nrow(antibiotics)) {
|
||||
|
||||
# REFER TO data-raw/loinc.R FOR ADDING LOINC CODES
|
||||
|
||||
usethis::use_data(antibiotics, overwrite = TRUE, version = 2)
|
||||
usethis::use_data(antibiotics, overwrite = TRUE, version = 2, compress = "xz")
|
||||
rm(antibiotics)
|
||||
|
||||
@@ -32,7 +32,7 @@ for (i in seq_len(nrow(antibiotics))) {
|
||||
}
|
||||
|
||||
int_resis <- eucast_rules(int_resis,
|
||||
eucast_rules_df = subset(AMR:::eucast_rules_file,
|
||||
eucast_rules_df = subset(AMR:::EUCAST_RULES_DF,
|
||||
is.na(have_these_values) & reference.version == 3.2),
|
||||
info = FALSE)
|
||||
|
||||
|
||||
+1
-1
@@ -1 +1 @@
|
||||
1a7fe52f8185c9bb2c470712863d1887
|
||||
67a83b234f25a303c7944222bea47d73
|
||||
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
@@ -754,6 +754,8 @@
|
||||
"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE
|
||||
"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Imipenem/relebactam" "Viridans group streptococci" 2 2 FALSE
|
||||
"EUCAST 2021" "MIC" "(unknown name)" "Imipenem/relebactam" "PK PD breakpoints" 2 2 FALSE
|
||||
"EUCAST 2021" "DISK" "Morganellaceae" "Imipenem" "Enterobacterales" "10ug" 50 19 FALSE
|
||||
"EUCAST 2021" "MIC" "Morganellaceae" "Imipenem" "Enterobacterales" 0.001 4 FALSE
|
||||
"EUCAST 2021" "DISK" "Enterobacterales" "Imipenem" "Enterobacterales" "10ug" 22 19 FALSE
|
||||
"EUCAST 2021" "MIC" "Enterobacterales" "Imipenem" "Enterobacterales" 2 4 FALSE
|
||||
"EUCAST 2021" "DISK" "Acinetobacter" "Imipenem" "Acinetobacter" "10ug" 24 21 FALSE
|
||||
@@ -2542,6 +2544,8 @@
|
||||
"EUCAST 2020" "MIC" "Staphylococcus saccharolyticus" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE
|
||||
"EUCAST 2020" "MIC" "Viridans Group Streptococcus (VGS)" "Imipenem/relebactam" "Viridans group streptococci" 2 2 FALSE
|
||||
"EUCAST 2020" "MIC" "(unknown name)" "Imipenem/relebactam" "PK PD breakpoints" 2 2 FALSE
|
||||
"EUCAST 2020" "DISK" "Morganellaceae" "Imipenem" "Enterobacterales" "10ug" 50 19 FALSE
|
||||
"EUCAST 2020" "MIC" "Morganellaceae" "Imipenem" "Enterobacterales" 0.001 4 FALSE
|
||||
"EUCAST 2020" "DISK" "Enterobacterales" "Imipenem" "Enterobacterales" "10ug" 22 17 FALSE
|
||||
"EUCAST 2020" "MIC" "Enterobacterales" "Imipenem" "Enterobacterales" 2 4 FALSE
|
||||
"EUCAST 2020" "DISK" "Acinetobacter" "Imipenem" "Acinetobacter" "10ug" 24 21 FALSE
|
||||
|
||||
@@ -16,6 +16,7 @@ unknown genus TRUE TRUE FALSE TRUE unbekannte Gattung onbekend geslacht género
|
||||
unknown species TRUE TRUE FALSE TRUE unbekannte Art onbekende soort especie desconocida specie sconosciute espèce inconnue espécies desconhecida
|
||||
unknown subspecies TRUE TRUE FALSE TRUE unbekannte Unterart onbekende ondersoort subespecie desconocida sottospecie sconosciute sous-espèce inconnue subespécies desconhecida
|
||||
unknown rank TRUE TRUE FALSE TRUE unbekannter Rang onbekende rang rango desconocido grado sconosciuto rang inconnu classificação desconhecido
|
||||
group TRUE TRUE FALSE TRUE Gruppe groep grupo gruppo groupe grupo
|
||||
CoNS FALSE TRUE FALSE TRUE KNS CNS SCN
|
||||
CoPS FALSE TRUE FALSE TRUE KPS CPS SCP
|
||||
Gram-negative TRUE TRUE FALSE FALSE Gramnegativ Gram-negatief Gram negativo Gram negativo Gram négatif Gram negativo
|
||||
@@ -31,8 +32,10 @@ vegetative TRUE TRUE FALSE FALSE vegetativ vegetatief vegetativo vegetativo vég
|
||||
([([ ]*?)Group TRUE TRUE FALSE FALSE \\1Gruppe \\1Groep \\1Grupo \\1Gruppo \\1Groupe \\1Grupo
|
||||
no .*growth TRUE FALSE FALSE FALSE keine? .*wachstum geen .*groei no .*crecimientonon sem .*crescimento pas .*croissance sem .*crescimento
|
||||
no|not TRUE FALSE FALSE FALSE keine? geen|niet no|sin sem non sem
|
||||
Susceptible TRUE FALSE FALSE FALSE Empfindlich Gevoelig Susceptible
|
||||
Intermediate TRUE FALSE FALSE FALSE Mittlere Intermediair Intermedio
|
||||
Susceptible, incr. exp. FALSE TRUE FALSE FALSE Empfindlich, erh Belastung Gevoelig, hoge dosis
|
||||
susceptible, incr. exp. FALSE TRUE FALSE FALSE empfindlich, erh Belastung gevoelig, hoge dosis
|
||||
Susceptible TRUE FALSE FALSE FALSE Empfindlich Gevoelig Susceptible
|
||||
Incr. exposure TRUE FALSE FALSE FALSE Empfindlich, erh Belastung 'Incr. exposure' 'Incr. exposure'
|
||||
Resistant TRUE FALSE FALSE FALSE Resistent Resistent Resistente
|
||||
antibiotic TRUE TRUE FALSE FALSE Antibiotikum antibioticum antibiótico
|
||||
|
||||
|
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<html lang="en">
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||||
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<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
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<div class="navbar-header">
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<button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
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@@ -80,102 +39,102 @@
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<span class="navbar-brand">
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<a class="navbar-link" href="https://msberends.github.io/AMR//index.html">AMR (for R)</a>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
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<a class="navbar-link" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
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Predict antimicrobial resistance
|
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Conduct principal component analysis for AMR
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||||
</a>
|
||||
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|
||||
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||||
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Determine multi-drug resistance (MDR)
|
||||
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||||
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||||
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Work with WHONET data
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|
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||||
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||||
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<span class="fa fa-file-upload"></span>
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Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
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|
||||
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||||
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Apply EUCAST rules
|
||||
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|
||||
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|
||||
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Get properties of a microorganism
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</a>
|
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|
||||
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||||
Get properties of an antibiotic
|
||||
</a>
|
||||
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|
||||
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||||
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||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -183,29 +142,29 @@
|
||||
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|
||||
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|
||||
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|
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@@ -213,23 +172,23 @@
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</div><!--/.nav-collapse -->
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</div><!--/.container -->
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</div>
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||||
|
||||
</header>
|
||||
|
||||
<div class="row">
|
||||
</header><div class="row">
|
||||
<div class="contents col-md-9">
|
||||
<div class="page-header">
|
||||
<h1>Page not found (404)</h1>
|
||||
@@ -240,31 +199,31 @@ Content not found. Please use links in the navbar.
|
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</div>
|
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|
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<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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<nav id="toc" data-toggle="toc" class="sticky-top">
|
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<h2 data-toc-skip>Contents</h2>
|
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<nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2>
|
||||
</nav>
|
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</div>
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<footer>
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<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/'>Alexander 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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<footer><div class="copyright">
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<p></p>
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<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link">Corinna Glasner</a>.</p>
|
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</div>
|
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|
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<div class="pkgdown">
|
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<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
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<p></p>
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 1.6.1.9001.</p>
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</footer>
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||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
|
||||
+29
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@@ -54,6 +54,8 @@
|
||||
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||||
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||||
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|
||||
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||||
<!-- mathjax -->
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
|
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<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
|
||||
@@ -65,9 +67,15 @@
|
||||
|
||||
|
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|
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|
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|
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</head>
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<body data-spy="scroll" data-target="#toc">
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<div class="container template-title-body">
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<header>
|
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<div class="navbar navbar-default navbar-fixed-top" role="navigation">
|
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@@ -81,7 +89,7 @@
|
||||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
|
||||
</div>
|
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|
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@@ -89,14 +97,14 @@
|
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<ul class="nav navbar-nav">
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<li>
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<a href="index.html">
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<span class="fas fa-home"></span>
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<span class="fa fa-home"></span>
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Home
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</a>
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</li>
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<li class="dropdown">
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
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<span class="fas fa-question-circle"></span>
|
||||
<span class="fa fa-question-circle"></span>
|
||||
|
||||
How to
|
||||
|
||||
@@ -105,77 +113,77 @@
|
||||
<ul class="dropdown-menu" role="menu">
|
||||
<li>
|
||||
<a href="articles/AMR.html">
|
||||
<span class="fas fa-directions"></span>
|
||||
<span class="fa fa-directions"></span>
|
||||
|
||||
Conduct AMR analysis
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
||||
<span class="fa fa-dice"></span>
|
||||
|
||||
Predict antimicrobial resistance
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/datasets.html">
|
||||
<span class="fas fa-database"></span>
|
||||
<span class="fa fa-database"></span>
|
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|
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Data sets for download / own use
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
||||
Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
||||
<span class="fa fa-skull-crossbones"></span>
|
||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/WHONET.html">
|
||||
<span class="fas fa-globe-americas"></span>
|
||||
<span class="fa fa-globe-americas"></span>
|
||||
|
||||
Work with WHONET data
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/SPSS.html">
|
||||
<span class="fas fa-file-upload"></span>
|
||||
<span class="fa fa-file-upload"></span>
|
||||
|
||||
Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/EUCAST.html">
|
||||
<span class="fas fa-exchange-alt"></span>
|
||||
<span class="fa fa-exchange-alt"></span>
|
||||
|
||||
Apply EUCAST rules
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
||||
<span class="fa fa-bug"></span>
|
||||
|
||||
Get properties of a microorganism
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="reference/ab_property.html">
|
||||
<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
||||
|
||||
Get properties of an antibiotic
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/benchmarks.html">
|
||||
<span class="fas fa-shipping-fast"></span>
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -184,14 +192,14 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
||||
<span class="fa fa-book-open"></span>
|
||||
|
||||
Manual
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
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|
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Authors
|
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</a>
|
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@@ -214,7 +222,7 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
||||
<span class="fa fa-clipboard-list"></span>
|
||||
|
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Survey
|
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</a>
|
||||
@@ -499,11 +507,11 @@ END OF TERMS AND CONDITIONS
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<footer>
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<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/'>Alexander 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>
|
||||
<p><p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link">Corinna Glasner</a>.</p></p>
|
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</div>
|
||||
|
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<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
||||
<p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 1.6.1.9001.</p></p>
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</div>
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</footer>
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@@ -512,6 +520,8 @@ END OF TERMS AND CONDITIONS
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|
||||
// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
|
||||
// be compatible with the behavior of Pandoc < 2.8).
|
||||
document.addEventListener('DOMContentLoaded', function(e) {
|
||||
var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
|
||||
var i, h, a;
|
||||
for (i = 0; i < hs.length; i++) {
|
||||
h = hs[i];
|
||||
if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6
|
||||
a = h.attributes;
|
||||
while (a.length > 0) h.removeAttribute(a[0].name);
|
||||
}
|
||||
});
|
||||
+36
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|
||||
<![endif]-->
|
||||
</head>
|
||||
<body data-spy="scroll" data-target="#toc">
|
||||
|
||||
|
||||
<div class="container template-article">
|
||||
<header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
|
||||
<div class="container">
|
||||
@@ -39,7 +41,7 @@
|
||||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
@@ -47,14 +49,14 @@
|
||||
<ul class="nav navbar-nav">
|
||||
<li>
|
||||
<a href="../index.html">
|
||||
<span class="fas fa-home"></span>
|
||||
<span class="fa fa-home"></span>
|
||||
|
||||
Home
|
||||
</a>
|
||||
</li>
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
|
||||
<span class="fas fa-question-circle"></span>
|
||||
<span class="fa fa-question-circle"></span>
|
||||
|
||||
How to
|
||||
|
||||
@@ -63,77 +65,77 @@
|
||||
<ul class="dropdown-menu" role="menu">
|
||||
<li>
|
||||
<a href="../articles/AMR.html">
|
||||
<span class="fas fa-directions"></span>
|
||||
<span class="fa fa-directions"></span>
|
||||
|
||||
Conduct AMR analysis
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
||||
<span class="fa fa-dice"></span>
|
||||
|
||||
Predict antimicrobial resistance
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/datasets.html">
|
||||
<span class="fas fa-database"></span>
|
||||
<span class="fa fa-database"></span>
|
||||
|
||||
Data sets for download / own use
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
||||
Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
||||
<span class="fa fa-skull-crossbones"></span>
|
||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/WHONET.html">
|
||||
<span class="fas fa-globe-americas"></span>
|
||||
<span class="fa fa-globe-americas"></span>
|
||||
|
||||
Work with WHONET data
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/SPSS.html">
|
||||
<span class="fas fa-file-upload"></span>
|
||||
<span class="fa fa-file-upload"></span>
|
||||
|
||||
Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/EUCAST.html">
|
||||
<span class="fas fa-exchange-alt"></span>
|
||||
<span class="fa fa-exchange-alt"></span>
|
||||
|
||||
Apply EUCAST rules
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
||||
<span class="fa fa-bug"></span>
|
||||
|
||||
Get properties of a microorganism
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/ab_property.html">
|
||||
<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
||||
|
||||
Get properties of an antibiotic
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/benchmarks.html">
|
||||
<span class="fas fa-shipping-fast"></span>
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -142,14 +144,14 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
||||
<span class="fa fa-book-open"></span>
|
||||
|
||||
Manual
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
||||
|
||||
Authors
|
||||
</a>
|
||||
@@ -164,7 +166,7 @@
|
||||
</ul>
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li>
|
||||
<a href="https://github.com/msberends/AMR">
|
||||
<a href="https://github.com/msberends/AMR" class="external-link">
|
||||
<span class="fab fa-github"></span>
|
||||
|
||||
Source Code
|
||||
@@ -172,7 +174,7 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
||||
<span class="fa fa-clipboard-list"></span>
|
||||
|
||||
Survey
|
||||
</a>
|
||||
@@ -187,13 +189,13 @@
|
||||
|
||||
|
||||
|
||||
</header><script src="EUCAST_files/header-attrs-2.8/header-attrs.js"></script><div class="row">
|
||||
</header><script src="EUCAST_files/header-attrs-2.9/header-attrs.js"></script><div class="row">
|
||||
<div class="col-md-9 contents">
|
||||
<div class="page-header toc-ignore">
|
||||
<h1 data-toc-skip>How to apply EUCAST rules</h1>
|
||||
|
||||
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/EUCAST.Rmd"><code>vignettes/EUCAST.Rmd</code></a></small>
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/EUCAST.Rmd" class="external-link"><code>vignettes/EUCAST.Rmd</code></a></small>
|
||||
<div class="hidden name"><code>EUCAST.Rmd</code></div>
|
||||
|
||||
</div>
|
||||
@@ -202,21 +204,21 @@
|
||||
|
||||
<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="https://www.eucast.org/expert_rules_and_intrinsic_resistance/">on their website</a>:</p>
|
||||
<a href="#introduction" class="anchor" aria-hidden="true"></a>Introduction</h2>
|
||||
<p>What are EUCAST rules? The European Committee on Antimicrobial Susceptibility Testing (EUCAST) states <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/" class="external-link">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 unusual phenotypes (v3.2, 2020).</p>
|
||||
<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" class="external-link">Brown <em>et al.</em>, 2015</a>). Our package features their latest insights on intrinsic resistance and unusual phenotypes (v3.2, 2020).</p>
|
||||
<p>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>
|
||||
</div>
|
||||
<div id="examples" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#examples" class="anchor"></a>Examples</h2>
|
||||
<a href="#examples" class="anchor" aria-hidden="true"></a>Examples</h2>
|
||||
<p>These rules can be used to discard impossible bug-drug combinations in your data. For example, <em>Klebsiella</em> produces beta-lactamase that prevents ampicillin (or amoxicillin) from working against it. In other words, practically every strain of <em>Klebsiella</em> is resistant to ampicillin.</p>
|
||||
<p>Sometimes, laboratory data can still contain such strains with ampicillin being susceptible to ampicillin. This could be because an antibiogram is available before an identification is available, and the antibiogram is then not re-interpreted based on the identification (namely, <em>Klebsiella</em>). EUCAST expert rules solve this, that can be applied using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:</p>
|
||||
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">oops</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>,
|
||||
<code class="sourceCode R"><span class="va">oops</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>,
|
||||
<span class="st">"Escherichia"</span><span class="op">)</span>,
|
||||
ampicillin <span class="op">=</span> <span class="st">"S"</span><span class="op">)</span>
|
||||
<span class="va">oops</span>
|
||||
@@ -230,16 +232,16 @@
|
||||
<span class="co"># 2 Escherichia S</span></code></pre></div>
|
||||
<p>A more convenient function is <code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> that uses the same guideline, but allows to check for one or more specific microorganisms or antibiotics:</p>
|
||||
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <span class="st">"Escherichia"</span><span class="op">)</span>,
|
||||
<code class="sourceCode R"><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <span class="st">"Escherichia"</span><span class="op">)</span>,
|
||||
<span class="st">"ampicillin"</span><span class="op">)</span>
|
||||
<span class="co"># [1] TRUE FALSE</span>
|
||||
|
||||
<span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>,
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"ampicillin"</span>, <span class="st">"kanamycin"</span><span class="op">)</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"ampicillin"</span>, <span class="st">"kanamycin"</span><span class="op">)</span><span class="op">)</span>
|
||||
<span class="co"># [1] TRUE FALSE</span></code></pre></div>
|
||||
<p>EUCAST rules can not only be used for correction, they can also be used for filling in known resistance and susceptibility based on results of other antimicrobials drugs. This process is called <em>interpretive reading</em>, is basically a form of imputation, and is part of the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function as well:</p>
|
||||
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">data</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span>,
|
||||
<code class="sourceCode R"><span class="va">data</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span>,
|
||||
<span class="st">"Enterococcus faecalis"</span>,
|
||||
<span class="st">"Escherichia coli"</span>,
|
||||
<span class="st">"Klebsiella pneumoniae"</span>,
|
||||
@@ -398,11 +400,13 @@
|
||||
|
||||
|
||||
<footer><div class="copyright">
|
||||
<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/">Alexander 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>
|
||||
<p></p>
|
||||
<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link external-link">Corinna Glasner</a>.</p>
|
||||
</div>
|
||||
|
||||
<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
||||
<p></p>
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link external-link">pkgdown</a> 1.6.1.9001.</p>
|
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|
||||
|
||||
</footer>
|
||||
@@ -411,5 +415,7 @@
|
||||
|
||||
|
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|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -0,0 +1,12 @@
|
||||
// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
|
||||
// be compatible with the behavior of Pandoc < 2.8).
|
||||
document.addEventListener('DOMContentLoaded', function(e) {
|
||||
var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
|
||||
var i, h, a;
|
||||
for (i = 0; i < hs.length; i++) {
|
||||
h = hs[i];
|
||||
if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6
|
||||
a = h.attributes;
|
||||
while (a.length > 0) h.removeAttribute(a[0].name);
|
||||
}
|
||||
});
|
||||
+119
-81
@@ -27,6 +27,8 @@
|
||||
<![endif]-->
|
||||
</head>
|
||||
<body data-spy="scroll" data-target="#toc">
|
||||
|
||||
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||||
<div class="container template-article">
|
||||
<header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
|
||||
<div class="container">
|
||||
@@ -39,7 +41,7 @@
|
||||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
@@ -47,14 +49,14 @@
|
||||
<ul class="nav navbar-nav">
|
||||
<li>
|
||||
<a href="../index.html">
|
||||
<span class="fas fa-home"></span>
|
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<span class="fa fa-home"></span>
|
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|
||||
Home
|
||||
</a>
|
||||
</li>
|
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<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
|
||||
<span class="fas fa-question-circle"></span>
|
||||
<span class="fa fa-question-circle"></span>
|
||||
|
||||
How to
|
||||
|
||||
@@ -63,77 +65,77 @@
|
||||
<ul class="dropdown-menu" role="menu">
|
||||
<li>
|
||||
<a href="../articles/AMR.html">
|
||||
<span class="fas fa-directions"></span>
|
||||
<span class="fa fa-directions"></span>
|
||||
|
||||
Conduct AMR analysis
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
||||
<span class="fa fa-dice"></span>
|
||||
|
||||
Predict antimicrobial resistance
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/datasets.html">
|
||||
<span class="fas fa-database"></span>
|
||||
<span class="fa fa-database"></span>
|
||||
|
||||
Data sets for download / own use
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
||||
Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
||||
<span class="fa fa-skull-crossbones"></span>
|
||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/WHONET.html">
|
||||
<span class="fas fa-globe-americas"></span>
|
||||
<span class="fa fa-globe-americas"></span>
|
||||
|
||||
Work with WHONET data
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/SPSS.html">
|
||||
<span class="fas fa-file-upload"></span>
|
||||
<span class="fa fa-file-upload"></span>
|
||||
|
||||
Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/EUCAST.html">
|
||||
<span class="fas fa-exchange-alt"></span>
|
||||
<span class="fa fa-exchange-alt"></span>
|
||||
|
||||
Apply EUCAST rules
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
||||
<span class="fa fa-bug"></span>
|
||||
|
||||
Get properties of a microorganism
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/ab_property.html">
|
||||
<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
||||
|
||||
Get properties of an antibiotic
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/benchmarks.html">
|
||||
<span class="fas fa-shipping-fast"></span>
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -142,14 +144,14 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
||||
<span class="fa fa-book-open"></span>
|
||||
|
||||
Manual
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
||||
|
||||
Authors
|
||||
</a>
|
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@@ -164,7 +166,7 @@
|
||||
</ul>
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li>
|
||||
<a href="https://github.com/msberends/AMR">
|
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<a href="https://github.com/msberends/AMR" class="external-link">
|
||||
<span class="fab fa-github"></span>
|
||||
|
||||
Source Code
|
||||
@@ -172,7 +174,7 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
||||
<span class="fa fa-clipboard-list"></span>
|
||||
|
||||
Survey
|
||||
</a>
|
||||
@@ -187,13 +189,13 @@
|
||||
|
||||
|
||||
|
||||
</header><script src="MDR_files/header-attrs-2.8/header-attrs.js"></script><div class="row">
|
||||
</header><script src="MDR_files/header-attrs-2.9/header-attrs.js"></script><div class="row">
|
||||
<div class="col-md-9 contents">
|
||||
<div class="page-header toc-ignore">
|
||||
<h1 data-toc-skip>How to determine multi-drug resistance (MDR)</h1>
|
||||
|
||||
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/MDR.Rmd"><code>vignettes/MDR.Rmd</code></a></small>
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/MDR.Rmd" class="external-link"><code>vignettes/MDR.Rmd</code></a></small>
|
||||
<div class="hidden name"><code>MDR.Rmd</code></div>
|
||||
|
||||
</div>
|
||||
@@ -203,50 +205,50 @@
|
||||
<p>With the function <code><a href="../reference/mdro.html">mdro()</a></code>, you can determine which micro-organisms are multi-drug resistant organisms (MDRO).</p>
|
||||
<div id="type-of-input" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#type-of-input" class="anchor"></a>Type of input</h3>
|
||||
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function takes a data set as input, such as a regular <code>data.frame</code>. It tries to automatically determine the right columns for info about your isolates, like the name of the species and all columns with results of antimicrobial agents. See the help page for more info about how to set the right settings for your data with the command <code><a href="../reference/mdro.html">?mdro</a></code>.</p>
|
||||
<a href="#type-of-input" class="anchor" aria-hidden="true"></a>Type of input</h3>
|
||||
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function takes a data set as input, such as a regular <code>data.frame</code>. It tries to automatically determine the right columns for info about your isolates, such as the name of the species and all columns with results of antimicrobial agents. See the help page for more info about how to set the right settings for your data with the command <code><a href="../reference/mdro.html">?mdro</a></code>.</p>
|
||||
<p>For WHONET data (and most other data), all settings are automatically set correctly.</p>
|
||||
</div>
|
||||
<div id="guidelines" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#guidelines" class="anchor"></a>Guidelines</h3>
|
||||
<p>The function support multiple guidelines. You can select a guideline with the <code>guideline</code> parameter. Currently supported guidelines are (case-insensitive):</p>
|
||||
<a href="#guidelines" class="anchor" aria-hidden="true"></a>Guidelines</h3>
|
||||
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function support multiple guidelines. You can select a guideline with the <code>guideline</code> parameter. Currently supported guidelines are (case-insensitive):</p>
|
||||
<ul>
|
||||
<li>
|
||||
<p><code>guideline = "CMI2012"</code> (default)</p>
|
||||
<p>Magiorakos AP, Srinivasan A <em>et al.</em> “Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.” Clinical Microbiology and Infection (2012) (<a href="https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61632-3/fulltext">link</a>)</p>
|
||||
<p>Magiorakos AP, Srinivasan A <em>et al.</em> “Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.” Clinical Microbiology and Infection (2012) (<a href="https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61632-3/fulltext" class="external-link">link</a>)</p>
|
||||
</li>
|
||||
<li>
|
||||
<p><code>guideline = "EUCAST3.2"</code> (or simply <code>guideline = "EUCAST"</code>)</p>
|
||||
<p>The European international guideline - EUCAST Expert Rules Version 3.2 “Intrinsic Resistance and Unusual Phenotypes” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf">link</a>)</p>
|
||||
<p>The European international guideline - EUCAST Expert Rules Version 3.2 “Intrinsic Resistance and Unusual Phenotypes” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf" class="external-link">link</a>)</p>
|
||||
</li>
|
||||
<li>
|
||||
<p><code>guideline = "EUCAST3.1"</code></p>
|
||||
<p>The European international guideline - EUCAST Expert Rules Version 3.1 “Intrinsic Resistance and Exceptional Phenotypes Tables” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf">link</a>)</p>
|
||||
<p>The European international guideline - EUCAST Expert Rules Version 3.1 “Intrinsic Resistance and Exceptional Phenotypes Tables” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf" class="external-link">link</a>)</p>
|
||||
</li>
|
||||
<li>
|
||||
<p><code>guideline = "TB"</code></p>
|
||||
<p>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” (<a href="https://www.who.int/tb/publications/pmdt_companionhandbook/en/">link</a>)</p>
|
||||
<p>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” (<a href="https://www.who.int/tb/publications/pmdt_companionhandbook/en/" class="external-link">link</a>)</p>
|
||||
</li>
|
||||
<li>
|
||||
<p><code>guideline = "MRGN"</code></p>
|
||||
<p>The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7. DOI: 10.1186/s13756-015-0047-6</p>
|
||||
<p>The German national guideline - Mueller <em>et al.</em> (2015) Antimicrobial Resistance and Infection Control 4:7. DOI: 10.1186/s13756-015-0047-6</p>
|
||||
</li>
|
||||
<li>
|
||||
<p><code>guideline = "BRMO"</code></p>
|
||||
<p>The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu “WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)” (<a href="https://www.rivm.nl/wip-richtlijn-brmo-bijzonder-resistente-micro-organismen-zkh">link</a>)</p>
|
||||
<p>The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu “WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)” (<a href="https://www.rivm.nl/wip-richtlijn-brmo-bijzonder-resistente-micro-organismen-zkh" class="external-link">link</a>)</p>
|
||||
</li>
|
||||
</ul>
|
||||
<p>Please suggest your own (country-specific) guidelines by letting us know: <a href="https://github.com/msberends/AMR/issues/new" class="uri">https://github.com/msberends/AMR/issues/new</a>.</p>
|
||||
<p>Please suggest your own (country-specific) guidelines by letting us know: <a href="https://github.com/msberends/AMR/issues/new" class="external-link uri">https://github.com/msberends/AMR/issues/new</a>.</p>
|
||||
<div id="custom-guidelines" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#custom-guidelines" class="anchor"></a>Custom Guidelines</h4>
|
||||
<a href="#custom-guidelines" class="anchor" aria-hidden="true"></a>Custom Guidelines</h4>
|
||||
<p>You can also use your own custom guideline. Custom guidelines can be set with the <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code> function. This is of great importance if you have custom rules to determine MDROs in your hospital, e.g., rules that are dependent on ward, state of contact isolation or other variables in your data.</p>
|
||||
<p>If you are familiar with <code><a href="https://dplyr.tidyverse.org/reference/case_when.html">case_when()</a></code> of the <code>dplyr</code> package, you will recognise the input method to set your own rules. Rules must be set using what considers to be the ‘formula notation’:</p>
|
||||
<p>If you are familiar with <code><a href="https://dplyr.tidyverse.org/reference/case_when.html" class="external-link">case_when()</a></code> of the <code>dplyr</code> package, you will recognise the input method to set your own rules. Rules must be set using what R considers to be the ‘formula notation’:</p>
|
||||
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">custom</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mdro.html">custom_mdro_guideline</a></span><span class="op">(</span><span class="va">CIP</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&</span> <span class="va">age</span> <span class="op">></span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type A"</span>,
|
||||
<span class="va">ERY</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&</span> <span class="va">age</span> <span class="op">></span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type B"</span><span class="op">)</span></code></pre></div>
|
||||
<p>If a row/an isolate matches the first rule, the value after the first <code><a href="https://rdrr.io/r/base/tilde.html">~</a></code> (in this case <em>‘Elderly Type A’</em>) will be set as MDRO value. Otherwise, the second rule will be tried and so on. The number of rules is unlimited.</p>
|
||||
<p>If a row/an isolate matches the first rule, the value after the first <code><a href="https://rdrr.io/r/base/tilde.html" class="external-link">~</a></code> (in this case <em>‘Elderly Type A’</em>) will be set as MDRO value. Otherwise, the second rule will be tried and so on. The maximum number of rules is unlimited.</p>
|
||||
<p>You can print the rules set in the console for an overview. Colours will help reading it if your console supports colours.</p>
|
||||
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">custom</span>
|
||||
@@ -257,30 +259,50 @@
|
||||
<span class="co"># </span>
|
||||
<span class="co"># Unmatched rows will return NA.</span>
|
||||
<span class="co"># Results will be of class <factor>, with ordered levels: Negative < Elderly Type A < Elderly Type B</span></code></pre></div>
|
||||
<p>The outcome of the function can be used for the <code>guideline</code> argument in the [mdro()] function:</p>
|
||||
<p>The outcome of the function can be used for the <code>guideline</code> argument in the <code><a href="../reference/mdro.html">mdro()</a></code> function:</p>
|
||||
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">x</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">example_isolates</span>, guideline <span class="op">=</span> <span class="va">custom</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/table.html">table</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
|
||||
<span class="co"># Determining MDROs based on custom rules, resulting in [factor] levels:</span>
|
||||
<span class="co"># Negative < Elderly Type A < Elderly Type B.</span>
|
||||
<span class="co"># - Custom MDRO rule 1: `CIP == "R" & age > 60` (198 rows matched)</span>
|
||||
<span class="co"># - Custom MDRO rule 2: `ERY == "R" & age > 60` (732 rows matched)</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/table.html" class="external-link">table</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
|
||||
<span class="co"># x</span>
|
||||
<span class="co"># Negative Elderly Type A Elderly Type B </span>
|
||||
<span class="co"># 1070 198 732</span></code></pre></div>
|
||||
<p>The rules set (the <code>custom</code> object in this case) could be exported to a shared file location using <code><a href="https://rdrr.io/r/base/readRDS.html">saveRDS()</a></code> if you collaborate with multiple users. The custom rules set could then be imported using <code><a href="https://rdrr.io/r/base/readRDS.html">readRDS()</a></code>.</p>
|
||||
<p>The rules set (the <code>custom</code> object in this case) could be exported to a shared file location using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">saveRDS()</a></code> if you collaborate with multiple users. The custom rules set could then be imported using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">readRDS()</a></code>.</p>
|
||||
</div>
|
||||
</div>
|
||||
<div id="examples" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#examples" class="anchor"></a>Examples</h3>
|
||||
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function always returns an ordered <code>factor</code>. For example, the output of the default guideline by Magiorakos <em>et al.</em> returns a <code>factor</code> with levels ‘Negative’, ‘MDR’, ‘XDR’ or ‘PDR’ in that order.</p>
|
||||
<p>The next example uses the <code>example_isolates</code> data set. This is a data set included with this package and contains 2,000 microbial isolates with their full antibiograms. It reflects reality and can be used to practice AMR data analysis. If we test the MDR/XDR/PDR guideline on this data set, we get:</p>
|
||||
<a href="#examples" class="anchor" aria-hidden="true"></a>Examples</h3>
|
||||
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function always returns an ordered <code>factor</code> for predefined guidelines. For example, the output of the default guideline by Magiorakos <em>et al.</em> returns a <code>factor</code> with levels ‘Negative’, ‘MDR’, ‘XDR’ or ‘PDR’ in that order.</p>
|
||||
<p>The next example uses the <code>example_isolates</code> data set. This is a data set included with this package and contains full antibiograms of 2,000 microbial isolates. It reflects reality and can be used to practise AMR data analysis. If we test the MDR/XDR/PDR guideline on this data set, we get:</p>
|
||||
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span> <span class="co"># to support pipes: %>%</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div>
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <span class="co"># to support pipes: %>%</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner" class="external-link">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div>
|
||||
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">example_isolates</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="op">)</span> <span class="co"># show frequency table of the result</span>
|
||||
<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="op">)</span> <span class="co"># show frequency table of the result</span>
|
||||
<span class="co"># ℹ Using column 'mo' as input for `col_mo`.</span>
|
||||
<span class="co"># Auto-guessing columns suitable for analysis... OK.</span>
|
||||
<span class="co"># ℹ Reliability would be improved if these antimicrobial results would be</span>
|
||||
<span class="co"># available too: ampicillin/sulbactam (SAM), aztreonam (ATM), cefotetan</span>
|
||||
<span class="co"># (CTT), ceftaroline (CPT), daptomycin (DAP), doripenem (DOR), ertapenem</span>
|
||||
<span class="co"># (ETP), fusidic acid (FUS), gentamicin-high (GEH), levofloxacin (LVX),</span>
|
||||
<span class="co"># minocycline (MNO), netilmicin (NET), polymyxin B (PLB),</span>
|
||||
<span class="co"># quinupristin/dalfopristin (QDA), streptomycin-high (STH), telavancin (TLV)</span>
|
||||
<span class="co"># and ticarcillin/clavulanic acid (TCC)</span>
|
||||
<span class="co"># Table 1 - Staphylococcus aureus... OK.</span>
|
||||
<span class="co"># Table 2 - Enterococcus spp.... OK.</span>
|
||||
<span class="co"># Table 3 - Enterobacteriaceae... OK.</span>
|
||||
<span class="co"># Table 4 - Pseudomonas aeruginosa... OK.</span>
|
||||
<span class="co"># Table 5 - Acinetobacter spp.... OK.</span>
|
||||
<span class="co"># Warning: NA introduced for isolates where the available percentage of antimicrobial</span>
|
||||
<span class="co"># classes was below 50% (set with `pct_required_classes`)</span></code></pre></div>
|
||||
<p>Only results with ‘R’ are considered as resistance. Use <code>combine_SI = FALSE</code> to also consider ‘I’ as resistance.</p>
|
||||
<p>Determining multidrug-resistant organisms (MDRO), according to: Guideline: Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Author(s): Magiorakos AP, Srinivasan A, Carey RB, …, Vatopoulos A, Weber JT, Monnet DL Source: Clinical Microbiology and Infection 18:3, 2012; doi: 10.1111/j.1469-0691.2011.03570.x</p>
|
||||
<p><strong>Frequency table</strong></p>
|
||||
<p>Class: factor > ordered (numeric)<br>
|
||||
Length: 2,000<br>
|
||||
@@ -319,16 +341,16 @@ Unique: 2</p>
|
||||
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># random_rsi() is a helper function to generate</span>
|
||||
<span class="co"># a random vector with values S, I and R</span>
|
||||
<span class="va">my_TB_data</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>rifampicin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
<span class="va">my_TB_data</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>rifampicin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
isoniazid <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
gatifloxacin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
ethambutol <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
pyrazinamide <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
moxifloxacin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
kanamycin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span><span class="op">)</span></code></pre></div>
|
||||
<p>Because all column names are automatically verified for valid drug names or codes, this would have worked exactly the same:</p>
|
||||
<p>Because all column names are automatically verified for valid drug names or codes, this would have worked exactly the same way:</p>
|
||||
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">my_TB_data</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>RIF <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
<code class="sourceCode R"><span class="va">my_TB_data</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>RIF <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
INH <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
GAT <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
ETH <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
|
||||
@@ -337,21 +359,21 @@ Unique: 2</p>
|
||||
KAN <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span><span class="op">)</span></code></pre></div>
|
||||
<p>The data set now looks like this:</p>
|
||||
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span>
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span>
|
||||
<span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span>
|
||||
<span class="co"># 1 S I R R R S</span>
|
||||
<span class="co"># 2 I R R R R R</span>
|
||||
<span class="co"># 3 S S S R I R</span>
|
||||
<span class="co"># 4 R I R R S S</span>
|
||||
<span class="co"># 5 I R S S R I</span>
|
||||
<span class="co"># 6 I S S R R R</span>
|
||||
<span class="co"># 1 I S S R I S</span>
|
||||
<span class="co"># 2 R R R R S R</span>
|
||||
<span class="co"># 3 R R R I S S</span>
|
||||
<span class="co"># 4 R S I R R R</span>
|
||||
<span class="co"># 5 R S S S I R</span>
|
||||
<span class="co"># 6 S I S S S I</span>
|
||||
<span class="co"># kanamycin</span>
|
||||
<span class="co"># 1 I</span>
|
||||
<span class="co"># 2 R</span>
|
||||
<span class="co"># 3 R</span>
|
||||
<span class="co"># 4 R</span>
|
||||
<span class="co"># 5 S</span>
|
||||
<span class="co"># 6 S</span></code></pre></div>
|
||||
<span class="co"># 1 S</span>
|
||||
<span class="co"># 2 S</span>
|
||||
<span class="co"># 3 I</span>
|
||||
<span class="co"># 4 S</span>
|
||||
<span class="co"># 5 I</span>
|
||||
<span class="co"># 6 I</span></code></pre></div>
|
||||
<p>We can now add the interpretation of MDR-TB to our data set. You can use:</p>
|
||||
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">my_TB_data</span>, guideline <span class="op">=</span> <span class="st">"TB"</span><span class="op">)</span></code></pre></div>
|
||||
@@ -359,10 +381,22 @@ Unique: 2</p>
|
||||
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">my_TB_data</span><span class="op">$</span><span class="va">mdr</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mdro.html">mdr_tb</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span>
|
||||
<span class="co"># ℹ No column found as input for `col_mo`, assuming all rows contain</span>
|
||||
<span class="co"># Mycobacterium tuberculosis.</span></code></pre></div>
|
||||
<span class="co"># Mycobacterium tuberculosis.</span>
|
||||
<span class="co"># Auto-guessing columns suitable for analysis... OK.</span>
|
||||
<span class="co"># ℹ Reliability would be improved if these antimicrobial results would be</span>
|
||||
<span class="co"># available too: capreomycin (CAP), rifabutin (RIB) and rifapentine (RFP)</span>
|
||||
<span class="co"># </span>
|
||||
<span class="co"># Only results with 'R' are considered as resistance. Use `combine_SI = FALSE` to also consider 'I' as resistance.</span>
|
||||
<span class="co"># </span>
|
||||
<span class="co"># Determining multidrug-resistant organisms (MDRO), according to:</span>
|
||||
<span class="co"># Guideline: Companion handbook to the WHO guidelines for the programmatic</span>
|
||||
<span class="co"># management of drug-resistant tuberculosis</span>
|
||||
<span class="co"># Author(s): WHO (World Health Organization)</span>
|
||||
<span class="co"># Version: WHO/HTM/TB/2014.11, 2014</span>
|
||||
<span class="co"># Source: https://www.who.int/tb/publications/pmdt_companionhandbook/en/</span></code></pre></div>
|
||||
<p>Create a frequency table of the results:</p>
|
||||
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">$</span><span class="va">mdr</span><span class="op">)</span></code></pre></div>
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">$</span><span class="va">mdr</span><span class="op">)</span></code></pre></div>
|
||||
<p><strong>Frequency table</strong></p>
|
||||
<p>Class: factor > ordered (numeric)<br>
|
||||
Length: 5,000<br>
|
||||
@@ -382,40 +416,40 @@ Unique: 5</p>
|
||||
<tr class="odd">
|
||||
<td align="left">1</td>
|
||||
<td align="left">Mono-resistant</td>
|
||||
<td align="right">3187</td>
|
||||
<td align="right">63.74%</td>
|
||||
<td align="right">3187</td>
|
||||
<td align="right">63.74%</td>
|
||||
<td align="right">3175</td>
|
||||
<td align="right">63.50%</td>
|
||||
<td align="right">3175</td>
|
||||
<td align="right">63.50%</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">2</td>
|
||||
<td align="left">Negative</td>
|
||||
<td align="right">1027</td>
|
||||
<td align="right">20.54%</td>
|
||||
<td align="right">4214</td>
|
||||
<td align="right">84.28%</td>
|
||||
<td align="right">1014</td>
|
||||
<td align="right">20.28%</td>
|
||||
<td align="right">4189</td>
|
||||
<td align="right">83.78%</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left">3</td>
|
||||
<td align="left">Multi-drug-resistant</td>
|
||||
<td align="right">430</td>
|
||||
<td align="right">8.60%</td>
|
||||
<td align="right">4644</td>
|
||||
<td align="right">92.88%</td>
|
||||
<td align="right">445</td>
|
||||
<td align="right">8.90%</td>
|
||||
<td align="right">4634</td>
|
||||
<td align="right">92.68%</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">4</td>
|
||||
<td align="left">Poly-resistant</td>
|
||||
<td align="right">245</td>
|
||||
<td align="right">4.90%</td>
|
||||
<td align="right">4889</td>
|
||||
<td align="right">97.78%</td>
|
||||
<td align="right">272</td>
|
||||
<td align="right">5.44%</td>
|
||||
<td align="right">4906</td>
|
||||
<td align="right">98.12%</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left">5</td>
|
||||
<td align="left">Extensively drug-resistant</td>
|
||||
<td align="right">111</td>
|
||||
<td align="right">2.22%</td>
|
||||
<td align="right">94</td>
|
||||
<td align="right">1.88%</td>
|
||||
<td align="right">5000</td>
|
||||
<td align="right">100.00%</td>
|
||||
</tr>
|
||||
@@ -433,11 +467,13 @@ Unique: 5</p>
|
||||
|
||||
|
||||
<footer><div class="copyright">
|
||||
<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/">Alexander 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>
|
||||
<p></p>
|
||||
<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link external-link">Corinna Glasner</a>.</p>
|
||||
</div>
|
||||
|
||||
<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
||||
<p></p>
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link external-link">pkgdown</a> 1.6.1.9001.</p>
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</div>
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||||
|
||||
</footer>
|
||||
@@ -446,5 +482,7 @@ Unique: 5</p>
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||||
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||||
|
||||
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -0,0 +1,12 @@
|
||||
// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
|
||||
// be compatible with the behavior of Pandoc < 2.8).
|
||||
document.addEventListener('DOMContentLoaded', function(e) {
|
||||
var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
|
||||
var i, h, a;
|
||||
for (i = 0; i < hs.length; i++) {
|
||||
h = hs[i];
|
||||
if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6
|
||||
a = h.attributes;
|
||||
while (a.length > 0) h.removeAttribute(a[0].name);
|
||||
}
|
||||
});
|
||||
+44
-38
@@ -27,6 +27,8 @@
|
||||
<![endif]-->
|
||||
</head>
|
||||
<body data-spy="scroll" data-target="#toc">
|
||||
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||||
|
||||
<div class="container template-article">
|
||||
<header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
|
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<div class="container">
|
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@@ -39,7 +41,7 @@
|
||||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
@@ -47,14 +49,14 @@
|
||||
<ul class="nav navbar-nav">
|
||||
<li>
|
||||
<a href="../index.html">
|
||||
<span class="fas fa-home"></span>
|
||||
<span class="fa fa-home"></span>
|
||||
|
||||
Home
|
||||
</a>
|
||||
</li>
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
|
||||
<span class="fas fa-question-circle"></span>
|
||||
<span class="fa fa-question-circle"></span>
|
||||
|
||||
How to
|
||||
|
||||
@@ -63,77 +65,77 @@
|
||||
<ul class="dropdown-menu" role="menu">
|
||||
<li>
|
||||
<a href="../articles/AMR.html">
|
||||
<span class="fas fa-directions"></span>
|
||||
<span class="fa fa-directions"></span>
|
||||
|
||||
Conduct AMR analysis
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
||||
<span class="fa fa-dice"></span>
|
||||
|
||||
Predict antimicrobial resistance
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/datasets.html">
|
||||
<span class="fas fa-database"></span>
|
||||
<span class="fa fa-database"></span>
|
||||
|
||||
Data sets for download / own use
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
||||
Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
||||
<span class="fa fa-skull-crossbones"></span>
|
||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/WHONET.html">
|
||||
<span class="fas fa-globe-americas"></span>
|
||||
<span class="fa fa-globe-americas"></span>
|
||||
|
||||
Work with WHONET data
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/SPSS.html">
|
||||
<span class="fas fa-file-upload"></span>
|
||||
<span class="fa fa-file-upload"></span>
|
||||
|
||||
Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/EUCAST.html">
|
||||
<span class="fas fa-exchange-alt"></span>
|
||||
<span class="fa fa-exchange-alt"></span>
|
||||
|
||||
Apply EUCAST rules
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
||||
<span class="fa fa-bug"></span>
|
||||
|
||||
Get properties of a microorganism
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/ab_property.html">
|
||||
<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
||||
|
||||
Get properties of an antibiotic
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/benchmarks.html">
|
||||
<span class="fas fa-shipping-fast"></span>
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -142,14 +144,14 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
||||
<span class="fa fa-book-open"></span>
|
||||
|
||||
Manual
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
||||
|
||||
Authors
|
||||
</a>
|
||||
@@ -164,7 +166,7 @@
|
||||
</ul>
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li>
|
||||
<a href="https://github.com/msberends/AMR">
|
||||
<a href="https://github.com/msberends/AMR" class="external-link">
|
||||
<span class="fab fa-github"></span>
|
||||
|
||||
Source Code
|
||||
@@ -172,7 +174,7 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
||||
<span class="fa fa-clipboard-list"></span>
|
||||
|
||||
Survey
|
||||
</a>
|
||||
@@ -187,13 +189,13 @@
|
||||
|
||||
|
||||
|
||||
</header><script src="PCA_files/header-attrs-2.8/header-attrs.js"></script><div class="row">
|
||||
</header><script src="PCA_files/header-attrs-2.9/header-attrs.js"></script><div class="row">
|
||||
<div class="col-md-9 contents">
|
||||
<div class="page-header toc-ignore">
|
||||
<h1 data-toc-skip>How to conduct principal component analysis (PCA) for AMR</h1>
|
||||
|
||||
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/PCA.Rmd"><code>vignettes/PCA.Rmd</code></a></small>
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/PCA.Rmd" class="external-link"><code>vignettes/PCA.Rmd</code></a></small>
|
||||
<div class="hidden name"><code>PCA.Rmd</code></div>
|
||||
|
||||
</div>
|
||||
@@ -203,16 +205,16 @@
|
||||
<p><strong>NOTE: This page will be updated soon, as the pca() function is currently being developed.</strong></p>
|
||||
<div id="introduction" class="section level1">
|
||||
<h1 class="hasAnchor">
|
||||
<a href="#introduction" class="anchor"></a>Introduction</h1>
|
||||
<a href="#introduction" class="anchor" aria-hidden="true"></a>Introduction</h1>
|
||||
</div>
|
||||
<div id="transforming" class="section level1">
|
||||
<h1 class="hasAnchor">
|
||||
<a href="#transforming" class="anchor"></a>Transforming</h1>
|
||||
<a href="#transforming" class="anchor" aria-hidden="true"></a>Transforming</h1>
|
||||
<p>For PCA, we need to transform our AMR data first. This is what the <code>example_isolates</code> data set in this package looks like:</p>
|
||||
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html">glimpse</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/AMR" class="external-link">AMR</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
|
||||
<span class="co"># Rows: 2,000</span>
|
||||
<span class="co"># Columns: 49</span>
|
||||
<span class="co"># $ date <date> 2002-01-02, 2002-01-03, 2002-01-07, 2002-01-07, 2002-…</span>
|
||||
@@ -267,13 +269,13 @@
|
||||
<p>Now to transform this to a data set with only resistance percentages per taxonomic order and genus:</p>
|
||||
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">resistance_data</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span><span class="op">(</span>order <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, <span class="co"># group on anything, like order</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span>order <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, <span class="co"># group on anything, like order</span>
|
||||
genus <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op">%>%</span> <span class="co"># and genus as we do here</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html">summarise_if</a></span><span class="op">(</span><span class="va">is.rsi</span>, <span class="va">resistance</span><span class="op">)</span> <span class="op">%>%</span> <span class="co"># then get resistance of all drugs</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">order</span>, <span class="va">genus</span>, <span class="va">AMC</span>, <span class="va">CXM</span>, <span class="va">CTX</span>,
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html" class="external-link">summarise_if</a></span><span class="op">(</span><span class="va">is.rsi</span>, <span class="va">resistance</span><span class="op">)</span> <span class="op">%>%</span> <span class="co"># then get resistance of all drugs</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">order</span>, <span class="va">genus</span>, <span class="va">AMC</span>, <span class="va">CXM</span>, <span class="va">CTX</span>,
|
||||
<span class="va">CAZ</span>, <span class="va">GEN</span>, <span class="va">TOB</span>, <span class="va">TMP</span>, <span class="va">SXT</span><span class="op">)</span> <span class="co"># and select only relevant columns</span>
|
||||
|
||||
<span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
|
||||
<span class="co"># # A tibble: 6 x 10</span>
|
||||
<span class="co"># # Groups: order [5]</span>
|
||||
<span class="co"># order genus AMC CXM CTX CAZ GEN TOB TMP SXT</span>
|
||||
@@ -287,15 +289,15 @@
|
||||
</div>
|
||||
<div id="perform-principal-component-analysis" class="section level1">
|
||||
<h1 class="hasAnchor">
|
||||
<a href="#perform-principal-component-analysis" class="anchor"></a>Perform principal component analysis</h1>
|
||||
<a href="#perform-principal-component-analysis" class="anchor" aria-hidden="true"></a>Perform principal component analysis</h1>
|
||||
<p>The new <code><a href="../reference/pca.html">pca()</a></code> function will automatically filter on rows that contain numeric values in all selected variables, so we now only need to do:</p>
|
||||
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">pca_result</span> <span class="op"><-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
|
||||
<span class="co"># ℹ Columns selected for PCA: "AMC", "CAZ", "CTX", "CXM", "GEN", "SXT", "TMP"</span>
|
||||
<span class="co"># and "TOB". Total observations available: 7.</span></code></pre></div>
|
||||
<p>The result can be reviewed with the good old <code><a href="https://rdrr.io/r/base/summary.html">summary()</a></code> function:</p>
|
||||
<p>The result can be reviewed with the good old <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code> function:</p>
|
||||
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span>
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span>
|
||||
<span class="co"># Groups (n=4, named as 'order'):</span>
|
||||
<span class="co"># [1] "Caryophanales" "Enterobacterales" "Lactobacillales" "Pseudomonadales"</span>
|
||||
<span class="co"># Importance of components:</span>
|
||||
@@ -305,13 +307,13 @@
|
||||
<span class="co"># Cumulative Proportion 0.5799 0.9330 0.9801 0.99446 0.99988 1.00000 1.000e+00</span></code></pre></div>
|
||||
<pre><code># Groups (n=4, named as 'order'):
|
||||
# [1] "Caryophanales" "Enterobacterales" "Lactobacillales" "Pseudomonadales"</code></pre>
|
||||
<p>Good news. The first two components explain a total of 93.3% of the variance (see the PC1 and PC2 values of the <em>Proportion of Variance</em>. We can create a so-called biplot with the base R <code><a href="https://rdrr.io/r/stats/biplot.html">biplot()</a></code> function, to see which antimicrobial resistance per drug explain the difference per microorganism.</p>
|
||||
<p>Good news. The first two components explain a total of 93.3% of the variance (see the PC1 and PC2 values of the <em>Proportion of Variance</em>. We can create a so-called biplot with the base R <code><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot()</a></code> function, to see which antimicrobial resistance per drug explain the difference per microorganism.</p>
|
||||
</div>
|
||||
<div id="plotting-the-results" class="section level1">
|
||||
<h1 class="hasAnchor">
|
||||
<a href="#plotting-the-results" class="anchor"></a>Plotting the results</h1>
|
||||
<a href="#plotting-the-results" class="anchor" aria-hidden="true"></a>Plotting the results</h1>
|
||||
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/stats/biplot.html">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></code></pre></div>
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></code></pre></div>
|
||||
<p><img src="PCA_files/figure-html/unnamed-chunk-5-1.png" width="750"></p>
|
||||
<p>But we can’t see the explanation of the points. Perhaps this works better with our new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function, that automatically adds the right labels and even groups:</p>
|
||||
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
|
||||
@@ -320,7 +322,7 @@
|
||||
<p>You can also print an ellipse per group, and edit the appearance:</p>
|
||||
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span>, ellipse <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op">+</span>
|
||||
<span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"An AMR/PCA biplot!"</span><span class="op">)</span></code></pre></div>
|
||||
<span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"An AMR/PCA biplot!"</span><span class="op">)</span></code></pre></div>
|
||||
<p><img src="PCA_files/figure-html/unnamed-chunk-7-1.png" width="750"></p>
|
||||
</div>
|
||||
</div>
|
||||
@@ -336,11 +338,13 @@
|
||||
|
||||
|
||||
<footer><div class="copyright">
|
||||
<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/">Alexander 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>
|
||||
<p></p>
|
||||
<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link external-link">Corinna Glasner</a>.</p>
|
||||
</div>
|
||||
|
||||
<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
||||
<p></p>
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link external-link">pkgdown</a> 1.6.1.9001.</p>
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||||
</footer>
|
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@@ -349,5 +353,7 @@
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||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -0,0 +1,12 @@
|
||||
// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
|
||||
// be compatible with the behavior of Pandoc < 2.8).
|
||||
document.addEventListener('DOMContentLoaded', function(e) {
|
||||
var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
|
||||
var i, h, a;
|
||||
for (i = 0; i < hs.length; i++) {
|
||||
h = hs[i];
|
||||
if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6
|
||||
a = h.attributes;
|
||||
while (a.length > 0) h.removeAttribute(a[0].name);
|
||||
}
|
||||
});
|
||||
+65
-59
@@ -27,6 +27,8 @@
|
||||
<![endif]-->
|
||||
</head>
|
||||
<body data-spy="scroll" data-target="#toc">
|
||||
|
||||
|
||||
<div class="container template-article">
|
||||
<header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
|
||||
<div class="container">
|
||||
@@ -39,7 +41,7 @@
|
||||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
@@ -47,14 +49,14 @@
|
||||
<ul class="nav navbar-nav">
|
||||
<li>
|
||||
<a href="../index.html">
|
||||
<span class="fas fa-home"></span>
|
||||
<span class="fa fa-home"></span>
|
||||
|
||||
Home
|
||||
</a>
|
||||
</li>
|
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<li class="dropdown">
|
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
|
||||
<span class="fas fa-question-circle"></span>
|
||||
<span class="fa fa-question-circle"></span>
|
||||
|
||||
How to
|
||||
|
||||
@@ -63,77 +65,77 @@
|
||||
<ul class="dropdown-menu" role="menu">
|
||||
<li>
|
||||
<a href="../articles/AMR.html">
|
||||
<span class="fas fa-directions"></span>
|
||||
<span class="fa fa-directions"></span>
|
||||
|
||||
Conduct AMR analysis
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
||||
<span class="fa fa-dice"></span>
|
||||
|
||||
Predict antimicrobial resistance
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/datasets.html">
|
||||
<span class="fas fa-database"></span>
|
||||
<span class="fa fa-database"></span>
|
||||
|
||||
Data sets for download / own use
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
||||
Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
||||
<span class="fa fa-skull-crossbones"></span>
|
||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/WHONET.html">
|
||||
<span class="fas fa-globe-americas"></span>
|
||||
<span class="fa fa-globe-americas"></span>
|
||||
|
||||
Work with WHONET data
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/SPSS.html">
|
||||
<span class="fas fa-file-upload"></span>
|
||||
<span class="fa fa-file-upload"></span>
|
||||
|
||||
Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/EUCAST.html">
|
||||
<span class="fas fa-exchange-alt"></span>
|
||||
<span class="fa fa-exchange-alt"></span>
|
||||
|
||||
Apply EUCAST rules
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
||||
<span class="fa fa-bug"></span>
|
||||
|
||||
Get properties of a microorganism
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/ab_property.html">
|
||||
<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
||||
|
||||
Get properties of an antibiotic
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/benchmarks.html">
|
||||
<span class="fas fa-shipping-fast"></span>
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -142,14 +144,14 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
||||
<span class="fa fa-book-open"></span>
|
||||
|
||||
Manual
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
||||
|
||||
Authors
|
||||
</a>
|
||||
@@ -164,7 +166,7 @@
|
||||
</ul>
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li>
|
||||
<a href="https://github.com/msberends/AMR">
|
||||
<a href="https://github.com/msberends/AMR" class="external-link">
|
||||
<span class="fab fa-github"></span>
|
||||
|
||||
Source Code
|
||||
@@ -172,7 +174,7 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
||||
<span class="fa fa-clipboard-list"></span>
|
||||
|
||||
Survey
|
||||
</a>
|
||||
@@ -187,15 +189,15 @@
|
||||
|
||||
|
||||
|
||||
</header><script src="SPSS_files/header-attrs-2.8/header-attrs.js"></script><div class="row">
|
||||
</header><script src="SPSS_files/header-attrs-2.9/header-attrs.js"></script><div class="row">
|
||||
<div class="col-md-9 contents">
|
||||
<div class="page-header toc-ignore">
|
||||
<h1 data-toc-skip>How to import data from SPSS / SAS / Stata</h1>
|
||||
<h4 class="author">Matthijs S. Berends</h4>
|
||||
<h4 data-toc-skip class="author">Matthijs S. Berends</h4>
|
||||
|
||||
<h4 class="date">03 June 2021</h4>
|
||||
<h4 data-toc-skip class="date">23 July 2021</h4>
|
||||
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/SPSS.Rmd"><code>vignettes/SPSS.Rmd</code></a></small>
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/SPSS.Rmd" class="external-link"><code>vignettes/SPSS.Rmd</code></a></small>
|
||||
<div class="hidden name"><code>SPSS.Rmd</code></div>
|
||||
|
||||
</div>
|
||||
@@ -204,17 +206,17 @@
|
||||
|
||||
<div id="spss-sas-stata" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#spss-sas-stata" class="anchor"></a>SPSS / SAS / Stata</h2>
|
||||
<a href="#spss-sas-stata" class="anchor" aria-hidden="true"></a>SPSS / SAS / Stata</h2>
|
||||
<p>SPSS (Statistical Package for the Social Sciences) is probably the most well-known software package for statistical analysis. SPSS is easier to learn than R, because in SPSS you only have to click a menu to run parts of your analysis. Because of its user-friendliness, it is taught at universities and particularly useful for students who are new to statistics. From my experience, I would guess that pretty much all (bio)medical students know it at the time they graduate. SAS and Stata are comparable statistical packages popular in big industries.</p>
|
||||
</div>
|
||||
<div id="compared-to-r" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#compared-to-r" class="anchor"></a>Compared to R</h2>
|
||||
<a href="#compared-to-r" class="anchor" aria-hidden="true"></a>Compared to R</h2>
|
||||
<p>As said, SPSS is easier to learn than R. But SPSS, SAS and Stata come with major downsides when comparing it with R:</p>
|
||||
<ul>
|
||||
<li>
|
||||
<p><strong>R is highly modular.</strong></p>
|
||||
<p>The <a href="https://cran.r-project.org/">official R network (CRAN)</a> features more than 16,000 packages at the time of writing, our <code>AMR</code> package being one of them. All these packages were peer-reviewed before publication. Aside from this official channel, there are also developers who choose not to submit to CRAN, but rather keep it on their own public repository, like GitHub. So there may even be a lot more than 14,000 packages out there.</p>
|
||||
<p>The <a href="https://cran.r-project.org/" class="external-link">official R network (CRAN)</a> features more than 16,000 packages at the time of writing, our <code>AMR</code> package being one of them. All these packages were peer-reviewed before publication. Aside from this official channel, there are also developers who choose not to submit to CRAN, but rather keep it on their own public repository, like GitHub. So there may even be a lot more than 14,000 packages out there.</p>
|
||||
<p>Bottom line is, you can really extend it yourself or ask somebody to do this for you. Take for example our <code>AMR</code> package. Among other things, it adds reliable reference data to R to help you with the data cleaning and analysis. SPSS, SAS and Stata will never know what a valid MIC value is or what the Gram stain of <em>E. coli</em> is. Or that all species of <em>Klebiella</em> are resistant to amoxicillin and that Floxapen<sup>®</sup> is a trade name of flucloxacillin. These facts and properties are often needed to clean existing data, which would be very inconvenient in a software package without reliable reference data. See below for a demonstration.</p>
|
||||
</li>
|
||||
<li>
|
||||
@@ -223,27 +225,27 @@
|
||||
</li>
|
||||
<li>
|
||||
<p><strong>R can be easily automated.</strong></p>
|
||||
<p>Over the last years, <a href="https://rmarkdown.rstudio.com/">R Markdown</a> has really made an interesting development. With R Markdown, you can very easily produce reports, whether the format has to be Word, PowerPoint, a website, a PDF document or just the raw data to Excel. It even allows the use of a reference file containing the layout style (e.g. fonts and colours) of your organisation. I use this a lot to generate weekly and monthly reports automatically. Just write the code once and enjoy the automatically updated reports at any interval you like.</p>
|
||||
<p>For an even more professional environment, you could create <a href="https://shiny.rstudio.com/">Shiny apps</a>: live manipulation of data using a custom made website. The webdesign knowledge needed (JavaScript, CSS, HTML) is almost <em>zero</em>.</p>
|
||||
<p>Over the last years, <a href="https://rmarkdown.rstudio.com/" class="external-link">R Markdown</a> has really made an interesting development. With R Markdown, you can very easily produce reports, whether the format has to be Word, PowerPoint, a website, a PDF document or just the raw data to Excel. It even allows the use of a reference file containing the layout style (e.g. fonts and colours) of your organisation. I use this a lot to generate weekly and monthly reports automatically. Just write the code once and enjoy the automatically updated reports at any interval you like.</p>
|
||||
<p>For an even more professional environment, you could create <a href="https://shiny.rstudio.com/" class="external-link">Shiny apps</a>: live manipulation of data using a custom made website. The webdesign knowledge needed (JavaScript, CSS, HTML) is almost <em>zero</em>.</p>
|
||||
</li>
|
||||
<li>
|
||||
<p><strong>R has a huge community.</strong></p>
|
||||
<p>Many R users just ask questions on websites like <a href="https://stackoverflow.com">StackOverflow.com</a>, the largest online community for programmers. At the time of writing, <a href="https://stackoverflow.com/questions/tagged/r?sort=votes">404,559 R-related questions</a> have already been asked on this platform (that covers questions and answers for any programming language). In my own experience, most questions are answered within a couple of minutes.</p>
|
||||
<p>Many R users just ask questions on websites like <a href="https://stackoverflow.com" class="external-link">StackOverflow.com</a>, the largest online community for programmers. At the time of writing, <a href="https://stackoverflow.com/questions/tagged/r?sort=votes" class="external-link">411,199 R-related questions</a> have already been asked on this platform (that covers questions and answers for any programming language). In my own experience, most questions are answered within a couple of minutes.</p>
|
||||
</li>
|
||||
<li>
|
||||
<p><strong>R understands any data type, including SPSS/SAS/Stata.</strong></p>
|
||||
<p>And that’s not vice versa I’m afraid. You can import data from any source into R. For example from SPSS, SAS and Stata (<a href="https://haven.tidyverse.org/">link</a>), from Minitab, Epi Info and EpiData (<a href="https://cran.r-project.org/package=foreign">link</a>), from Excel (<a href="https://readxl.tidyverse.org/">link</a>), from flat files like CSV, TXT or TSV (<a href="https://readr.tidyverse.org/">link</a>), or directly from databases and datawarehouses from anywhere on the world (<a href="https://dbplyr.tidyverse.org/">link</a>). You can even scrape websites to download tables that are live on the internet (<a href="https://github.com/hadley/rvest">link</a>) or get the results of an API call and transform it into data in only one command (<a href="https://github.com/Rdatatable/data.table/wiki/Convenience-features-of-fread">link</a>).</p>
|
||||
<p>And that’s not vice versa I’m afraid. You can import data from any source into R. For example from SPSS, SAS and Stata (<a href="https://haven.tidyverse.org/" class="external-link">link</a>), from Minitab, Epi Info and EpiData (<a href="https://cran.r-project.org/package=foreign" class="external-link">link</a>), from Excel (<a href="https://readxl.tidyverse.org/" class="external-link">link</a>), from flat files like CSV, TXT or TSV (<a href="https://readr.tidyverse.org/" class="external-link">link</a>), or directly from databases and datawarehouses from anywhere on the world (<a href="https://dbplyr.tidyverse.org/" class="external-link">link</a>). You can even scrape websites to download tables that are live on the internet (<a href="https://github.com/hadley/rvest" class="external-link">link</a>) or get the results of an API call and transform it into data in only one command (<a href="https://github.com/Rdatatable/data.table/wiki/Convenience-features-of-fread" class="external-link">link</a>).</p>
|
||||
<p>And the best part - you can export from R to most data formats as well. So you can import an SPSS file, do your analysis neatly in R and export the resulting tables to Excel files for sharing.</p>
|
||||
</li>
|
||||
<li>
|
||||
<p><strong>R is completely free and open-source.</strong></p>
|
||||
<p>No strings attached. It was created and is being maintained by volunteers who believe that (data) science should be open and publicly available to everybody. SPSS, SAS and Stata are quite expensive. IBM SPSS Staticstics only comes with subscriptions nowadays, varying <a href="https://www.ibm.com/products/spss-statistics/pricing">between USD 1,300 and USD 8,500</a> per user <em>per year</em>. SAS Analytics Pro costs <a href="https://www.sas.com/store/products-solutions/sas-analytics-pro/prodPERSANL.html">around USD 10,000</a> per computer. Stata also has a business model with subscription fees, varying <a href="https://www.stata.com/order/new/bus/single-user-licenses/dl/">between USD 600 and USD 2,800</a> per computer per year, but lower prices come with a limitation of the number of variables you can work with. And still they do not offer the above benefits of R.</p>
|
||||
<p>No strings attached. It was created and is being maintained by volunteers who believe that (data) science should be open and publicly available to everybody. SPSS, SAS and Stata are quite expensive. IBM SPSS Staticstics only comes with subscriptions nowadays, varying <a href="https://www.ibm.com/products/spss-statistics/pricing" class="external-link">between USD 1,300 and USD 8,500</a> per user <em>per year</em>. SAS Analytics Pro costs <a href="https://www.sas.com/store/products-solutions/sas-analytics-pro/prodPERSANL.html" class="external-link">around USD 10,000</a> per computer. Stata also has a business model with subscription fees, varying <a href="https://www.stata.com/order/new/bus/single-user-licenses/dl/" class="external-link">between USD 600 and USD 2,800</a> per computer per year, but lower prices come with a limitation of the number of variables you can work with. And still they do not offer the above benefits of R.</p>
|
||||
<p>If you are working at a midsized or small company, you can save it tens of thousands of dollars by using R instead of e.g. SPSS - gaining even more functions and flexibility. And all R enthousiasts can do as much PR as they want (like I do here), because nobody is officially associated with or affiliated by R. It is really free.</p>
|
||||
</li>
|
||||
<li>
|
||||
<p><strong>R is (nowadays) the preferred analysis software in academic papers.</strong></p>
|
||||
<p>At present, R is among the world most powerful statistical languages, and it is generally very popular in science (Bollmann <em>et al.</em>, 2017). For all the above reasons, the number of references to R as an analysis method in academic papers <a href="https://r4stats.com/2014/08/20/r-passes-spss-in-scholarly-use-stata-growing-rapidly/">is rising continuously</a> and has even surpassed SPSS for academic use (Muenchen, 2014).</p>
|
||||
<p>I believe that the thing with SPSS is, that it has always had a great user interface which is very easy to learn and use. Back when they developed it, they had very little competition, let alone from R. R didn’t even had a professional user interface until the last decade (called RStudio, see below). How people used R between the nineties and 2010 is almost completely incomparable to how R is being used now. The language itself <a href="https://www.tidyverse.org/packages/">has been restyled completely</a> by volunteers who are dedicated professionals in the field of data science. SPSS was great when there was nothing else that could compete. But now in 2021, I don’t see any reason why SPSS would be of any better use than R.</p>
|
||||
<p>At present, R is among the world most powerful statistical languages, and it is generally very popular in science (Bollmann <em>et al.</em>, 2017). For all the above reasons, the number of references to R as an analysis method in academic papers <a href="https://r4stats.com/2014/08/20/r-passes-spss-in-scholarly-use-stata-growing-rapidly/" class="external-link">is rising continuously</a> and has even surpassed SPSS for academic use (Muenchen, 2014).</p>
|
||||
<p>I believe that the thing with SPSS is, that it has always had a great user interface which is very easy to learn and use. Back when they developed it, they had very little competition, let alone from R. R didn’t even had a professional user interface until the last decade (called RStudio, see below). How people used R between the nineties and 2010 is almost completely incomparable to how R is being used now. The language itself <a href="https://www.tidyverse.org/packages/" class="external-link">has been restyled completely</a> by volunteers who are dedicated professionals in the field of data science. SPSS was great when there was nothing else that could compete. But now in 2021, I don’t see any reason why SPSS would be of any better use than R.</p>
|
||||
</li>
|
||||
</ul>
|
||||
<p>To demonstrate the first point:</p>
|
||||
@@ -261,7 +263,7 @@
|
||||
<span class="co"># [1] "Gram-negative"</span>
|
||||
|
||||
<span class="co"># Klebsiella is intrinsic resistant to amoxicillin, according to EUCAST:</span>
|
||||
<span class="va">klebsiella_test</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="st">"klebsiella"</span>,
|
||||
<span class="va">klebsiella_test</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="st">"klebsiella"</span>,
|
||||
amox <span class="op">=</span> <span class="st">"S"</span>,
|
||||
stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
|
||||
<span class="va">klebsiella_test</span> <span class="co"># (our original data)</span>
|
||||
@@ -283,17 +285,17 @@
|
||||
</div>
|
||||
<div id="import-data-from-spsssasstata" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#import-data-from-spsssasstata" class="anchor"></a>Import data from SPSS/SAS/Stata</h2>
|
||||
<a href="#import-data-from-spsssasstata" class="anchor" aria-hidden="true"></a>Import data from SPSS/SAS/Stata</h2>
|
||||
<div id="rstudio" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#rstudio" class="anchor"></a>RStudio</h3>
|
||||
<p>To work with R, probably the best option is to use <a href="https://www.rstudio.com/products/rstudio/">RStudio</a>. It is an open-source and free desktop environment which not only allows you to run R code, but also supports project management, version management, package management and convenient import menus to work with other data sources. You can also install <a href="https://www.rstudio.com/products/rstudio/">RStudio Server</a> on a private or corporate server, which brings nothing less than the complete RStudio software to you as a website (at home or at work).</p>
|
||||
<a href="#rstudio" class="anchor" aria-hidden="true"></a>RStudio</h3>
|
||||
<p>To work with R, probably the best option is to use <a href="https://www.rstudio.com/products/rstudio/" class="external-link">RStudio</a>. It is an open-source and free desktop environment which not only allows you to run R code, but also supports project management, version management, package management and convenient import menus to work with other data sources. You can also install <a href="https://www.rstudio.com/products/rstudio/" class="external-link">RStudio Server</a> on a private or corporate server, which brings nothing less than the complete RStudio software to you as a website (at home or at work).</p>
|
||||
<p>To import a data file, just click <em>Import Dataset</em> in the Environment tab:</p>
|
||||
<p><img src="https://github.com/msberends/AMR/raw/master/docs/import1.png"></p>
|
||||
<p>If additional packages are needed, RStudio will ask you if they should be installed on beforehand.</p>
|
||||
<p>In the the window that opens, you can define all options (parameters) that should be used for import and you’re ready to go:</p>
|
||||
<p><img src="https://github.com/msberends/AMR/raw/master/docs/import2.png"></p>
|
||||
<p>If you want named variables to be imported as factors so it resembles SPSS more, use <code><a href="https://haven.tidyverse.org/reference/as_factor.html">as_factor()</a></code>.</p>
|
||||
<p>If you want named variables to be imported as factors so it resembles SPSS more, use <code><a href="https://haven.tidyverse.org/reference/as_factor.html" class="external-link">as_factor()</a></code>.</p>
|
||||
<p>The difference is this:</p>
|
||||
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">SPSS_data</span>
|
||||
@@ -330,70 +332,70 @@
|
||||
</div>
|
||||
<div id="base-r" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#base-r" class="anchor"></a>Base R</h3>
|
||||
<p>To import data from SPSS, SAS or Stata, you can use the <a href="https://haven.tidyverse.org/">great <code>haven</code> package</a> yourself:</p>
|
||||
<a href="#base-r" class="anchor" aria-hidden="true"></a>Base R</h3>
|
||||
<p>To import data from SPSS, SAS or Stata, you can use the <a href="https://haven.tidyverse.org/" class="external-link">great <code>haven</code> package</a> yourself:</p>
|
||||
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># download and install the latest version:</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span><span class="op">(</span><span class="st">"haven"</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"haven"</span><span class="op">)</span>
|
||||
<span class="co"># load the package you just installed:</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://haven.tidyverse.org">haven</a></span><span class="op">)</span> </code></pre></div>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://haven.tidyverse.org" class="external-link">haven</a></span><span class="op">)</span> </code></pre></div>
|
||||
<p>You can now import files as follows:</p>
|
||||
<div id="spss" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#spss" class="anchor"></a>SPSS</h4>
|
||||
<a href="#spss" class="anchor" aria-hidden="true"></a>SPSS</h4>
|
||||
<p>To read files from SPSS into R:</p>
|
||||
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># read any SPSS file based on file extension (best way):</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_spss</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html" class="external-link">read_spss</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
|
||||
|
||||
<span class="co"># read .sav or .zsav file:</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_sav</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html" class="external-link">read_sav</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
|
||||
|
||||
<span class="co"># read .por file:</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_por</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></code></pre></div>
|
||||
<p>Do not forget about <code><a href="https://haven.tidyverse.org/reference/as_factor.html">as_factor()</a></code>, as mentioned above.</p>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html" class="external-link">read_por</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></code></pre></div>
|
||||
<p>Do not forget about <code><a href="https://haven.tidyverse.org/reference/as_factor.html" class="external-link">as_factor()</a></code>, as mentioned above.</p>
|
||||
<p>To export your R objects to the SPSS file format:</p>
|
||||
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># save as .sav file:</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">write_sav</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html" class="external-link">write_sav</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
|
||||
|
||||
<span class="co"># save as compressed .zsav file:</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">write_sav</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, compress <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html" class="external-link">write_sav</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, compress <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div>
|
||||
</div>
|
||||
<div id="sas" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#sas" class="anchor"></a>SAS</h4>
|
||||
<a href="#sas" class="anchor" aria-hidden="true"></a>SAS</h4>
|
||||
<p>To read files from SAS into R:</p>
|
||||
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># read .sas7bdat + .sas7bcat files:</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html">read_sas</a></span><span class="op">(</span>data_file <span class="op">=</span> <span class="st">"path/to/file"</span>, catalog_file <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html" class="external-link">read_sas</a></span><span class="op">(</span>data_file <span class="op">=</span> <span class="st">"path/to/file"</span>, catalog_file <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span>
|
||||
|
||||
<span class="co"># read SAS transport files (version 5 and version 8):</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html">read_xpt</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></code></pre></div>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html" class="external-link">read_xpt</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></code></pre></div>
|
||||
<p>To export your R objects to the SAS file format:</p>
|
||||
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># save as regular SAS file:</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html">write_sas</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html" class="external-link">write_sas</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
|
||||
|
||||
<span class="co"># the SAS transport format is an open format </span>
|
||||
<span class="co"># (required for submission of the data to the FDA)</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html">write_xpt</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, version <span class="op">=</span> <span class="fl">8</span><span class="op">)</span></code></pre></div>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html" class="external-link">write_xpt</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, version <span class="op">=</span> <span class="fl">8</span><span class="op">)</span></code></pre></div>
|
||||
</div>
|
||||
<div id="stata" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#stata" class="anchor"></a>Stata</h4>
|
||||
<a href="#stata" class="anchor" aria-hidden="true"></a>Stata</h4>
|
||||
<p>To read files from Stata into R:</p>
|
||||
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># read .dta file:</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">read_stata</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"/path/to/file"</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html" class="external-link">read_stata</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"/path/to/file"</span><span class="op">)</span>
|
||||
|
||||
<span class="co"># works exactly the same:</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">read_dta</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"/path/to/file"</span><span class="op">)</span></code></pre></div>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html" class="external-link">read_dta</a></span><span class="op">(</span>file <span class="op">=</span> <span class="st">"/path/to/file"</span><span class="op">)</span></code></pre></div>
|
||||
<p>To export your R objects to the Stata file format:</p>
|
||||
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># save as .dta file, Stata version 14:</span>
|
||||
<span class="co"># (supports Stata v8 until v15 at the time of writing)</span>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">write_dta</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"/path/to/file"</span>, version <span class="op">=</span> <span class="fl">14</span><span class="op">)</span></code></pre></div>
|
||||
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html" class="external-link">write_dta</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"/path/to/file"</span>, version <span class="op">=</span> <span class="fl">14</span><span class="op">)</span></code></pre></div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@@ -410,11 +412,13 @@
|
||||
|
||||
|
||||
<footer><div class="copyright">
|
||||
<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/">Alexander 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>
|
||||
<p></p>
|
||||
<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link external-link">Corinna Glasner</a>.</p>
|
||||
</div>
|
||||
|
||||
<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
||||
<p></p>
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link external-link">pkgdown</a> 1.6.1.9001.</p>
|
||||
</div>
|
||||
|
||||
</footer>
|
||||
@@ -423,5 +427,7 @@
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -0,0 +1,12 @@
|
||||
// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
|
||||
// be compatible with the behavior of Pandoc < 2.8).
|
||||
document.addEventListener('DOMContentLoaded', function(e) {
|
||||
var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
|
||||
var i, h, a;
|
||||
for (i = 0; i < hs.length; i++) {
|
||||
h = hs[i];
|
||||
if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6
|
||||
a = h.attributes;
|
||||
while (a.length > 0) h.removeAttribute(a[0].name);
|
||||
}
|
||||
});
|
||||
+46
-40
@@ -27,6 +27,8 @@
|
||||
<![endif]-->
|
||||
</head>
|
||||
<body data-spy="scroll" data-target="#toc">
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||||
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<div class="container template-article">
|
||||
<header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
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<div class="container">
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@@ -39,7 +41,7 @@
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</button>
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<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
|
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</div>
|
||||
|
||||
@@ -47,14 +49,14 @@
|
||||
<ul class="nav navbar-nav">
|
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<li>
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<a href="../index.html">
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<span class="fas fa-home"></span>
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<span class="fa fa-home"></span>
|
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Home
|
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</a>
|
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</li>
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<li class="dropdown">
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
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<span class="fas fa-question-circle"></span>
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||||
<span class="fa fa-question-circle"></span>
|
||||
|
||||
How to
|
||||
|
||||
@@ -63,77 +65,77 @@
|
||||
<ul class="dropdown-menu" role="menu">
|
||||
<li>
|
||||
<a href="../articles/AMR.html">
|
||||
<span class="fas fa-directions"></span>
|
||||
<span class="fa fa-directions"></span>
|
||||
|
||||
Conduct AMR analysis
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
||||
<span class="fa fa-dice"></span>
|
||||
|
||||
Predict antimicrobial resistance
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/datasets.html">
|
||||
<span class="fas fa-database"></span>
|
||||
<span class="fa fa-database"></span>
|
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|
||||
Data sets for download / own use
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||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
||||
Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
||||
<span class="fa fa-skull-crossbones"></span>
|
||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/WHONET.html">
|
||||
<span class="fas fa-globe-americas"></span>
|
||||
<span class="fa fa-globe-americas"></span>
|
||||
|
||||
Work with WHONET data
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/SPSS.html">
|
||||
<span class="fas fa-file-upload"></span>
|
||||
<span class="fa fa-file-upload"></span>
|
||||
|
||||
Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/EUCAST.html">
|
||||
<span class="fas fa-exchange-alt"></span>
|
||||
<span class="fa fa-exchange-alt"></span>
|
||||
|
||||
Apply EUCAST rules
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
||||
<span class="fa fa-bug"></span>
|
||||
|
||||
Get properties of a microorganism
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/ab_property.html">
|
||||
<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
||||
|
||||
Get properties of an antibiotic
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/benchmarks.html">
|
||||
<span class="fas fa-shipping-fast"></span>
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -142,14 +144,14 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
||||
<span class="fa fa-book-open"></span>
|
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|
||||
Manual
|
||||
</a>
|
||||
</li>
|
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<li>
|
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<a href="../authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
||||
|
||||
Authors
|
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</a>
|
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@@ -164,7 +166,7 @@
|
||||
</ul>
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li>
|
||||
<a href="https://github.com/msberends/AMR">
|
||||
<a href="https://github.com/msberends/AMR" class="external-link">
|
||||
<span class="fab fa-github"></span>
|
||||
|
||||
Source Code
|
||||
@@ -172,7 +174,7 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
||||
<span class="fa fa-clipboard-list"></span>
|
||||
|
||||
Survey
|
||||
</a>
|
||||
@@ -187,13 +189,13 @@
|
||||
|
||||
|
||||
|
||||
</header><script src="WHONET_files/header-attrs-2.8/header-attrs.js"></script><div class="row">
|
||||
</header><script src="WHONET_files/header-attrs-2.9/header-attrs.js"></script><div class="row">
|
||||
<div class="col-md-9 contents">
|
||||
<div class="page-header toc-ignore">
|
||||
<h1 data-toc-skip>How to work with WHONET data</h1>
|
||||
|
||||
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/WHONET.Rmd"><code>vignettes/WHONET.Rmd</code></a></small>
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/WHONET.Rmd" class="external-link"><code>vignettes/WHONET.Rmd</code></a></small>
|
||||
<div class="hidden name"><code>WHONET.Rmd</code></div>
|
||||
|
||||
</div>
|
||||
@@ -202,23 +204,23 @@
|
||||
|
||||
<div id="import-of-data" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#import-of-data" class="anchor"></a>Import of data</h3>
|
||||
<p>This tutorial assumes you already imported the WHONET data with e.g. the <a href="https://readxl.tidyverse.org/"><code>readxl</code> package</a>. In RStudio, this can be done using the menu button ‘Import Dataset’ in the tab ‘Environment’. Choose the option ‘From Excel’ and select your exported file. Make sure date fields are imported correctly.</p>
|
||||
<a href="#import-of-data" class="anchor" aria-hidden="true"></a>Import of data</h3>
|
||||
<p>This tutorial assumes you already imported the WHONET data with e.g. the <a href="https://readxl.tidyverse.org/" class="external-link"><code>readxl</code> package</a>. In RStudio, this can be done using the menu button ‘Import Dataset’ in the tab ‘Environment’. Choose the option ‘From Excel’ and select your exported file. Make sure date fields are imported correctly.</p>
|
||||
<p>An example syntax could look like this:</p>
|
||||
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://readxl.tidyverse.org">readxl</a></span><span class="op">)</span>
|
||||
<span class="va">data</span> <span class="op"><-</span> <span class="fu"><a href="https://readxl.tidyverse.org/reference/read_excel.html">read_excel</a></span><span class="op">(</span>path <span class="op">=</span> <span class="st">"path/to/your/file.xlsx"</span><span class="op">)</span></code></pre></div>
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://readxl.tidyverse.org" class="external-link">readxl</a></span><span class="op">)</span>
|
||||
<span class="va">data</span> <span class="op"><-</span> <span class="fu"><a href="https://readxl.tidyverse.org/reference/read_excel.html" class="external-link">read_excel</a></span><span class="op">(</span>path <span class="op">=</span> <span class="st">"path/to/your/file.xlsx"</span><span class="op">)</span></code></pre></div>
|
||||
<p>This package comes with an <a href="https://msberends.github.io/AMR/reference/WHONET.html">example data set <code>WHONET</code></a>. We will use it for this analysis.</p>
|
||||
</div>
|
||||
<div id="preparation" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#preparation" class="anchor"></a>Preparation</h3>
|
||||
<p>First, load the relevant packages if you did not yet did this. I use the tidyverse for all of my analyses. All of them. If you don’t know it yet, I suggest you read about it on their website: <a href="https://www.tidyverse.org/" class="uri">https://www.tidyverse.org/</a>.</p>
|
||||
<a href="#preparation" class="anchor" aria-hidden="true"></a>Preparation</h3>
|
||||
<p>First, load the relevant packages if you did not yet did this. I use the tidyverse for all of my analyses. All of them. If you don’t know it yet, I suggest you read about it on their website: <a href="https://www.tidyverse.org/" class="external-link uri">https://www.tidyverse.org/</a>.</p>
|
||||
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org">ggplot2</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span> <span class="co"># this package</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div>
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/AMR" class="external-link">AMR</a></span><span class="op">)</span> <span class="co"># this package</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner" class="external-link">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div>
|
||||
<p>We will have to transform some variables to simplify and automate the analysis:</p>
|
||||
<ul>
|
||||
<li>Microorganisms should be transformed to our own microorganism codes (called an <code>mo</code>) using <a href="https://msberends.github.io/AMR/reference/catalogue_of_life">our Catalogue of Life reference data set</a>, which contains all ~70,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with <code><a href="../reference/as.mo.html">as.mo()</a></code>. This function also recognises almost all WHONET abbreviations of microorganisms.</li>
|
||||
@@ -228,15 +230,15 @@
|
||||
<code class="sourceCode R"><span class="co"># transform variables</span>
|
||||
<span class="va">data</span> <span class="op"><-</span> <span class="va">WHONET</span> <span class="op">%>%</span>
|
||||
<span class="co"># get microbial ID based on given organism</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">Organism</span><span class="op">)</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">Organism</span><span class="op">)</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="co"># transform everything from "AMP_ND10" to "CIP_EE" to the new `rsi` class</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span><span class="op">(</span><span class="va">AMP_ND10</span><span class="op">:</span><span class="va">CIP_EE</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span></code></pre></div>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">AMP_ND10</span><span class="op">:</span><span class="va">CIP_EE</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span></code></pre></div>
|
||||
<p>No errors or warnings, so all values are transformed succesfully.</p>
|
||||
<p>We also created a package dedicated to data cleaning and checking, called the <code>cleaner</code> package. Its <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> function can be used to create frequency tables.</p>
|
||||
<p>We also created a package dedicated to data cleaning and checking, called the <code>cleaner</code> package. Its <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq()</a></code> function can be used to create frequency tables.</p>
|
||||
<p>So let’s check our data, with a couple of frequency tables:</p>
|
||||
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># our newly created `mo` variable, put in the mo_name() function</span>
|
||||
<span class="va">data</span> <span class="op">%>%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, nmax <span class="op">=</span> <span class="fl">10</span><span class="op">)</span></code></pre></div>
|
||||
<span class="va">data</span> <span class="op">%>%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, nmax <span class="op">=</span> <span class="fl">10</span><span class="op">)</span></code></pre></div>
|
||||
<p><strong>Frequency table</strong></p>
|
||||
<p>Class: character<br>
|
||||
Length: 500<br>
|
||||
@@ -340,7 +342,7 @@ Longest: 40</p>
|
||||
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># our transformed antibiotic columns</span>
|
||||
<span class="co"># amoxicillin/clavulanic acid (J01CR02) as an example</span>
|
||||
<span class="va">data</span> <span class="op">%>%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">AMC_ND2</span><span class="op">)</span></code></pre></div>
|
||||
<span class="va">data</span> <span class="op">%>%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="va">AMC_ND2</span><span class="op">)</span></code></pre></div>
|
||||
<p><strong>Frequency table</strong></p>
|
||||
<p>Class: factor > ordered > rsi (numeric)<br>
|
||||
Length: 500<br>
|
||||
@@ -389,12 +391,12 @@ Drug group: Beta-lactams/penicillins<br>
|
||||
</div>
|
||||
<div id="a-first-glimpse-at-results" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#a-first-glimpse-at-results" class="anchor"></a>A first glimpse at results</h3>
|
||||
<a href="#a-first-glimpse-at-results" class="anchor" aria-hidden="true"></a>A first glimpse at results</h3>
|
||||
<p>An easy <code>ggplot</code> will already give a lot of information, using the included <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code> function:</p>
|
||||
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">data</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span><span class="op">(</span><span class="va">Country</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">Country</span>, <span class="va">AMP_ND2</span>, <span class="va">AMC_ED20</span>, <span class="va">CAZ_ED10</span>, <span class="va">CIP_ED5</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Country</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">Country</span>, <span class="va">AMP_ND2</span>, <span class="va">AMC_ED20</span>, <span class="va">CAZ_ED10</span>, <span class="va">CIP_ED5</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="../reference/ggplot_rsi.html">ggplot_rsi</a></span><span class="op">(</span>translate_ab <span class="op">=</span> <span class="st">'ab'</span>, facet <span class="op">=</span> <span class="st">"Country"</span>, datalabels <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
|
||||
<p><img src="WHONET_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
|
||||
</div>
|
||||
@@ -409,11 +411,13 @@ Drug group: Beta-lactams/penicillins<br>
|
||||
|
||||
|
||||
<footer><div class="copyright">
|
||||
<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/">Alexander 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>
|
||||
<p></p>
|
||||
<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link external-link">Corinna Glasner</a>.</p>
|
||||
</div>
|
||||
|
||||
<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
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<p></p>
|
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<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link external-link">pkgdown</a> 1.6.1.9001.</p>
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||||
</footer>
|
||||
@@ -422,5 +426,7 @@ Drug group: Beta-lactams/penicillins<br>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -0,0 +1,12 @@
|
||||
// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
|
||||
// be compatible with the behavior of Pandoc < 2.8).
|
||||
document.addEventListener('DOMContentLoaded', function(e) {
|
||||
var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
|
||||
var i, h, a;
|
||||
for (i = 0; i < hs.length; i++) {
|
||||
h = hs[i];
|
||||
if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6
|
||||
a = h.attributes;
|
||||
while (a.length > 0) h.removeAttribute(a[0].name);
|
||||
}
|
||||
});
|
||||
@@ -27,6 +27,8 @@
|
||||
<![endif]-->
|
||||
</head>
|
||||
<body data-spy="scroll" data-target="#toc">
|
||||
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<header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
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@@ -39,7 +41,7 @@
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||||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
@@ -47,14 +49,14 @@
|
||||
<ul class="nav navbar-nav">
|
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<li>
|
||||
<a href="../index.html">
|
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<span class="fas fa-home"></span>
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Home
|
||||
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|
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<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
|
||||
<span class="fas fa-question-circle"></span>
|
||||
<span class="fa fa-question-circle"></span>
|
||||
|
||||
How to
|
||||
|
||||
@@ -63,77 +65,77 @@
|
||||
<ul class="dropdown-menu" role="menu">
|
||||
<li>
|
||||
<a href="../articles/AMR.html">
|
||||
<span class="fas fa-directions"></span>
|
||||
<span class="fa fa-directions"></span>
|
||||
|
||||
Conduct AMR analysis
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
||||
<span class="fa fa-dice"></span>
|
||||
|
||||
Predict antimicrobial resistance
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/datasets.html">
|
||||
<span class="fas fa-database"></span>
|
||||
<span class="fa fa-database"></span>
|
||||
|
||||
Data sets for download / own use
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
||||
Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
||||
<span class="fa fa-skull-crossbones"></span>
|
||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/WHONET.html">
|
||||
<span class="fas fa-globe-americas"></span>
|
||||
<span class="fa fa-globe-americas"></span>
|
||||
|
||||
Work with WHONET data
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/SPSS.html">
|
||||
<span class="fas fa-file-upload"></span>
|
||||
<span class="fa fa-file-upload"></span>
|
||||
|
||||
Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/EUCAST.html">
|
||||
<span class="fas fa-exchange-alt"></span>
|
||||
<span class="fa fa-exchange-alt"></span>
|
||||
|
||||
Apply EUCAST rules
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
||||
<span class="fa fa-bug"></span>
|
||||
|
||||
Get properties of a microorganism
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/ab_property.html">
|
||||
<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
||||
|
||||
Get properties of an antibiotic
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/benchmarks.html">
|
||||
<span class="fas fa-shipping-fast"></span>
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -142,14 +144,14 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
||||
<span class="fa fa-book-open"></span>
|
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|
||||
Manual
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
||||
|
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Authors
|
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</a>
|
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@@ -164,7 +166,7 @@
|
||||
</ul>
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li>
|
||||
<a href="https://github.com/msberends/AMR">
|
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<a href="https://github.com/msberends/AMR" class="external-link">
|
||||
<span class="fab fa-github"></span>
|
||||
|
||||
Source Code
|
||||
@@ -172,7 +174,7 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
||||
<span class="fa fa-clipboard-list"></span>
|
||||
|
||||
Survey
|
||||
</a>
|
||||
@@ -187,30 +189,30 @@
|
||||
|
||||
|
||||
|
||||
</header><script src="benchmarks_files/header-attrs-2.8/header-attrs.js"></script><div class="row">
|
||||
</header><script src="benchmarks_files/header-attrs-2.9/header-attrs.js"></script><div class="row">
|
||||
<div class="col-md-9 contents">
|
||||
<div class="page-header toc-ignore">
|
||||
<h1 data-toc-skip>Benchmarks</h1>
|
||||
|
||||
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/benchmarks.Rmd"><code>vignettes/benchmarks.Rmd</code></a></small>
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/benchmarks.Rmd" class="external-link"><code>vignettes/benchmarks.Rmd</code></a></small>
|
||||
<div class="hidden name"><code>benchmarks.Rmd</code></div>
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the <a href="http://www.catalogueoflife.org">Catalogue of Life</a> (CoL) and the <a href="https://lpsn.dsmz.de">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN). We created a function <code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid microbial ID by using intelligent rules combined with the microbial taxonomy.</p>
|
||||
<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark()</a></code> runs different input expressions independently of each other and measures their time-to-result.</p>
|
||||
<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the <a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a> (CoL) and the <a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN). We created a function <code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid microbial ID by using intelligent rules combined with the microbial taxonomy.</p>
|
||||
<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark()</a></code> runs different input expressions independently of each other and measures their time-to-result.</p>
|
||||
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/joshuaulrich/microbenchmark/">microbenchmark</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span></code></pre></div>
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/joshuaulrich/microbenchmark/" class="external-link">microbenchmark</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/AMR" class="external-link">AMR</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></code></pre></div>
|
||||
<p>In the next test, we try to ‘coerce’ different input values into the microbial code of <em>Staphylococcus aureus</em>. Coercion is a computational process of forcing output based on an input. For microorganism names, coercing user input to taxonomically valid microorganism names is crucial to ensure correct interpretation and to enable grouping based on taxonomic properties.</p>
|
||||
<p>The actual result is the same every time: it returns its microorganism code <code>B_STPHY_AURS</code> (<em>B</em> stands for <em>Bacteria</em>, its taxonomic kingdom).</p>
|
||||
<p>But the calculation time differs a lot:</p>
|
||||
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">S.aureus</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>
|
||||
<code class="sourceCode R"><span class="va">S.aureus</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>
|
||||
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"sau"</span><span class="op">)</span>, <span class="co"># WHONET code</span>
|
||||
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"stau"</span><span class="op">)</span>,
|
||||
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"STAU"</span><span class="op">)</span>,
|
||||
@@ -224,80 +226,80 @@
|
||||
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"MRSA"</span><span class="op">)</span>, <span class="co"># Methicillin Resistant S. aureus</span>
|
||||
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"VISA"</span><span class="op">)</span>, <span class="co"># Vancomycin Intermediate S. aureus</span>
|
||||
times <span class="op">=</span> <span class="fl">25</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">S.aureus</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">S.aureus</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>
|
||||
<span class="co"># Unit: milliseconds</span>
|
||||
<span class="co"># expr min lq mean median uq max neval</span>
|
||||
<span class="co"># as.mo("sau") 13.0 13.0 16.0 15.0 16.0 44 25</span>
|
||||
<span class="co"># as.mo("stau") 55.0 58.0 75.0 62.0 94.0 110 25</span>
|
||||
<span class="co"># as.mo("STAU") 55.0 59.0 77.0 89.0 94.0 100 25</span>
|
||||
<span class="co"># as.mo("staaur") 11.0 13.0 20.0 14.0 16.0 48 25</span>
|
||||
<span class="co"># as.mo("STAAUR") 11.0 13.0 17.0 15.0 16.0 49 25</span>
|
||||
<span class="co"># as.mo("S. aureus") 26.0 30.0 41.0 32.0 60.0 68 25</span>
|
||||
<span class="co"># as.mo("S aureus") 27.0 29.0 44.0 32.0 58.0 160 25</span>
|
||||
<span class="co"># as.mo("Staphylococcus aureus") 3.3 3.9 5.5 4.2 4.7 37 25</span>
|
||||
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 250.0 260.0 280.0 280.0 290.0 320 25</span>
|
||||
<span class="co"># as.mo("Sthafilokkockus aaureuz") 170.0 200.0 210.0 200.0 220.0 250 25</span>
|
||||
<span class="co"># as.mo("MRSA") 12.0 14.0 21.0 15.0 17.0 56 25</span>
|
||||
<span class="co"># as.mo("VISA") 20.0 23.0 33.0 25.0 51.0 59 25</span></code></pre></div>
|
||||
<span class="co"># as.mo("sau") 12.0 13.0 19.0 14 16.0 49 25</span>
|
||||
<span class="co"># as.mo("stau") 55.0 58.0 80.0 91 96.0 110 25</span>
|
||||
<span class="co"># as.mo("STAU") 57.0 63.0 79.0 66 96.0 110 25</span>
|
||||
<span class="co"># as.mo("staaur") 13.0 13.0 19.0 14 16.0 48 25</span>
|
||||
<span class="co"># as.mo("STAAUR") 13.0 13.0 22.0 15 17.0 48 25</span>
|
||||
<span class="co"># as.mo("S. aureus") 27.0 30.0 42.0 33 62.0 67 25</span>
|
||||
<span class="co"># as.mo("S aureus") 28.0 30.0 37.0 32 34.0 64 25</span>
|
||||
<span class="co"># as.mo("Staphylococcus aureus") 3.5 3.9 5.5 4 4.4 38 25</span>
|
||||
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 260.0 270.0 280.0 270 290.0 370 25</span>
|
||||
<span class="co"># as.mo("Sthafilokkockus aaureuz") 170.0 200.0 210.0 210 230.0 250 25</span>
|
||||
<span class="co"># as.mo("MRSA") 13.0 14.0 20.0 15 15.0 51 25</span>
|
||||
<span class="co"># as.mo("VISA") 22.0 23.0 33.0 25 27.0 64 25</span></code></pre></div>
|
||||
<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="750"></p>
|
||||
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 200 milliseconds, this is only 5 input values per second. It is clear that accepted taxonomic names are extremely fast, but some variations are up to 200 times slower to determine.</p>
|
||||
<p>To improve performance, we implemented two important algorithms to save unnecessary calculations: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
|
||||
<div id="repetitive-results" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#repetitive-results" class="anchor"></a>Repetitive results</h3>
|
||||
<a href="#repetitive-results" class="anchor" aria-hidden="true"></a>Repetitive results</h3>
|
||||
<p>Repetitive results are values that are present more than once in a vector. Unique values will only be calculated once by <code><a href="../reference/as.mo.html">as.mo()</a></code>. So running <code><a href="../reference/as.mo.html">as.mo(c("E. coli", "E. coli"))</a></code> will check the value <code>"E. coli"</code> only once.</p>
|
||||
<p>To prove this, we will use <code><a href="../reference/mo_property.html">mo_name()</a></code> for testing - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
|
||||
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># start with the example_isolates data set</span>
|
||||
<span class="va">x</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op">%>%</span>
|
||||
<span class="co"># take all MO codes from the 'mo' column</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html">pull</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html" class="external-link">pull</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="co"># and copy them a thousand times</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/rep.html">rep</a></span><span class="op">(</span><span class="fl">1000</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="fl">1000</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="co"># then scramble them</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/sample.html">sample</a></span><span class="op">(</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="op">)</span>
|
||||
|
||||
<span class="co"># what do these values look like? They are of class <mo>:</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
|
||||
<span class="co"># Class <mo></span>
|
||||
<span class="co"># [1] B_STPHY_CONS B_ESCHR_COLI B_STPHY_AURS B_STRPT_PYGN B_ESCHR_COLI</span>
|
||||
<span class="co"># [6] B_HMPHL_INFL</span>
|
||||
<span class="co"># [1] B_SERRT_MRCS B_STRPT_ORLS B_STPHY_CPTS B_STPHY_HMNS B_ESCHR_COLI</span>
|
||||
<span class="co"># [6] B_ESCHR_COLI</span>
|
||||
|
||||
<span class="co"># as the example_isolates data set has 2,000 rows, we should have 2 million items</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/length.html">length</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
|
||||
<span class="co"># [1] 2000000</span>
|
||||
|
||||
<span class="co"># and how many unique values do we have?</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html">n_distinct</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html" class="external-link">n_distinct</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
|
||||
<span class="co"># [1] 90</span>
|
||||
|
||||
<span class="co"># now let's see:</span>
|
||||
<span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>,
|
||||
<span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>,
|
||||
times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
|
||||
<span class="co"># Unit: milliseconds</span>
|
||||
<span class="co"># expr min lq mean median uq max neval</span>
|
||||
<span class="co"># mo_name(x) 165 238 258 246 253 369 10</span></code></pre></div>
|
||||
<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.246 seconds. That is 123 nanoseconds on average. You only lose time on your unique input values.</p>
|
||||
<span class="co"># mo_name(x) 190 210 273 248 347 419 10</span></code></pre></div>
|
||||
<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.248 seconds. That is 124 nanoseconds on average. You only lose time on your unique input values.</p>
|
||||
</div>
|
||||
<div id="precalculated-results" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#precalculated-results" class="anchor"></a>Precalculated results</h3>
|
||||
<a href="#precalculated-results" class="anchor" aria-hidden="true"></a>Precalculated results</h3>
|
||||
<p>What about precalculated results? If the input is an already precalculated result of a helper function such as <code><a href="../reference/mo_property.html">mo_name()</a></code>, it almost doesn’t take any time at all. In other words, if you run <code><a href="../reference/mo_property.html">mo_name()</a></code> on a valid taxonomic name, it will return the results immediately (see ‘C’ below):</p>
|
||||
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"STAAUR"</span><span class="op">)</span>,
|
||||
<code class="sourceCode R"><span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"STAAUR"</span><span class="op">)</span>,
|
||||
B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span>,
|
||||
C <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span><span class="op">)</span>,
|
||||
times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
|
||||
<span class="co"># Unit: milliseconds</span>
|
||||
<span class="co"># expr min lq mean median uq max neval</span>
|
||||
<span class="co"># A 8.20 8.33 13.30 8.53 9.71 53.2 10</span>
|
||||
<span class="co"># B 22.80 23.50 29.20 24.60 26.80 69.3 10</span>
|
||||
<span class="co"># C 1.82 2.04 2.25 2.16 2.38 2.9 10</span></code></pre></div>
|
||||
<span class="co"># expr min lq mean median uq max neval</span>
|
||||
<span class="co"># A 8.72 9.35 9.96 10.20 10.40 11.10 10</span>
|
||||
<span class="co"># B 24.20 25.00 31.40 27.10 27.50 77.90 10</span>
|
||||
<span class="co"># C 1.80 1.84 2.20 2.18 2.59 2.67 10</span></code></pre></div>
|
||||
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0022 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
|
||||
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"aureus"</span><span class="op">)</span>,
|
||||
<code class="sourceCode R"><span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"aureus"</span><span class="op">)</span>,
|
||||
B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"Staphylococcus"</span><span class="op">)</span>,
|
||||
C <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span><span class="op">)</span>,
|
||||
D <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_family</a></span><span class="op">(</span><span class="st">"Staphylococcaceae"</span><span class="op">)</span>,
|
||||
@@ -306,22 +308,22 @@
|
||||
G <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_phylum</a></span><span class="op">(</span><span class="st">"Firmicutes"</span><span class="op">)</span>,
|
||||
H <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_kingdom</a></span><span class="op">(</span><span class="st">"Bacteria"</span><span class="op">)</span>,
|
||||
times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
|
||||
<span class="co"># Unit: milliseconds</span>
|
||||
<span class="co"># expr min lq mean median uq max neval</span>
|
||||
<span class="co"># A 1.66 1.70 1.86 1.77 1.90 2.41 10</span>
|
||||
<span class="co"># B 1.61 1.71 1.99 1.84 2.37 2.56 10</span>
|
||||
<span class="co"># C 1.64 1.72 1.79 1.74 1.77 2.14 10</span>
|
||||
<span class="co"># D 1.68 1.71 2.06 2.06 2.23 2.77 10</span>
|
||||
<span class="co"># E 1.63 1.71 1.85 1.75 1.92 2.43 10</span>
|
||||
<span class="co"># F 1.61 1.67 1.80 1.75 1.86 2.22 10</span>
|
||||
<span class="co"># G 1.63 1.67 4.37 1.96 2.58 25.70 10</span>
|
||||
<span class="co"># H 1.67 1.73 1.88 1.83 2.01 2.28 10</span></code></pre></div>
|
||||
<span class="co"># expr min lq mean median uq max neval</span>
|
||||
<span class="co"># A 1.73 1.79 1.89 1.84 1.95 2.31 10</span>
|
||||
<span class="co"># B 1.73 1.75 1.91 1.89 1.99 2.26 10</span>
|
||||
<span class="co"># C 1.76 1.81 1.90 1.83 1.98 2.17 10</span>
|
||||
<span class="co"># D 1.71 1.78 1.97 1.83 2.12 2.77 10</span>
|
||||
<span class="co"># E 1.70 1.74 1.80 1.80 1.85 1.89 10</span>
|
||||
<span class="co"># F 1.73 1.74 1.82 1.77 1.84 2.20 10</span>
|
||||
<span class="co"># G 1.69 1.75 1.91 1.79 1.85 2.70 10</span>
|
||||
<span class="co"># H 1.66 1.74 1.84 1.81 1.82 2.27 10</span></code></pre></div>
|
||||
<p>Of course, when running <code><a href="../reference/mo_property.html">mo_phylum("Firmicutes")</a></code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> anyway, there is no point in calculating the result. And because this package contains all phyla of all known bacteria, it can just return the initial value immediately.</p>
|
||||
</div>
|
||||
<div id="results-in-other-languages" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#results-in-other-languages" class="anchor"></a>Results in other languages</h3>
|
||||
<a href="#results-in-other-languages" class="anchor" aria-hidden="true"></a>Results in other languages</h3>
|
||||
<p>When the system language is non-English and supported by this <code>AMR</code> package, some functions will have a translated result. This almost does’t take extra time:</p>
|
||||
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"en"</span><span class="op">)</span> <span class="co"># or just mo_name("CoNS") on an English system</span>
|
||||
@@ -333,7 +335,7 @@
|
||||
<span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"nl"</span><span class="op">)</span> <span class="co"># or just mo_name("CoNS") on a Dutch system</span>
|
||||
<span class="co"># [1] "Coagulase-negatieve Staphylococcus (CNS)"</span>
|
||||
|
||||
<span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>en <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"en"</span><span class="op">)</span>,
|
||||
<span class="va">run_it</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>en <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"en"</span><span class="op">)</span>,
|
||||
de <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"de"</span><span class="op">)</span>,
|
||||
nl <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"nl"</span><span class="op">)</span>,
|
||||
es <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"es"</span><span class="op">)</span>,
|
||||
@@ -341,16 +343,16 @@
|
||||
fr <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"fr"</span><span class="op">)</span>,
|
||||
pt <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"pt"</span><span class="op">)</span>,
|
||||
times <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">4</span><span class="op">)</span>
|
||||
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">4</span><span class="op">)</span>
|
||||
<span class="co"># Unit: milliseconds</span>
|
||||
<span class="co"># expr min lq mean median uq max neval</span>
|
||||
<span class="co"># en 19.99 20.43 25.64 21.15 22.38 82.52 100</span>
|
||||
<span class="co"># de 31.03 31.96 38.34 32.88 35.27 82.31 100</span>
|
||||
<span class="co"># nl 35.25 36.19 43.25 37.63 39.66 85.19 100</span>
|
||||
<span class="co"># es 35.01 35.85 40.89 36.91 38.58 83.68 100</span>
|
||||
<span class="co"># it 24.35 24.90 30.43 25.81 28.03 78.90 100</span>
|
||||
<span class="co"># fr 23.87 25.02 31.72 26.03 27.46 83.88 100</span>
|
||||
<span class="co"># pt 24.00 24.99 31.16 26.05 28.06 80.74 100</span></code></pre></div>
|
||||
<span class="co"># expr min lq mean median uq max neval</span>
|
||||
<span class="co"># en 20.17 20.83 23.58 21.44 22.59 69.64 100</span>
|
||||
<span class="co"># de 31.48 32.42 42.10 34.02 36.34 204.60 100</span>
|
||||
<span class="co"># nl 35.21 36.63 45.71 37.75 40.25 97.01 100</span>
|
||||
<span class="co"># es 35.09 36.14 43.52 37.44 39.09 90.89 100</span>
|
||||
<span class="co"># it 24.46 25.36 31.24 26.06 28.11 77.93 100</span>
|
||||
<span class="co"># fr 24.11 25.02 29.21 25.70 27.61 74.69 100</span>
|
||||
<span class="co"># pt 24.44 25.27 29.79 26.05 28.12 70.28 100</span></code></pre></div>
|
||||
<p>Currently supported non-English languages are German, Dutch, Spanish, Italian, French and Portuguese.</p>
|
||||
</div>
|
||||
</div>
|
||||
@@ -364,11 +366,13 @@
|
||||
|
||||
|
||||
<footer><div class="copyright">
|
||||
<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/">Alexander 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>
|
||||
<p></p>
|
||||
<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link external-link">Corinna Glasner</a>.</p>
|
||||
</div>
|
||||
|
||||
<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
||||
<p></p>
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link external-link">pkgdown</a> 1.6.1.9001.</p>
|
||||
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|
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
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|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
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Home
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How to
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Predict antimicrobial resistance
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Data sets for download / own use
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Conduct principal component analysis for AMR
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<a href="../articles/MDR.html">
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Determine multi-drug resistance (MDR)
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Work with WHONET data
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</a>
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</li>
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<a href="../articles/SPSS.html">
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<span class="fas fa-file-upload"></span>
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Import data from SPSS/SAS/Stata
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Apply EUCAST rules
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<span class="fas fa-bug"></span>
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Get properties of a microorganism
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Get properties of an antibiotic
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<span class="fas fa-shipping-fast"></span>
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<span class="fa fa-shipping-fast"></span>
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Other: benchmarks
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</a>
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</li>
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<li>
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<a href="../reference/index.html">
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Manual
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<span class="fa fa-users"></span>
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Authors
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</ul>
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<ul class="nav navbar-nav navbar-right">
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<span class="fab fa-github"></span>
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Source Code
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<a href="../survey.html">
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Survey
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||||
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</header><script src="datasets_files/header-attrs-2.8/header-attrs.js"></script><div class="row">
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</header><script src="datasets_files/header-attrs-2.9/header-attrs.js"></script><div class="row">
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<div class="col-md-9 contents">
|
||||
<div class="page-header toc-ignore">
|
||||
<h1 data-toc-skip>Data sets for download / own use</h1>
|
||||
|
||||
<h4 class="date">03 June 2021</h4>
|
||||
<h4 data-toc-skip class="date">23 July 2021</h4>
|
||||
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/datasets.Rmd"><code>vignettes/datasets.Rmd</code></a></small>
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
|
||||
<div class="hidden name"><code>datasets.Rmd</code></div>
|
||||
|
||||
</div>
|
||||
@@ -208,40 +210,40 @@ If you are reading this page from within R, please <a href="https://msberends.gi
|
||||
</p>
|
||||
<div id="microorganisms-currently-accepted-names" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#microorganisms-currently-accepted-names" class="anchor"></a>Microorganisms (currently accepted names)</h2>
|
||||
<a href="#microorganisms-currently-accepted-names" class="anchor" aria-hidden="true"></a>Microorganisms (currently accepted names)</h2>
|
||||
<p>A data set with 70,026 rows and 16 columns, containing the following column names:<br><em>mo</em>, <em>fullname</em>, <em>kingdom</em>, <em>phylum</em>, <em>class</em>, <em>order</em>, <em>family</em>, <em>genus</em>, <em>species</em>, <em>subspecies</em>, <em>rank</em>, <em>ref</em>, <em>species_id</em>, <em>source</em>, <em>prevalence</em> and <em>snomed</em>.</p>
|
||||
<p>This data set is in R available as <code>microorganisms</code>, after you load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 11 March 2021 20:59:32 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.html">here</a>.</p>
|
||||
<p><strong>Direct download links:</strong></p>
|
||||
<ul>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.rds">R file</a> (2.2 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.rds" class="external-link">R file</a> (2.2 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.xlsx">Excel file</a> (6.4 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.xlsx" class="external-link">Excel file</a> (6.4 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.txt">plain text file</a> (14.8 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.txt" class="external-link">plain text file</a> (14.8 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.sas">SAS file</a> (27.4 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.sas" class="external-link">SAS file</a> (27.4 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.sav">SPSS file</a> (27.8 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.sav" class="external-link">SPSS file</a> (27.8 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.dta">Stata file</a> (25.1 MB)</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.dta" class="external-link">Stata file</a> (25.1 MB)</li>
|
||||
</ul>
|
||||
<p><strong>NOTE: The exported files for SAS, SPSS and Stata do not contain SNOMED codes, as their file size would exceed 100 MB; the file size limit of GitHub.</strong> Advice? Use R instead.</p>
|
||||
<div id="source" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#source" class="anchor"></a>Source</h3>
|
||||
<a href="#source" class="anchor" aria-hidden="true"></a>Source</h3>
|
||||
<p>Our full taxonomy of microorganisms is based on the authoritative and comprehensive:</p>
|
||||
<ul>
|
||||
<li>
|
||||
<a href="http://www.catalogueoflife.org">Catalogue of Life</a> (included version: 2019)</li>
|
||||
<a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a> (included version: 2019)</li>
|
||||
<li>
|
||||
<a href="https://lpsn.dsmz.de">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN, last updated: March 2021)</li>
|
||||
<li>US Edition of SNOMED CT from 1 September 2020, retrieved from the <a href="https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009">Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS)</a>, OID 2.16.840.1.114222.4.11.1009, version 12</li>
|
||||
<a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN, last updated: March 2021)</li>
|
||||
<li>US Edition of SNOMED CT from 1 September 2020, retrieved from the <a href="https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009" class="external-link">Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS)</a>, OID 2.16.840.1.114222.4.11.1009, version 12</li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="example-content" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#example-content" class="anchor"></a>Example content</h3>
|
||||
<a href="#example-content" class="anchor" aria-hidden="true"></a>Example content</h3>
|
||||
<p>Included (sub)species per taxonomic kingdom:</p>
|
||||
<table class="table">
|
||||
<thead><tr class="header">
|
||||
@@ -428,39 +430,39 @@ If you are reading this page from within R, please <a href="https://msberends.gi
|
||||
</div>
|
||||
<div id="microorganisms-previously-accepted-names" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#microorganisms-previously-accepted-names" class="anchor"></a>Microorganisms (previously accepted names)</h2>
|
||||
<a href="#microorganisms-previously-accepted-names" class="anchor" aria-hidden="true"></a>Microorganisms (previously accepted names)</h2>
|
||||
<p>A data set with 14,100 rows and 4 columns, containing the following column names:<br><em>fullname</em>, <em>fullname_new</em>, <em>ref</em> and <em>prevalence</em>.</p>
|
||||
<p><strong>Note:</strong> remember that the ‘ref’ columns contains the scientific reference to the old taxonomic entries, i.e. of column <em>‘fullname’</em>. For the scientific reference of the new names, i.e. of column <em>‘fullname_new’</em>, see the <code>microorganisms</code> data set.</p>
|
||||
<p>This data set is in R available as <code>microorganisms.old</code>, after you load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 5 March 2021 09:46:55 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.old.html">here</a>.</p>
|
||||
<p><strong>Direct download links:</strong></p>
|
||||
<ul>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.rds">R file</a> (0.2 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.rds" class="external-link">R file</a> (0.2 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.xlsx">Excel file</a> (0.5 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.xlsx" class="external-link">Excel file</a> (0.5 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.txt">plain text file</a> (0.9 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.txt" class="external-link">plain text file</a> (0.9 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.sas">SAS file</a> (2.1 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.sas" class="external-link">SAS file</a> (2.1 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.sav">SPSS file</a> (2.2 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.sav" class="external-link">SPSS file</a> (2.2 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.dta">Stata file</a> (2 MB)</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.dta" class="external-link">Stata file</a> (2 MB)</li>
|
||||
</ul>
|
||||
<div id="source-1" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#source-1" class="anchor"></a>Source</h3>
|
||||
<a href="#source-1" class="anchor" aria-hidden="true"></a>Source</h3>
|
||||
<p>This data set contains old, previously accepted taxonomic names. The data sources are the same as the <code>microorganisms</code> data set:</p>
|
||||
<ul>
|
||||
<li>
|
||||
<a href="http://www.catalogueoflife.org">Catalogue of Life</a> (included version: 2019)</li>
|
||||
<a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a> (included version: 2019)</li>
|
||||
<li>
|
||||
<a href="https://lpsn.dsmz.de">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN, last updated: March 2021)</li>
|
||||
<a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN, last updated: March 2021)</li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="example-content-1" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#example-content-1" class="anchor"></a>Example content</h3>
|
||||
<a href="#example-content-1" class="anchor" aria-hidden="true"></a>Example content</h3>
|
||||
<p>Example rows when filtering on <em>Escherichia</em>:</p>
|
||||
<table class="table">
|
||||
<thead><tr class="header">
|
||||
@@ -494,39 +496,39 @@ If you are reading this page from within R, please <a href="https://msberends.gi
|
||||
</div>
|
||||
<div id="antibiotic-agents" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#antibiotic-agents" class="anchor"></a>Antibiotic agents</h2>
|
||||
<a href="#antibiotic-agents" class="anchor" aria-hidden="true"></a>Antibiotic agents</h2>
|
||||
<p>A data set with 456 rows and 14 columns, containing the following column names:<br><em>ab</em>, <em>atc</em>, <em>cid</em>, <em>name</em>, <em>group</em>, <em>atc_group1</em>, <em>atc_group2</em>, <em>abbreviations</em>, <em>synonyms</em>, <em>oral_ddd</em>, <em>oral_units</em>, <em>iv_ddd</em>, <em>iv_units</em> and <em>loinc</em>.</p>
|
||||
<p>This data set is in R available as <code>antibiotics</code>, after you load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 4 May 2021 13:38:27 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/antibiotics.html">here</a>.</p>
|
||||
<p>It was last updated on 23 June 2021 13:07:57 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/antibiotics.html">here</a>.</p>
|
||||
<p><strong>Direct download links:</strong></p>
|
||||
<ul>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.rds">R file</a> (32 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.rds" class="external-link">R file</a> (32 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.xlsx">Excel file</a> (65 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.xlsx" class="external-link">Excel file</a> (65 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.txt">plain text file</a> (0.1 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.txt" class="external-link">plain text file</a> (0.1 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.sas">SAS file</a> (1.8 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.sas" class="external-link">SAS file</a> (1.8 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.sav">SPSS file</a> (1.3 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.sav" class="external-link">SPSS file</a> (0.3 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.dta">Stata file</a> (0.3 MB)</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.dta" class="external-link">Stata file</a> (0.3 MB)</li>
|
||||
</ul>
|
||||
<div id="source-2" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#source-2" class="anchor"></a>Source</h3>
|
||||
<a href="#source-2" class="anchor" aria-hidden="true"></a>Source</h3>
|
||||
<p>This data set contains all EARS-Net and ATC codes gathered from WHO and WHONET, and all compound IDs from PubChem. It also contains all brand names (synonyms) as found on PubChem and Defined Daily Doses (DDDs) for oral and parenteral administration.</p>
|
||||
<ul>
|
||||
<li>
|
||||
<a href="https://www.whocc.no/atc_ddd_index/">ATC/DDD index from WHO Collaborating Centre for Drug Statistics Methodology</a> (note: this may not be used for commercial purposes, but is freely available from the WHO CC website for personal use)</li>
|
||||
<li><a href="https://pubchem.ncbi.nlm.nih.gov">PubChem by the US National Library of Medicine</a></li>
|
||||
<li><a href="https://whonet.org">WHONET software 2019</a></li>
|
||||
<a href="https://www.whocc.no/atc_ddd_index/" class="external-link">ATC/DDD index from WHO Collaborating Centre for Drug Statistics Methodology</a> (note: this may not be used for commercial purposes, but is freely available from the WHO CC website for personal use)</li>
|
||||
<li><a href="https://pubchem.ncbi.nlm.nih.gov" class="external-link">PubChem by the US National Library of Medicine</a></li>
|
||||
<li><a href="https://whonet.org" class="external-link">WHONET software 2019</a></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="example-content-2" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#example-content-2" class="anchor"></a>Example content</h3>
|
||||
<table class="table">
|
||||
<a href="#example-content-2" class="anchor" aria-hidden="true"></a>Example content</h3>
|
||||
<table style="width:100%;" class="table">
|
||||
<colgroup>
|
||||
<col width="1%">
|
||||
<col width="2%">
|
||||
@@ -662,37 +664,37 @@ If you are reading this page from within R, please <a href="https://msberends.gi
|
||||
</div>
|
||||
<div id="antiviral-agents" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#antiviral-agents" class="anchor"></a>Antiviral agents</h2>
|
||||
<a href="#antiviral-agents" class="anchor" aria-hidden="true"></a>Antiviral agents</h2>
|
||||
<p>A data set with 102 rows and 9 columns, containing the following column names:<br><em>atc</em>, <em>cid</em>, <em>name</em>, <em>atc_group</em>, <em>synonyms</em>, <em>oral_ddd</em>, <em>oral_units</em>, <em>iv_ddd</em> and <em>iv_units</em>.</p>
|
||||
<p>This data set is in R available as <code>antivirals</code>, after you load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 29 August 2020 19:53:07 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/antibiotics.html">here</a>.</p>
|
||||
<p><strong>Direct download links:</strong></p>
|
||||
<ul>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.rds">R file</a> (5 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.rds" class="external-link">R file</a> (5 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.xlsx">Excel file</a> (14 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.xlsx" class="external-link">Excel file</a> (14 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.txt">plain text file</a> (16 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.txt" class="external-link">plain text file</a> (16 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.sas">SAS file</a> (80 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.sas" class="external-link">SAS file</a> (80 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.sav">SPSS file</a> (68 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.sav" class="external-link">SPSS file</a> (68 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.dta">Stata file</a> (67 kB)</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.dta" class="external-link">Stata file</a> (67 kB)</li>
|
||||
</ul>
|
||||
<div id="source-3" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#source-3" class="anchor"></a>Source</h3>
|
||||
<a href="#source-3" class="anchor" aria-hidden="true"></a>Source</h3>
|
||||
<p>This data set contains all ATC codes gathered from WHO and all compound IDs from PubChem. It also contains all brand names (synonyms) as found on PubChem and Defined Daily Doses (DDDs) for oral and parenteral administration.</p>
|
||||
<ul>
|
||||
<li>
|
||||
<a href="https://www.whocc.no/atc_ddd_index/">ATC/DDD index from WHO Collaborating Centre for Drug Statistics Methodology</a> (note: this may not be used for commercial purposes, but is freely available from the WHO CC website for personal use)</li>
|
||||
<li><a href="https://pubchem.ncbi.nlm.nih.gov">PubChem by the US National Library of Medicine</a></li>
|
||||
<a href="https://www.whocc.no/atc_ddd_index/" class="external-link">ATC/DDD index from WHO Collaborating Centre for Drug Statistics Methodology</a> (note: this may not be used for commercial purposes, but is freely available from the WHO CC website for personal use)</li>
|
||||
<li><a href="https://pubchem.ncbi.nlm.nih.gov" class="external-link">PubChem by the US National Library of Medicine</a></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="example-content-3" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#example-content-3" class="anchor"></a>Example content</h3>
|
||||
<a href="#example-content-3" class="anchor" aria-hidden="true"></a>Example content</h3>
|
||||
<table class="table">
|
||||
<colgroup>
|
||||
<col width="4%">
|
||||
@@ -789,32 +791,32 @@ If you are reading this page from within R, please <a href="https://msberends.gi
|
||||
</div>
|
||||
<div id="intrinsic-bacterial-resistance" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#intrinsic-bacterial-resistance" class="anchor"></a>Intrinsic bacterial resistance</h2>
|
||||
<a href="#intrinsic-bacterial-resistance" class="anchor" aria-hidden="true"></a>Intrinsic bacterial resistance</h2>
|
||||
<p>A data set with 93,892 rows and 2 columns, containing the following column names:<br><em>microorganism</em> and <em>antibiotic</em>.</p>
|
||||
<p>This data set is in R available as <code>intrinsic_resistant</code>, after you load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 5 March 2021 09:46:55 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/intrinsic_resistant.html">here</a>.</p>
|
||||
<p><strong>Direct download links:</strong></p>
|
||||
<ul>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.rds">R file</a> (69 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.rds" class="external-link">R file</a> (69 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.xlsx">Excel file</a> (0.9 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.xlsx" class="external-link">Excel file</a> (0.9 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.txt">plain text file</a> (3.5 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.txt" class="external-link">plain text file</a> (3.5 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.sas">SAS file</a> (7.1 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.sas" class="external-link">SAS file</a> (7.1 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.sav">SPSS file</a> (7.9 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.sav" class="external-link">SPSS file</a> (7.9 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.dta">Stata file</a> (7 MB)</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.dta" class="external-link">Stata file</a> (7 MB)</li>
|
||||
</ul>
|
||||
<div id="source-4" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#source-4" class="anchor"></a>Source</h3>
|
||||
<p>This data set contains all defined intrinsic resistance by EUCAST of all bug-drug combinations, and is based on <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/">‘EUCAST Expert Rules’ and ‘EUCAST Intrinsic Resistance and Unusual Phenotypes’ v3.2</a> (2020).</p>
|
||||
<a href="#source-4" class="anchor" aria-hidden="true"></a>Source</h3>
|
||||
<p>This data set contains all defined intrinsic resistance by EUCAST of all bug-drug combinations, and is based on <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/" class="external-link">‘EUCAST Expert Rules’ and ‘EUCAST Intrinsic Resistance and Unusual Phenotypes’ v3.2</a> (2020).</p>
|
||||
</div>
|
||||
<div id="example-content-4" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#example-content-4" class="anchor"></a>Example content</h3>
|
||||
<a href="#example-content-4" class="anchor" aria-hidden="true"></a>Example content</h3>
|
||||
<p>Example rows when filtering on <em>Enterobacter cloacae</em>:</p>
|
||||
<table class="table">
|
||||
<thead><tr class="header">
|
||||
@@ -1004,32 +1006,32 @@ If you are reading this page from within R, please <a href="https://msberends.gi
|
||||
</div>
|
||||
<div id="interpretation-from-mic-values-disk-diameters-to-rsi" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#interpretation-from-mic-values-disk-diameters-to-rsi" class="anchor"></a>Interpretation from MIC values / disk diameters to R/SI</h2>
|
||||
<p>A data set with 21,996 rows and 10 columns, containing the following column names:<br><em>guideline</em>, <em>method</em>, <em>site</em>, <em>mo</em>, <em>ab</em>, <em>ref_tbl</em>, <em>disk_dose</em>, <em>breakpoint_S</em>, <em>breakpoint_R</em> and <em>uti</em>.</p>
|
||||
<a href="#interpretation-from-mic-values-disk-diameters-to-rsi" class="anchor" aria-hidden="true"></a>Interpretation from MIC values / disk diameters to R/SI</h2>
|
||||
<p>A data set with 22,000 rows and 10 columns, containing the following column names:<br><em>guideline</em>, <em>method</em>, <em>site</em>, <em>mo</em>, <em>ab</em>, <em>ref_tbl</em>, <em>disk_dose</em>, <em>breakpoint_S</em>, <em>breakpoint_R</em> and <em>uti</em>.</p>
|
||||
<p>This data set is in R available as <code>rsi_translation</code>, after you load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 1 June 2021 14:47:11 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/rsi_translation.html">here</a>.</p>
|
||||
<p>It was last updated on 12 July 2021 10:54:20 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/rsi_translation.html">here</a>.</p>
|
||||
<p><strong>Direct download links:</strong></p>
|
||||
<ul>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.rds">R file</a> (37 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.rds" class="external-link">R file</a> (37 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.xlsx">Excel file</a> (0.7 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.xlsx" class="external-link">Excel file</a> (0.7 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.txt">plain text file</a> (1.8 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.txt" class="external-link">plain text file</a> (1.8 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.sas">SAS file</a> (3.8 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.sas" class="external-link">SAS file</a> (3.8 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.sav">SPSS file</a> (2.4 MB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.sav" class="external-link">SPSS file</a> (2.4 MB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.dta">Stata file</a> (3.5 MB)</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.dta" class="external-link">Stata file</a> (3.5 MB)</li>
|
||||
</ul>
|
||||
<div id="source-5" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#source-5" class="anchor"></a>Source</h3>
|
||||
<a href="#source-5" class="anchor" aria-hidden="true"></a>Source</h3>
|
||||
<p>This data set contains interpretation rules for MIC values and disk diffusion diameters. Included guidelines are CLSI (2010-2020) and EUCAST (2011-2021).</p>
|
||||
</div>
|
||||
<div id="example-content-5" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#example-content-5" class="anchor"></a>Example content</h3>
|
||||
<a href="#example-content-5" class="anchor" aria-hidden="true"></a>Example content</h3>
|
||||
<table class="table">
|
||||
<colgroup>
|
||||
<col width="8%">
|
||||
@@ -1134,33 +1136,33 @@ If you are reading this page from within R, please <a href="https://msberends.gi
|
||||
</div>
|
||||
<div id="dosage-guidelines-from-eucast" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#dosage-guidelines-from-eucast" class="anchor"></a>Dosage guidelines from EUCAST</h2>
|
||||
<a href="#dosage-guidelines-from-eucast" class="anchor" aria-hidden="true"></a>Dosage guidelines from EUCAST</h2>
|
||||
<p>A data set with 169 rows and 9 columns, containing the following column names:<br><em>ab</em>, <em>name</em>, <em>type</em>, <em>dose</em>, <em>dose_times</em>, <em>administration</em>, <em>notes</em>, <em>original_txt</em> and <em>eucast_version</em>.</p>
|
||||
<p>This data set is in R available as <code>dosage</code>, after you load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 25 January 2021 20:58:20 UTC. Find more info about the structure of this data set <a href="https://msberends.github.io/AMR/reference/dosage.html">here</a>.</p>
|
||||
<p><strong>Direct download links:</strong></p>
|
||||
<ul>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.rds">R file</a> (3 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.rds" class="external-link">R file</a> (3 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.xlsx">Excel file</a> (14 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.xlsx" class="external-link">Excel file</a> (14 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.txt">plain text file</a> (15 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.txt" class="external-link">plain text file</a> (15 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.sas">SAS file</a> (52 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.sas" class="external-link">SAS file</a> (52 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.sav">SPSS file</a> (45 kB)<br>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.sav" class="external-link">SPSS file</a> (45 kB)<br>
|
||||
</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.dta">Stata file</a> (44 kB)</li>
|
||||
<li>Download as <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/dosage.dta" class="external-link">Stata file</a> (44 kB)</li>
|
||||
</ul>
|
||||
<div id="source-6" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#source-6" class="anchor"></a>Source</h3>
|
||||
<a href="#source-6" class="anchor" aria-hidden="true"></a>Source</h3>
|
||||
<p>EUCAST breakpoints used in this package are based on the dosages in this data set.</p>
|
||||
<p>Currently included dosages in the data set are meant for: <a href="https://www.eucast.org/clinical_breakpoints/">‘EUCAST Clinical Breakpoint Tables’ v11.0</a> (2021).</p>
|
||||
<p>Currently included dosages in the data set are meant for: <a href="https://www.eucast.org/clinical_breakpoints/" class="external-link">‘EUCAST Clinical Breakpoint Tables’ v11.0</a> (2021).</p>
|
||||
</div>
|
||||
<div id="example-content-6" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#example-content-6" class="anchor"></a>Example content</h3>
|
||||
<a href="#example-content-6" class="anchor" aria-hidden="true"></a>Example content</h3>
|
||||
<table class="table">
|
||||
<thead><tr class="header">
|
||||
<th align="center">ab</th>
|
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@@ -1257,11 +1259,13 @@ If you are reading this page from within R, please <a href="https://msberends.gi
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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/">Alexander 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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<p></p>
|
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<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link external-link">Corinna Glasner</a>.</p>
|
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</div>
|
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|
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<div class="pkgdown">
|
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<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
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<p></p>
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<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link external-link">pkgdown</a> 1.6.1.9001.</p>
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</footer>
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@@ -1270,5 +1274,7 @@ If you are reading this page from within R, please <a href="https://msberends.gi
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|
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|
||||
|
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</body>
|
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</html>
|
||||
|
||||
@@ -0,0 +1,12 @@
|
||||
// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
|
||||
// be compatible with the behavior of Pandoc < 2.8).
|
||||
document.addEventListener('DOMContentLoaded', function(e) {
|
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var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
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|
||||
a = h.attributes;
|
||||
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|
||||
}
|
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|
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+29
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|
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<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
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||||
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|
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@@ -81,7 +89,7 @@
|
||||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
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||||
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|
||||
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<span class="fas fa-home"></span>
|
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<span class="fa fa-home"></span>
|
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Home
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</a>
|
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</li>
|
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<li class="dropdown">
|
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
|
||||
<span class="fas fa-question-circle"></span>
|
||||
<span class="fa fa-question-circle"></span>
|
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|
||||
How to
|
||||
|
||||
@@ -105,77 +113,77 @@
|
||||
<ul class="dropdown-menu" role="menu">
|
||||
<li>
|
||||
<a href="../articles/AMR.html">
|
||||
<span class="fas fa-directions"></span>
|
||||
<span class="fa fa-directions"></span>
|
||||
|
||||
Conduct AMR analysis
|
||||
</a>
|
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</li>
|
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<li>
|
||||
<a href="../articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
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<span class="fa fa-dice"></span>
|
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|
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Predict antimicrobial resistance
|
||||
</a>
|
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</li>
|
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<li>
|
||||
<a href="../articles/datasets.html">
|
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<span class="fas fa-database"></span>
|
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<span class="fa fa-database"></span>
|
||||
|
||||
Data sets for download / own use
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
||||
Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
||||
<span class="fa fa-skull-crossbones"></span>
|
||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/WHONET.html">
|
||||
<span class="fas fa-globe-americas"></span>
|
||||
<span class="fa fa-globe-americas"></span>
|
||||
|
||||
Work with WHONET data
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/SPSS.html">
|
||||
<span class="fas fa-file-upload"></span>
|
||||
<span class="fa fa-file-upload"></span>
|
||||
|
||||
Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/EUCAST.html">
|
||||
<span class="fas fa-exchange-alt"></span>
|
||||
<span class="fa fa-exchange-alt"></span>
|
||||
|
||||
Apply EUCAST rules
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
||||
<span class="fa fa-bug"></span>
|
||||
|
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Get properties of a microorganism
|
||||
</a>
|
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</li>
|
||||
<li>
|
||||
<a href="../reference/ab_property.html">
|
||||
<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
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|
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Get properties of an antibiotic
|
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</a>
|
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</li>
|
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<li>
|
||||
<a href="../articles/benchmarks.html">
|
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<span class="fas fa-shipping-fast"></span>
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -184,14 +192,14 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
||||
<span class="fa fa-book-open"></span>
|
||||
|
||||
Manual
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
||||
|
||||
Authors
|
||||
</a>
|
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@@ -214,7 +222,7 @@
|
||||
</li>
|
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<li>
|
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<a href="../survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
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<span class="fa fa-clipboard-list"></span>
|
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|
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Survey
|
||||
</a>
|
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@@ -268,11 +276,11 @@
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|
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<footer>
|
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<div class="copyright">
|
||||
<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/'>Alexander 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>
|
||||
<p><p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link">Corinna Glasner</a>.</p></p>
|
||||
</div>
|
||||
|
||||
<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
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<p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 1.6.1.9001.</p></p>
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</div>
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</footer>
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@@ -281,6 +289,8 @@
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|
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</body>
|
||||
</html>
|
||||
|
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|
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@@ -27,6 +27,8 @@
|
||||
<![endif]-->
|
||||
</head>
|
||||
<body data-spy="scroll" data-target="#toc">
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<div class="container template-article">
|
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<header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
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<div class="container">
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@@ -39,7 +41,7 @@
|
||||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
|
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</div>
|
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|
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@@ -47,14 +49,14 @@
|
||||
<ul class="nav navbar-nav">
|
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<li>
|
||||
<a href="../index.html">
|
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<span class="fas fa-home"></span>
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<span class="fa fa-home"></span>
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Home
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</a>
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|
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<li class="dropdown">
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
|
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<span class="fas fa-question-circle"></span>
|
||||
<span class="fa fa-question-circle"></span>
|
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|
||||
How to
|
||||
|
||||
@@ -63,77 +65,77 @@
|
||||
<ul class="dropdown-menu" role="menu">
|
||||
<li>
|
||||
<a href="../articles/AMR.html">
|
||||
<span class="fas fa-directions"></span>
|
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<span class="fa fa-directions"></span>
|
||||
|
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Conduct AMR analysis
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
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<span class="fa fa-dice"></span>
|
||||
|
||||
Predict antimicrobial resistance
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/datasets.html">
|
||||
<span class="fas fa-database"></span>
|
||||
<span class="fa fa-database"></span>
|
||||
|
||||
Data sets for download / own use
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
||||
Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
||||
<span class="fa fa-skull-crossbones"></span>
|
||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/WHONET.html">
|
||||
<span class="fas fa-globe-americas"></span>
|
||||
<span class="fa fa-globe-americas"></span>
|
||||
|
||||
Work with WHONET data
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/SPSS.html">
|
||||
<span class="fas fa-file-upload"></span>
|
||||
<span class="fa fa-file-upload"></span>
|
||||
|
||||
Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/EUCAST.html">
|
||||
<span class="fas fa-exchange-alt"></span>
|
||||
<span class="fa fa-exchange-alt"></span>
|
||||
|
||||
Apply EUCAST rules
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
||||
<span class="fa fa-bug"></span>
|
||||
|
||||
Get properties of a microorganism
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/ab_property.html">
|
||||
<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
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|
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Get properties of an antibiotic
|
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</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/benchmarks.html">
|
||||
<span class="fas fa-shipping-fast"></span>
|
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<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -142,14 +144,14 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
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<span class="fa fa-book-open"></span>
|
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|
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Manual
|
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</a>
|
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</li>
|
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<li>
|
||||
<a href="../authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
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|
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Authors
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</a>
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@@ -164,7 +166,7 @@
|
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</ul>
|
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<ul class="nav navbar-nav navbar-right">
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<li>
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<a href="https://github.com/msberends/AMR">
|
||||
<a href="https://github.com/msberends/AMR" class="external-link">
|
||||
<span class="fab fa-github"></span>
|
||||
|
||||
Source Code
|
||||
@@ -172,7 +174,7 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
||||
<span class="fa fa-clipboard-list"></span>
|
||||
|
||||
Survey
|
||||
</a>
|
||||
@@ -187,13 +189,13 @@
|
||||
|
||||
|
||||
|
||||
</header><script src="resistance_predict_files/header-attrs-2.8/header-attrs.js"></script><div class="row">
|
||||
</header><script src="resistance_predict_files/header-attrs-2.9/header-attrs.js"></script><div class="row">
|
||||
<div class="col-md-9 contents">
|
||||
<div class="page-header toc-ignore">
|
||||
<h1 data-toc-skip>How to predict antimicrobial resistance</h1>
|
||||
|
||||
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/resistance_predict.Rmd"><code>vignettes/resistance_predict.Rmd</code></a></small>
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/resistance_predict.Rmd" class="external-link"><code>vignettes/resistance_predict.Rmd</code></a></small>
|
||||
<div class="hidden name"><code>resistance_predict.Rmd</code></div>
|
||||
|
||||
</div>
|
||||
@@ -202,20 +204,20 @@
|
||||
|
||||
<div id="needed-r-packages" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#needed-r-packages" class="anchor"></a>Needed R packages</h2>
|
||||
<p>As with many uses in R, we need some additional packages for AMR data analysis. Our package works closely together with the <a href="https://www.tidyverse.org">tidyverse packages</a> <a href="https://dplyr.tidyverse.org/"><code>dplyr</code></a> and <a href="https://ggplot2.tidyverse.org"><code>ggplot2</code></a> by Dr Hadley Wickham. The tidyverse tremendously improves the way we conduct data science - it allows for a very natural way of writing syntaxes and creating beautiful plots in R.</p>
|
||||
<a href="#needed-r-packages" class="anchor" aria-hidden="true"></a>Needed R packages</h2>
|
||||
<p>As with many uses in R, we need some additional packages for AMR data analysis. Our package works closely together with the <a href="https://www.tidyverse.org" class="external-link">tidyverse packages</a> <a href="https://dplyr.tidyverse.org/" class="external-link"><code>dplyr</code></a> and <a href="https://ggplot2.tidyverse.org" class="external-link"><code>ggplot2</code></a> by Dr Hadley Wickham. The tidyverse tremendously improves the way we conduct data science - it allows for a very natural way of writing syntaxes and creating beautiful plots in R.</p>
|
||||
<p>Our <code>AMR</code> package depends on these packages and even extends their use and functions.</p>
|
||||
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org">ggplot2</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
|
||||
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/AMR" class="external-link">AMR</a></span><span class="op">)</span>
|
||||
|
||||
<span class="co"># (if not yet installed, install with:)</span>
|
||||
<span class="co"># install.packages(c("tidyverse", "AMR"))</span></code></pre></div>
|
||||
</div>
|
||||
<div id="prediction-analysis" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#prediction-analysis" class="anchor"></a>Prediction analysis</h2>
|
||||
<a href="#prediction-analysis" class="anchor" aria-hidden="true"></a>Prediction analysis</h2>
|
||||
<p>Our package contains a function <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>, which takes the same input as functions for <a href="./AMR.html">other AMR data analysis</a>. Based on a date column, it calculates cases per year and uses a regression model to predict antimicrobial resistance.</p>
|
||||
<p>It is basically as easy as:</p>
|
||||
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># resistance prediction of piperacillin/tazobactam (TZP):</span></span>
|
||||
@@ -283,11 +285,11 @@
|
||||
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-5-2.png" width="720"></p>
|
||||
<div id="choosing-the-right-model" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#choosing-the-right-model" class="anchor"></a>Choosing the right model</h3>
|
||||
<a href="#choosing-the-right-model" class="anchor" aria-hidden="true"></a>Choosing the right model</h3>
|
||||
<p>Resistance is not easily predicted; if we look at vancomycin resistance in Gram-positive bacteria, the spread (i.e. standard error) is enormous:</p>
|
||||
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">example_isolates</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span>col_ab <span class="op">=</span> <span class="st">"VAN"</span>, year_min <span class="op">=</span> <span class="fl">2010</span>, info <span class="op">=</span> <span class="cn">FALSE</span>, model <span class="op">=</span> <span class="st">"binomial"</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span>
|
||||
<span class="co"># ℹ Using column 'date' as input for `col_date`.</span></code></pre></div>
|
||||
@@ -311,21 +313,21 @@
|
||||
<td>
|
||||
<code>"binomial"</code> or <code>"binom"</code> or <code>"logit"</code>
|
||||
</td>
|
||||
<td><code><a href="https://rdrr.io/r/stats/glm.html">glm(..., family = binomial)</a></code></td>
|
||||
<td><code><a href="https://rdrr.io/r/stats/glm.html" class="external-link">glm(..., family = binomial)</a></code></td>
|
||||
<td>Generalised linear model with binomial distribution</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td>
|
||||
<code>"loglin"</code> or <code>"poisson"</code>
|
||||
</td>
|
||||
<td><code><a href="https://rdrr.io/r/stats/glm.html">glm(..., family = poisson)</a></code></td>
|
||||
<td><code><a href="https://rdrr.io/r/stats/glm.html" class="external-link">glm(..., family = poisson)</a></code></td>
|
||||
<td>Generalised linear model with poisson distribution</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td>
|
||||
<code>"lin"</code> or <code>"linear"</code>
|
||||
</td>
|
||||
<td><code><a href="https://rdrr.io/r/stats/lm.html">lm()</a></code></td>
|
||||
<td><code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm()</a></code></td>
|
||||
<td>Linear model</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
@@ -333,7 +335,7 @@
|
||||
<p>For the vancomycin resistance in Gram-positive bacteria, a linear model might be more appropriate since no binomial distribution is to be expected based on the observed years:</p>
|
||||
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">example_isolates</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span>col_ab <span class="op">=</span> <span class="st">"VAN"</span>, year_min <span class="op">=</span> <span class="fl">2010</span>, info <span class="op">=</span> <span class="cn">FALSE</span>, model <span class="op">=</span> <span class="st">"linear"</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span>
|
||||
<span class="co"># ℹ Using column 'date' as input for `col_date`.</span></code></pre></div>
|
||||
@@ -341,14 +343,14 @@
|
||||
<p>This seems more likely, doesn’t it?</p>
|
||||
<p>The model itself is also available from the object, as an <code>attribute</code>:</p>
|
||||
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">model</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html">attributes</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span><span class="op">$</span><span class="va">model</span>
|
||||
<code class="sourceCode R"><span class="va">model</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html" class="external-link">attributes</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span><span class="op">$</span><span class="va">model</span>
|
||||
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">family</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">family</span>
|
||||
<span class="co"># </span>
|
||||
<span class="co"># Family: binomial </span>
|
||||
<span class="co"># Link function: logit</span>
|
||||
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">coefficients</span>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">coefficients</span>
|
||||
<span class="co"># Estimate Std. Error z value Pr(>|z|)</span>
|
||||
<span class="co"># (Intercept) -200.67944891 46.17315349 -4.346237 1.384932e-05</span>
|
||||
<span class="co"># year 0.09883005 0.02295317 4.305725 1.664395e-05</span></code></pre></div>
|
||||
@@ -367,11 +369,13 @@
|
||||
|
||||
|
||||
<footer><div class="copyright">
|
||||
<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/">Alexander 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>
|
||||
<p></p>
|
||||
<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link external-link">Corinna Glasner</a>.</p>
|
||||
</div>
|
||||
|
||||
<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
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<p></p>
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link external-link">pkgdown</a> 1.6.1.9001.</p>
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</footer>
|
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@@ -380,5 +384,7 @@
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|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -0,0 +1,12 @@
|
||||
// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
|
||||
// be compatible with the behavior of Pandoc < 2.8).
|
||||
document.addEventListener('DOMContentLoaded', function(e) {
|
||||
var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
|
||||
var i, h, a;
|
||||
for (i = 0; i < hs.length; i++) {
|
||||
h = hs[i];
|
||||
if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6
|
||||
a = h.attributes;
|
||||
while (a.length > 0) h.removeAttribute(a[0].name);
|
||||
}
|
||||
});
|
||||
@@ -27,6 +27,8 @@
|
||||
<![endif]-->
|
||||
</head>
|
||||
<body data-spy="scroll" data-target="#toc">
|
||||
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<div class="container template-article">
|
||||
<header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
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<div class="container">
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@@ -39,7 +41,7 @@
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||||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
|
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</div>
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|
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@@ -47,14 +49,14 @@
|
||||
<ul class="nav navbar-nav">
|
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<li>
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<a href="../index.html">
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<span class="fas fa-home"></span>
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<span class="fa fa-home"></span>
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Home
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<li class="dropdown">
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
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<span class="fas fa-question-circle"></span>
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<span class="fa fa-question-circle"></span>
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|
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How to
|
||||
|
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@@ -63,77 +65,77 @@
|
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<ul class="dropdown-menu" role="menu">
|
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<li>
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<a href="../articles/AMR.html">
|
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<span class="fas fa-directions"></span>
|
||||
<span class="fa fa-directions"></span>
|
||||
|
||||
Conduct AMR analysis
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||||
</a>
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</li>
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<li>
|
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<a href="../articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
||||
<span class="fa fa-dice"></span>
|
||||
|
||||
Predict antimicrobial resistance
|
||||
</a>
|
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</li>
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<li>
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<a href="../articles/datasets.html">
|
||||
<span class="fas fa-database"></span>
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<span class="fa fa-database"></span>
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Data sets for download / own use
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</a>
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</li>
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<a href="../articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
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Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
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<li>
|
||||
<a href="../articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
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<span class="fa fa-skull-crossbones"></span>
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||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
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</li>
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<a href="../articles/WHONET.html">
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<span class="fas fa-globe-americas"></span>
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<span class="fa fa-globe-americas"></span>
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Work with WHONET data
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</a>
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<a href="../articles/SPSS.html">
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<span class="fas fa-file-upload"></span>
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<span class="fa fa-file-upload"></span>
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Import data from SPSS/SAS/Stata
|
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</a>
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</li>
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<li>
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<a href="../articles/EUCAST.html">
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<span class="fas fa-exchange-alt"></span>
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<span class="fa fa-exchange-alt"></span>
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||||
Apply EUCAST rules
|
||||
</a>
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</li>
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<li>
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<a href="../reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
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<span class="fa fa-bug"></span>
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||||
Get properties of a microorganism
|
||||
</a>
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</li>
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<a href="../reference/ab_property.html">
|
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<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
||||
|
||||
Get properties of an antibiotic
|
||||
</a>
|
||||
</li>
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||||
<li>
|
||||
<a href="../articles/benchmarks.html">
|
||||
<span class="fas fa-shipping-fast"></span>
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -142,14 +144,14 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
||||
<span class="fa fa-book-open"></span>
|
||||
|
||||
Manual
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
||||
|
||||
Authors
|
||||
</a>
|
||||
@@ -164,7 +166,7 @@
|
||||
</ul>
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li>
|
||||
<a href="https://github.com/msberends/AMR">
|
||||
<a href="https://github.com/msberends/AMR" class="external-link">
|
||||
<span class="fab fa-github"></span>
|
||||
|
||||
Source Code
|
||||
@@ -172,7 +174,7 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="../survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
||||
<span class="fa fa-clipboard-list"></span>
|
||||
|
||||
Survey
|
||||
</a>
|
||||
@@ -187,13 +189,13 @@
|
||||
|
||||
|
||||
|
||||
</header><script src="welcome_to_AMR_files/header-attrs-2.8/header-attrs.js"></script><div class="row">
|
||||
</header><script src="welcome_to_AMR_files/header-attrs-2.9/header-attrs.js"></script><div class="row">
|
||||
<div class="col-md-9 contents">
|
||||
<div class="page-header toc-ignore">
|
||||
<h1 data-toc-skip>Welcome to the AMR package</h1>
|
||||
|
||||
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/welcome_to_AMR.Rmd"><code>vignettes/welcome_to_AMR.Rmd</code></a></small>
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/welcome_to_AMR.Rmd" class="external-link"><code>vignettes/welcome_to_AMR.Rmd</code></a></small>
|
||||
<div class="hidden name"><code>welcome_to_AMR.Rmd</code></div>
|
||||
|
||||
</div>
|
||||
@@ -203,14 +205,14 @@
|
||||
<p><strong>READ ALL VIGNETTES <a href="https://msberends.github.io/AMR/articles/">ON OUR WEBSITE</a>.</strong></p>
|
||||
<div id="welcome-to-the-amr-package" class="section level1">
|
||||
<h1 class="hasAnchor">
|
||||
<a href="#welcome-to-the-amr-package" class="anchor"></a>Welcome to the AMR package</h1>
|
||||
<a href="#welcome-to-the-amr-package" class="anchor" aria-hidden="true"></a>Welcome to the AMR package</h1>
|
||||
<p><code>AMR</code> is a free, open-source and independent R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
|
||||
<p>After installing this package, R knows <strong>~70,000 distinct microbial species</strong> and all <strong>~550 antibiotic, antimycotic and antiviral drugs</strong> by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
|
||||
<p>This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This R package is actively maintained (see Changelog) and is free software (see Copyright).</p>
|
||||
<p>Since its first public release in early 2018, this package has been downloaded from more than 100 countries.</p>
|
||||
<div id="usage-examples" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#usage-examples" class="anchor"></a>Usage examples</h2>
|
||||
<a href="#usage-examples" class="anchor" aria-hidden="true"></a>Usage examples</h2>
|
||||
<p>This package can be used for:</p>
|
||||
<ul>
|
||||
<li>Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the Catalogue of Life and List of Prokaryotic names with Standing in Nomenclature</li>
|
||||
@@ -245,11 +247,13 @@
|
||||
|
||||
|
||||
<footer><div class="copyright">
|
||||
<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/">Alexander 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>
|
||||
<p></p>
|
||||
<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link external-link">Corinna Glasner</a>.</p>
|
||||
</div>
|
||||
|
||||
<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
||||
<p></p>
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link external-link">pkgdown</a> 1.6.1.9001.</p>
|
||||
</div>
|
||||
|
||||
</footer>
|
||||
@@ -258,5 +262,7 @@
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -0,0 +1,12 @@
|
||||
// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
|
||||
// be compatible with the behavior of Pandoc < 2.8).
|
||||
document.addEventListener('DOMContentLoaded', function(e) {
|
||||
var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
|
||||
var i, h, a;
|
||||
for (i = 0; i < hs.length; i++) {
|
||||
h = hs[i];
|
||||
if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6
|
||||
a = h.attributes;
|
||||
while (a.length > 0) h.removeAttribute(a[0].name);
|
||||
}
|
||||
});
|
||||
+30
-19
@@ -54,6 +54,8 @@
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- mathjax -->
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
|
||||
@@ -65,9 +67,15 @@
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<body data-spy="scroll" data-target="#toc">
|
||||
|
||||
|
||||
<div class="container template-citation-authors">
|
||||
<header>
|
||||
<div class="navbar navbar-default navbar-fixed-top" role="navigation">
|
||||
@@ -81,7 +89,7 @@
|
||||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
@@ -89,14 +97,14 @@
|
||||
<ul class="nav navbar-nav">
|
||||
<li>
|
||||
<a href="index.html">
|
||||
<span class="fas fa-home"></span>
|
||||
<span class="fa fa-home"></span>
|
||||
|
||||
Home
|
||||
</a>
|
||||
</li>
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
|
||||
<span class="fas fa-question-circle"></span>
|
||||
<span class="fa fa-question-circle"></span>
|
||||
|
||||
How to
|
||||
|
||||
@@ -105,77 +113,77 @@
|
||||
<ul class="dropdown-menu" role="menu">
|
||||
<li>
|
||||
<a href="articles/AMR.html">
|
||||
<span class="fas fa-directions"></span>
|
||||
<span class="fa fa-directions"></span>
|
||||
|
||||
Conduct AMR analysis
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
||||
<span class="fa fa-dice"></span>
|
||||
|
||||
Predict antimicrobial resistance
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/datasets.html">
|
||||
<span class="fas fa-database"></span>
|
||||
<span class="fa fa-database"></span>
|
||||
|
||||
Data sets for download / own use
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
||||
Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
||||
<span class="fa fa-skull-crossbones"></span>
|
||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/WHONET.html">
|
||||
<span class="fas fa-globe-americas"></span>
|
||||
<span class="fa fa-globe-americas"></span>
|
||||
|
||||
Work with WHONET data
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/SPSS.html">
|
||||
<span class="fas fa-file-upload"></span>
|
||||
<span class="fa fa-file-upload"></span>
|
||||
|
||||
Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/EUCAST.html">
|
||||
<span class="fas fa-exchange-alt"></span>
|
||||
<span class="fa fa-exchange-alt"></span>
|
||||
|
||||
Apply EUCAST rules
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
||||
<span class="fa fa-bug"></span>
|
||||
|
||||
Get properties of a microorganism
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="reference/ab_property.html">
|
||||
<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
||||
|
||||
Get properties of an antibiotic
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/benchmarks.html">
|
||||
<span class="fas fa-shipping-fast"></span>
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
||||
@@ -184,14 +192,14 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
||||
<span class="fa fa-book-open"></span>
|
||||
|
||||
Manual
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
||||
|
||||
Authors
|
||||
</a>
|
||||
@@ -214,7 +222,7 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
||||
<span class="fa fa-clipboard-list"></span>
|
||||
|
||||
Survey
|
||||
</a>
|
||||
@@ -252,6 +260,7 @@ Antimicrobial Resistance Data. Journal of Statistical Software (accepted for pub
|
||||
<h1>Authors</h1>
|
||||
</div>
|
||||
|
||||
|
||||
<ul class="list-unstyled">
|
||||
<li>
|
||||
<p><strong><a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a></strong>. Author, maintainer. <a href='https://orcid.org/0000-0001-7620-1800' target='orcid.widget' aria-label='ORCID'><span class='fab fa-orcid orcid' aria-hidden='true'></span></a>
|
||||
@@ -327,11 +336,11 @@ Antimicrobial Resistance Data. Journal of Statistical Software (accepted for pub
|
||||
|
||||
<footer>
|
||||
<div class="copyright">
|
||||
<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/'>Alexander 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>
|
||||
<p><p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link">Corinna Glasner</a>.</p></p>
|
||||
</div>
|
||||
|
||||
<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
||||
<p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 1.6.1.9001.</p></p>
|
||||
</div>
|
||||
|
||||
</footer>
|
||||
@@ -340,6 +349,8 @@ Antimicrobial Resistance Data. Journal of Statistical Software (accepted for pub
|
||||
|
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|
||||
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -76,6 +76,10 @@ li a[href="#read-more-on-our-website-"] {
|
||||
display: none !important;
|
||||
}
|
||||
|
||||
code {
|
||||
color: black;
|
||||
background-color: #f4f4f4;
|
||||
}
|
||||
/* make colour darker and better readable for links */
|
||||
code a, code a:hover, code a:focus,
|
||||
pre a, pre a:hover, pre a:focus,
|
||||
@@ -92,6 +96,7 @@ a pre[href], a pre[href]:hover, a pre[href]:focus {
|
||||
/* adjusted colour for all real links; having href attribute */
|
||||
color: #128f76;
|
||||
}
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||||
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||||
.ot, .dv, .fl, .cn {
|
||||
/* numbers and TRUE/FALSE */
|
||||
color: slategray;
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+7
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@@ -47,16 +47,19 @@ $(document).ready(function() {
|
||||
$(".template-reference-topic h2#value").text("Returned value");
|
||||
|
||||
// replace \donttest and \dontrun texts in Examples
|
||||
if ($("pre.examples").length > 0) {
|
||||
$("pre.examples").html($("pre.examples").html().replaceAll("# \\donttest{", ""));
|
||||
$("pre.examples").html($("pre.examples").html().replaceAll("# \\dontrun{", ""));
|
||||
$("pre.examples").html($("pre.examples").html().replaceAll("# }", ""));
|
||||
if ($(".ref-examples pre").length > 0) {
|
||||
$(".ref-examples pre").html($(".ref-examples pre").html().replaceAll("# \\donttest{", ""));
|
||||
$(".ref-examples pre").html($(".ref-examples pre").html().replaceAll("# \\dontrun{", ""));
|
||||
$(".ref-examples pre").html($(".ref-examples pre").html().replaceAll("# }", ""));
|
||||
}
|
||||
|
||||
// remove leading newline in code examples on changelog
|
||||
if ($("body .template-news").length > 0) {
|
||||
$("body .template-news").html($("body .template-news").html().replaceAll('sourceCode R">\n<span', 'sourceCode R"><span'));
|
||||
}
|
||||
// change H1 header on dev version on changelog, since pkgdown uses the version number from the installed version
|
||||
// (rather then using the DESCRIPTION file)
|
||||
$("h1[id^=unreleased]").text("Current development version");
|
||||
|
||||
// PR for 'R for Data Science' on How To pages
|
||||
if ($(".template-article").length > 0) {
|
||||
|
||||
+100
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@@ -30,6 +30,8 @@
|
||||
<![endif]-->
|
||||
</head>
|
||||
<body data-spy="scroll" data-target="#toc">
|
||||
|
||||
|
||||
<div class="container template-home">
|
||||
<header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
|
||||
<div class="container">
|
||||
@@ -42,7 +44,7 @@
|
||||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9022</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
@@ -50,14 +52,14 @@
|
||||
<ul class="nav navbar-nav">
|
||||
<li>
|
||||
<a href="index.html">
|
||||
<span class="fas fa-home"></span>
|
||||
<span class="fa fa-home"></span>
|
||||
|
||||
Home
|
||||
</a>
|
||||
</li>
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
|
||||
<span class="fas fa-question-circle"></span>
|
||||
<span class="fa fa-question-circle"></span>
|
||||
|
||||
How to
|
||||
|
||||
@@ -66,77 +68,77 @@
|
||||
<ul class="dropdown-menu" role="menu">
|
||||
<li>
|
||||
<a href="articles/AMR.html">
|
||||
<span class="fas fa-directions"></span>
|
||||
<span class="fa fa-directions"></span>
|
||||
|
||||
Conduct AMR analysis
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/resistance_predict.html">
|
||||
<span class="fas fa-dice"></span>
|
||||
<span class="fa fa-dice"></span>
|
||||
|
||||
Predict antimicrobial resistance
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/datasets.html">
|
||||
<span class="fas fa-database"></span>
|
||||
<span class="fa fa-database"></span>
|
||||
|
||||
Data sets for download / own use
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/PCA.html">
|
||||
<span class="fas fa-compress"></span>
|
||||
<span class="fa fa-compress"></span>
|
||||
|
||||
Conduct principal component analysis for AMR
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/MDR.html">
|
||||
<span class="fas fa-skull-crossbones"></span>
|
||||
<span class="fa fa-skull-crossbones"></span>
|
||||
|
||||
Determine multi-drug resistance (MDR)
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/WHONET.html">
|
||||
<span class="fas fa-globe-americas"></span>
|
||||
<span class="fa fa-globe-americas"></span>
|
||||
|
||||
Work with WHONET data
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/SPSS.html">
|
||||
<span class="fas fa-file-upload"></span>
|
||||
<span class="fa fa-file-upload"></span>
|
||||
|
||||
Import data from SPSS/SAS/Stata
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/EUCAST.html">
|
||||
<span class="fas fa-exchange-alt"></span>
|
||||
<span class="fa fa-exchange-alt"></span>
|
||||
|
||||
Apply EUCAST rules
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="reference/mo_property.html">
|
||||
<span class="fas fa-bug"></span>
|
||||
<span class="fa fa-bug"></span>
|
||||
|
||||
Get properties of a microorganism
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="reference/ab_property.html">
|
||||
<span class="fas fa-capsules"></span>
|
||||
<span class="fa fa-capsules"></span>
|
||||
|
||||
Get properties of an antibiotic
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="articles/benchmarks.html">
|
||||
<span class="fas fa-shipping-fast"></span>
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
||||
Other: benchmarks
|
||||
</a>
|
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@@ -145,14 +147,14 @@
|
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</li>
|
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<li>
|
||||
<a href="reference/index.html">
|
||||
<span class="fas fa-book-open"></span>
|
||||
<span class="fa fa-book-open"></span>
|
||||
|
||||
Manual
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="authors.html">
|
||||
<span class="fas fa-users"></span>
|
||||
<span class="fa fa-users"></span>
|
||||
|
||||
Authors
|
||||
</a>
|
||||
@@ -175,7 +177,7 @@
|
||||
</li>
|
||||
<li>
|
||||
<a href="survey.html">
|
||||
<span class="fas fa-clipboard-list"></span>
|
||||
<span class="fa fa-clipboard-list"></span>
|
||||
|
||||
Survey
|
||||
</a>
|
||||
@@ -194,15 +196,15 @@
|
||||
<div class="contents col-md-9">
|
||||
<div id="amr-for-r-" class="section level1">
|
||||
<div class="page-header"><h1 class="hasAnchor">
|
||||
<a href="#amr-for-r-" class="anchor"></a><code>AMR</code> (for R) <img src="./logo.png" align="right" height="120px">
|
||||
<a href="#amr-for-r-" class="anchor" aria-hidden="true"></a><code>AMR</code> (for R) <img src="./logo.png" align="right" height="120px">
|
||||
</h1></div>
|
||||
<div id="what-is-amr-for-r" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#what-is-amr-for-r" class="anchor"></a>What is <code>AMR</code> (for R)?</h3>
|
||||
<a href="#what-is-amr-for-r" class="anchor" aria-hidden="true"></a>What is <code>AMR</code> (for R)?</h3>
|
||||
<p><em>(To find out how to conduct AMR data analysis, please <a href="./articles/AMR.html">continue reading here to get started</a>.)</em></p>
|
||||
<p><code>AMR</code> is a free, open-source and independent <a href="https://www.r-project.org">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
|
||||
<p><code>AMR</code> is a free, open-source and independent <a href="https://www.r-project.org" class="external-link">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
|
||||
<p>After installing this package, R knows <a href="./reference/microorganisms.html"><strong>~70,000 distinct microbial species</strong></a> and all <a href="./reference/antibiotics.html"><strong>~550 antibiotic, antimycotic and antiviral drugs</strong></a> by name and code (including ATC, EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
|
||||
<p>This package is <a href="https://en.wikipedia.org/wiki/Dependency_hell">fully independent of any other R package</a> and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the <a href="https://www.rug.nl">University of Groningen</a>, in collaboration with non-profit organisations <a href="https://www.certe.nl">Certe Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl">University Medical Center Groningen</a>. This R package is <a href="./news">actively maintained</a> and is free software (see <a href="#copyright">Copyright</a>).</p>
|
||||
<p>This package is <a href="https://en.wikipedia.org/wiki/Dependency_hell" class="external-link">fully independent of any other R package</a> and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the <a href="https://www.rug.nl" class="external-link">University of Groningen</a>, in collaboration with non-profit organisations <a href="https://www.certe.nl" class="external-link">Certe Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>. This R package is <a href="./news">actively maintained</a> and is free software (see <a href="#copyright">Copyright</a>).</p>
|
||||
<div class="main-content" style="display: inline-block;">
|
||||
<p>
|
||||
<a href="./countries_large.png" target="_blank"><img src="./countries.png" class="countries_map"></a> <strong>Used in 162 countries</strong><br> Since its first public release in early 2018, this package has been downloaded from 162 countries. Click the map to enlarge and to see the country names.
|
||||
@@ -210,59 +212,55 @@
|
||||
</div>
|
||||
<div id="with-amr-for-r-theres-always-a-knowledgeable-microbiologist-by-your-side" class="section level5">
|
||||
<h5 class="hasAnchor">
|
||||
<a href="#with-amr-for-r-theres-always-a-knowledgeable-microbiologist-by-your-side" class="anchor"></a>With <code>AMR</code> (for R), there’s always a knowledgeable microbiologist by your side!</h5>
|
||||
<a href="#with-amr-for-r-theres-always-a-knowledgeable-microbiologist-by-your-side" class="anchor" aria-hidden="true"></a>With <code>AMR</code> (for R), there’s always a knowledgeable microbiologist by your side!</h5>
|
||||
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="co"># AMR works great with dplyr, but it's not required or neccesary</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/AMR" class="external-link">AMR</a></span><span class="op">)</span>
|
||||
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span>
|
||||
|
||||
<span class="va">example_isolates</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>bacteria <span class="op">=</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">bacteria</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
|
||||
<span class="co">#> ℹ Using column 'mo' as input for `mo_is_gram_negative()`</span>
|
||||
<span class="co">#> ℹ Using column 'mo' as input for `mo_is_intrinsic_resistant()`</span>
|
||||
<span class="co">#> ℹ Determining intrinsic resistance based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic</span>
|
||||
<span class="co">#> Resistance and Unusual Phenotypes' v3.2 (2020)</span>
|
||||
<span class="co">#> ℹ For `aminoglycosides()` using columns: 'AMK' (amikacin), 'GEN' (gentamicin), 'KAN'</span>
|
||||
<span class="co">#> (kanamycin) and 'TOB' (tobramycin)</span>
|
||||
<span class="co">#> ℹ For `carbapenems()` using columns: 'IPM' (imipenem) and 'MEM' (meropenem)</span></code></pre></div>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>bacteria <span class="op">=</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span>,
|
||||
<span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">bacteria</span>,
|
||||
<span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>,
|
||||
<span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></code></pre></div>
|
||||
<p>With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (<code><a href="reference/mo_property.html">mo_is_gram_negative()</a></code> and <code><a href="reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>) and a column selection on two antibiotic groups (<code><a href="reference/antibiotic_class_selectors.html">aminoglycosides()</a></code> and <code><a href="reference/antibiotic_class_selectors.html">carbapenems()</a></code>), the reference data about <a href="./reference/microorganisms.html">all microorganisms</a> and <a href="./reference/antibiotics.html">all antibiotics</a> in the <code>AMR</code> package make sure you get what you meant:</p>
|
||||
<table class="table">
|
||||
<thead><tr class="header">
|
||||
<th align="left">bacteria</th>
|
||||
<th align="center">AMK</th>
|
||||
<th align="center">GEN</th>
|
||||
<th align="center">KAN</th>
|
||||
<th align="center">TOB</th>
|
||||
<th align="center">AMK</th>
|
||||
<th align="center">KAN</th>
|
||||
<th align="center">IPM</th>
|
||||
<th align="center">MEM</th>
|
||||
</tr></thead>
|
||||
<tbody>
|
||||
<tr class="odd">
|
||||
<td align="left"><em>Pseudomonas aeruginosa</em></td>
|
||||
<td align="center"></td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center"></td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center"></td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left"><em>Pseudomonas aeruginosa</em></td>
|
||||
<td align="center"></td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center"></td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center"></td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left"><em>Pseudomonas aeruginosa</em></td>
|
||||
<td align="center"></td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center"></td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center"></td>
|
||||
</tr>
|
||||
@@ -270,8 +268,8 @@
|
||||
<td align="left"><em>Pseudomonas aeruginosa</em></td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center"></td>
|
||||
<td align="center">S</td>
|
||||
</tr>
|
||||
@@ -279,8 +277,8 @@
|
||||
<td align="left"><em>Pseudomonas aeruginosa</em></td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
</tr>
|
||||
@@ -288,8 +286,8 @@
|
||||
<td align="left"><em>Pseudomonas aeruginosa</em></td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
</tr>
|
||||
@@ -306,8 +304,8 @@
|
||||
<td align="left"><em>Pseudomonas aeruginosa</em></td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center"></td>
|
||||
<td align="center">S</td>
|
||||
</tr>
|
||||
@@ -315,8 +313,8 @@
|
||||
<td align="left"><em>Pseudomonas aeruginosa</em></td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center"></td>
|
||||
<td align="center">S</td>
|
||||
</tr>
|
||||
@@ -324,8 +322,8 @@
|
||||
<td align="left"><em>Pseudomonas aeruginosa</em></td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
</tr>
|
||||
@@ -334,25 +332,25 @@
|
||||
<p>A base R equivalent would be, giving the exact same results:</p>
|
||||
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="va">example_isolates</span><span class="op">$</span><span class="va">bacteria</span> <span class="op"><-</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">mo</span><span class="op">)</span>
|
||||
<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html">which</a></span><span class="op">(</span><span class="fu"><a href="reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span> <span class="op">&</span>
|
||||
<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu"><a href="reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span> <span class="op">&</span>
|
||||
<span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</span>,
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"bacteria"</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">]</span></code></pre></div>
|
||||
<span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"bacteria"</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">]</span></code></pre></div>
|
||||
</div>
|
||||
<div id="partners" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#partners" class="anchor"></a>Partners</h4>
|
||||
<a href="#partners" class="anchor" aria-hidden="true"></a>Partners</h4>
|
||||
<p>The development of this package is part of, related to, or made possible by:</p>
|
||||
<div align="center">
|
||||
<p><a href="https://www.rug.nl" title="University of Groningen"><img src="./logo_rug.png" class="partner_logo"></a> <a href="https://www.umcg.nl" title="University Medical Center Groningen"><img src="./logo_umcg.png" class="partner_logo"></a> <a href="https://www.certe.nl" title="Certe Medical Diagnostics and Advice Foundation"><img src="./logo_certe.png" class="partner_logo"></a> <a href="http://www.eurhealth-1health.eu" title="EurHealth-1-Health"><img src="./logo_eh1h.png" class="partner_logo"></a> <a href="https://www.deutschland-nederland.eu" title="INTERREG"><img src="./logo_interreg.png" class="partner_logo"></a></p>
|
||||
<p><a href="https://www.rug.nl" title="University of Groningen" class="external-link"><img src="./logo_rug.png" class="partner_logo"></a> <a href="https://www.umcg.nl" title="University Medical Center Groningen" class="external-link"><img src="./logo_umcg.png" class="partner_logo"></a> <a href="https://www.certe.nl" title="Certe Medical Diagnostics and Advice Foundation" class="external-link"><img src="./logo_certe.png" class="partner_logo"></a> <a href="http://www.eurhealth-1health.eu" title="EurHealth-1-Health" class="external-link"><img src="./logo_eh1h.png" class="partner_logo"></a> <a href="https://www.deutschland-nederland.eu" title="INTERREG" class="external-link"><img src="./logo_interreg.png" class="partner_logo"></a></p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div id="what-can-you-do-with-this-package" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#what-can-you-do-with-this-package" class="anchor"></a>What can you do with this package?</h3>
|
||||
<a href="#what-can-you-do-with-this-package" class="anchor" aria-hidden="true"></a>What can you do with this package?</h3>
|
||||
<p>This package can be used for:</p>
|
||||
<ul>
|
||||
<li>Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the <a href="http://www.catalogueoflife.org">Catalogue of Life</a> and <a href="https://lpsn.dsmz.de">List of Prokaryotic names with Standing in Nomenclature</a> (<a href="./reference/mo_property.html">manual</a>)</li>
|
||||
<li>Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the <a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a> and <a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with Standing in Nomenclature</a> (<a href="./reference/mo_property.html">manual</a>)</li>
|
||||
<li>Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines (<a href="./reference/as.rsi.html">manual</a>)</li>
|
||||
<li>Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records (<a href="./reference/ab_from_text.html">manual</a>)</li>
|
||||
<li>Determining first isolates to be used for AMR data analysis (<a href="./reference/first_isolate.html">manual</a>)</li>
|
||||
@@ -372,72 +370,72 @@
|
||||
</div>
|
||||
<div id="get-this-package" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#get-this-package" class="anchor"></a>Get this package</h3>
|
||||
<a href="#get-this-package" class="anchor" aria-hidden="true"></a>Get this package</h3>
|
||||
<div id="latest-released-version" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#latest-released-version" class="anchor"></a>Latest released version</h4>
|
||||
<p><a href="https://cran.r-project.org/package=AMR"><img src="https://www.r-pkg.org/badges/version-ago/AMR" alt="CRAN"></a> <a href="https://cran.r-project.org/package=AMR"><img src="https://cranlogs.r-pkg.org/badges/grand-total/AMR" alt="CRANlogs"></a></p>
|
||||
<p>This package is available <a href="https://cran.r-project.org/package=AMR">here on the official R network (CRAN)</a>. Install this package in R from CRAN by using the command:</p>
|
||||
<a href="#latest-released-version" class="anchor" aria-hidden="true"></a>Latest released version</h4>
|
||||
<p><a href="https://cran.r-project.org/package=AMR" class="external-link"><img src="https://www.r-pkg.org/badges/version-ago/AMR" alt="CRAN"></a> <a href="https://cran.r-project.org/package=AMR" class="external-link"><img src="https://cranlogs.r-pkg.org/badges/grand-total/AMR" alt="CRANlogs"></a></p>
|
||||
<p>This package is available <a href="https://cran.r-project.org/package=AMR" class="external-link">here on the official R network (CRAN)</a>. Install this package in R from CRAN by using the command:</p>
|
||||
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span><span class="op">(</span><span class="st">"AMR"</span><span class="op">)</span></code></pre></div>
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"AMR"</span><span class="op">)</span></code></pre></div>
|
||||
<p>It will be downloaded and installed automatically. For RStudio, click on the menu <em>Tools</em> > <em>Install Packages…</em> and then type in “AMR” and press <kbd>Install</kbd>.</p>
|
||||
<p><strong>Note:</strong> Not all functions on this website may be available in this latest release. To use all functions and data sets mentioned on this website, install the latest development version.</p>
|
||||
</div>
|
||||
<div id="latest-development-version" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#latest-development-version" class="anchor"></a>Latest development version</h4>
|
||||
<p><img src="https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master" alt="R-code-check"><img src="https://www.codefactor.io/repository/github/msberends/amr" alt="CodeFactor"><img src="https://codecov.io/gh/msberends/AMR?branch=master" alt="Codecov"></p>
|
||||
<a href="#latest-development-version" class="anchor" aria-hidden="true"></a>Latest development version</h4>
|
||||
<p><a href="https://codecov.io/gh/msberends/AMR?branch=master" class="external-link"><img src="https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master" alt="R-code-check"></a> <a href="https://www.codefactor.io/repository/github/msberends/amr" class="external-link"><img src="https://www.codefactor.io/repository/github/msberends/amr/badge" alt="CodeFactor"></a> <a href="https://codecov.io/gh/msberends/AMR?branch=master" class="external-link"><img src="https://codecov.io/gh/msberends/AMR/branch/master/graph/badge.svg" alt="Codecov"></a></p>
|
||||
<p>The latest and unpublished development version can be installed from GitHub in two ways:</p>
|
||||
<ol>
|
||||
<ol style="list-style-type: decimal">
|
||||
<li>
|
||||
<p>Directly, using:</p>
|
||||
<p>Manually, using:</p>
|
||||
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span><span class="op">(</span><span class="st">"remotes"</span><span class="op">)</span> <span class="co"># if you haven't already</span>
|
||||
<span class="fu">remotes</span><span class="fu">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html">install_github</a></span><span class="op">(</span><span class="st">"msberends/AMR"</span><span class="op">)</span></code></pre></div>
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"remotes"</span><span class="op">)</span> <span class="co"># if you haven't already</span>
|
||||
<span class="fu">remotes</span><span class="fu">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html" class="external-link">install_github</a></span><span class="op">(</span><span class="st">"msberends/AMR"</span><span class="op">)</span></code></pre></div>
|
||||
</li>
|
||||
<li>
|
||||
<p>From the <a href="https://ropensci.org/r-universe/">rOpenSci R-universe platform</a>, by adding <a href="https://msberends.r-universe.dev">our R-universe address</a> to your list of repositories (‘repos’):</p>
|
||||
<p>Automatically, using the <a href="https://ropensci.org/r-universe/" class="external-link">rOpenSci R-universe platform</a>, by adding <a href="https://msberends.r-universe.dev" class="external-link">our R-universe address</a> to your list of repositories (‘repos’):</p>
|
||||
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/base/options.html">options</a></span><span class="op">(</span>repos <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/options.html">getOption</a></span><span class="op">(</span><span class="st">"repos"</span><span class="op">)</span>,
|
||||
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">options</a></span><span class="op">(</span>repos <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"repos"</span><span class="op">)</span>,
|
||||
msberends <span class="op">=</span> <span class="st">"https://msberends.r-universe.dev"</span><span class="op">)</span><span class="op">)</span></code></pre></div>
|
||||
<p>After this, you can install and update this <code>AMR</code> package like any official release (using <code><a href="https://rdrr.io/r/utils/install.packages.html">install.packages("AMR")</a></code> or in RStudio via <em>Tools</em> > <em>Check of Package Updates…</em>).</p>
|
||||
<p>After this, you can install and update this <code>AMR</code> package like any official release (e.g., using <code><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages("AMR")</a></code> or in RStudio via <em>Tools</em> > <em>Check for Package Updates…</em>).</p>
|
||||
</li>
|
||||
</ol>
|
||||
<p>You can also download the latest build from our repository: <a href="https://github.com/msberends/AMR/raw/master/data-raw/AMR_latest.tar.gz" class="uri">https://github.com/msberends/AMR/raw/master/data-raw/AMR_latest.tar.gz</a></p>
|
||||
<p>You can also download the latest build from our repository: <a href="https://github.com/msberends/AMR/raw/master/data-raw/AMR_latest.tar.gz" class="external-link uri">https://github.com/msberends/AMR/raw/master/data-raw/AMR_latest.tar.gz</a></p>
|
||||
</div>
|
||||
</div>
|
||||
<div id="get-started" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#get-started" class="anchor"></a>Get started</h3>
|
||||
<p>To find out how to conduct AMR data analysis, please <a href="./articles/AMR.html">continue reading here to get started</a> or click the links in the ‘How to’ menu.</p>
|
||||
<a href="#get-started" class="anchor" aria-hidden="true"></a>Get started</h3>
|
||||
<p>To find out how to conduct AMR data analysis, please <a href="./articles/AMR.html">continue reading here to get started</a> or click a link in the <a href="https://msberends.github.io/AMR/articles/">‘How to’ menu</a>.</p>
|
||||
</div>
|
||||
<div id="short-introduction" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#short-introduction" class="anchor"></a>Short introduction</h3>
|
||||
<a href="#short-introduction" class="anchor" aria-hidden="true"></a>Short introduction</h3>
|
||||
<div id="microbial-taxonomic-reference-data" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#microbial-taxonomic-reference-data" class="anchor"></a>Microbial (taxonomic) reference data</h4>
|
||||
<p>This package contains the complete taxonomic tree of almost all ~70,000 microorganisms from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org">www.catalogueoflife.org</a>), supplemented by data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, <a href="https://lpsn.dsmz.de">lpsn.dsmz.de</a>). This supplementation is needed until the <a href="https://github.com/Sp2000/colplus">CoL+ project</a> is finished, which we await. With <code><a href="reference/catalogue_of_life_version.html">catalogue_of_life_version()</a></code> can be checked which version of the CoL is included in this package.</p>
|
||||
<a href="#microbial-taxonomic-reference-data" class="anchor" aria-hidden="true"></a>Microbial (taxonomic) reference data</h4>
|
||||
<p>This package contains the complete taxonomic tree of almost all ~70,000 microorganisms from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org" class="external-link">www.catalogueoflife.org</a>), supplemented by data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, <a href="https://lpsn.dsmz.de" class="external-link">lpsn.dsmz.de</a>). This supplementation is needed until the <a href="https://github.com/Sp2000/colplus" class="external-link">CoL+ project</a> is finished, which we await. With <code><a href="reference/catalogue_of_life_version.html">catalogue_of_life_version()</a></code> can be checked which version of the CoL is included in this package.</p>
|
||||
<p>Read more about which data from the Catalogue of Life <a href="./reference/catalogue_of_life.html">in our manual</a>.</p>
|
||||
</div>
|
||||
<div id="antimicrobial-reference-data" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#antimicrobial-reference-data" class="anchor"></a>Antimicrobial reference data</h4>
|
||||
<p>This package contains <strong>all ~550 antibiotic, antimycotic and antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD, oral and IV) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href="https://www.whocc.no" class="uri">https://www.whocc.no</a>) and the <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm">Pharmaceuticals Community Register of the European Commission</a>.</p>
|
||||
<p><strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See <a href="https://www.whocc.no/copyright_disclaimer/" class="uri">https://www.whocc.no/copyright_disclaimer/</a>.</strong></p>
|
||||
<a href="#antimicrobial-reference-data" class="anchor" aria-hidden="true"></a>Antimicrobial reference data</h4>
|
||||
<p>This package contains <strong>all ~550 antibiotic, antimycotic and antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD, oral and IV) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href="https://www.whocc.no" class="external-link uri">https://www.whocc.no</a>) and the <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">Pharmaceuticals Community Register of the European Commission</a>.</p>
|
||||
<p><strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See <a href="https://www.whocc.no/copyright_disclaimer/" class="external-link uri">https://www.whocc.no/copyright_disclaimer/</a>.</strong></p>
|
||||
<p>Read more about the data from WHOCC <a href="./reference/WHOCC.html">in our manual</a>.</p>
|
||||
</div>
|
||||
<div id="whonet--ears-net" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#whonet--ears-net" class="anchor"></a>WHONET / EARS-Net</h4>
|
||||
<a href="#whonet--ears-net" class="anchor" aria-hidden="true"></a>WHONET / EARS-Net</h4>
|
||||
<p>We support WHONET and EARS-Net data. Exported files from WHONET can be imported into R and can be analysed easily using this package. For education purposes, we created an <a href="./reference/WHONET.html">example data set <code>WHONET</code></a> with the exact same structure as a WHONET export file. Furthermore, this package also contains a <a href="./reference/antibiotics.html">data set antibiotics</a> with all EARS-Net antibiotic abbreviations, and knows almost all WHONET abbreviations for microorganisms. When using WHONET data as input for analysis, all input parameters will be set automatically.</p>
|
||||
<p>Read our tutorial about <a href="./articles/WHONET.html">how to work with WHONET data here</a>.</p>
|
||||
</div>
|
||||
<div id="overview-of-functions" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#overview-of-functions" class="anchor"></a>Overview of functions</h4>
|
||||
<a href="#overview-of-functions" class="anchor" aria-hidden="true"></a>Overview of functions</h4>
|
||||
<p>The <code>AMR</code> package basically does four important things:</p>
|
||||
<ol>
|
||||
<ol style="list-style-type: decimal">
|
||||
<li>
|
||||
<p>It <strong>cleanses existing data</strong> by providing new <em>classes</em> for microoganisms, antibiotics and antimicrobial results (both S/I/R and MIC). By installing this package, you teach R everything about microbiology that is needed for analysis. These functions all use intelligent rules to guess results that you would expect:</p>
|
||||
<ul>
|
||||
@@ -450,13 +448,13 @@
|
||||
<li>
|
||||
<p>It <strong>enhances existing data</strong> and <strong>adds new data</strong> from data sets included in this package.</p>
|
||||
<ul>
|
||||
<li>Use <code><a href="reference/eucast_rules.html">eucast_rules()</a></code> to apply <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/">EUCAST expert rules to isolates</a> (not the translation from MIC to R/SI values, use <code><a href="reference/as.rsi.html">as.rsi()</a></code> for that).</li>
|
||||
<li>Use <code><a href="reference/first_isolate.html">first_isolate()</a></code> to identify the first isolates of every patient <a href="https://clsi.org/standards/products/microbiology/documents/m39/">using guidelines from the CLSI</a> (Clinical and Laboratory Standards Institute).
|
||||
<li>Use <code><a href="reference/eucast_rules.html">eucast_rules()</a></code> to apply <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/" class="external-link">EUCAST expert rules to isolates</a> (not the translation from MIC to R/SI values, use <code><a href="reference/as.rsi.html">as.rsi()</a></code> for that).</li>
|
||||
<li>Use <code><a href="reference/first_isolate.html">first_isolate()</a></code> to identify the first isolates of every patient <a href="https://clsi.org/standards/products/microbiology/documents/m39/" class="external-link">using guidelines from the CLSI</a> (Clinical and Laboratory Standards Institute).
|
||||
<ul>
|
||||
<li>You can also identify first <em>weighted</em> isolates of every patient, an adjusted version of the CLSI guideline. This takes into account key antibiotics of every strain and compares them.</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li>Use <code><a href="reference/mdro.html">mdro()</a></code> to determine which micro-organisms are multi-drug resistant organisms (MDRO). It supports a variety of international guidelines, such as the MDR-paper by Magiorakos <em>et al.</em> (2012, <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=21793988">PMID 21793988</a>), the exceptional phenotype definitions of EUCAST and the WHO guideline on multi-drug resistant TB. It also supports the national guidelines of the Netherlands and Germany.</li>
|
||||
<li>Use <code><a href="reference/mdro.html">mdro()</a></code> to determine which micro-organisms are multi-drug resistant organisms (MDRO). It supports a variety of international guidelines, such as the MDR-paper by Magiorakos <em>et al.</em> (2012, <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=21793988" class="external-link">PMID 21793988</a>), the exceptional phenotype definitions of EUCAST and the WHO guideline on multi-drug resistant TB. It also supports the national guidelines of the Netherlands and Germany.</li>
|
||||
<li>The <a href="./reference/microorganisms.html">data set microorganisms</a> contains the complete taxonomic tree of ~70,000 microorganisms. Furthermore, some colloquial names and all Gram stains are available, which enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like <code><a href="reference/mo_property.html">mo_genus()</a></code>, <code><a href="reference/mo_property.html">mo_family()</a></code>, <code><a href="reference/mo_property.html">mo_gramstain()</a></code> or even <code><a href="reference/mo_property.html">mo_phylum()</a></code>. Use <code><a href="reference/mo_property.html">mo_snomed()</a></code> to look up any SNOMED CT code associated with a microorganism. As all these function use <code><a href="reference/as.mo.html">as.mo()</a></code> internally, they also use the same intelligent rules for determination. For example, <code><a href="reference/mo_property.html">mo_genus("MRSA")</a></code> and <code><a href="reference/mo_property.html">mo_genus("S. aureus")</a></code> will both return <code>"Staphylococcus"</code>. They also come with support for German, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data.</li>
|
||||
<li>The <a href="./reference/antibiotics.html">data set antibiotics</a> contains ~450 antimicrobial drugs with their EARS-Net code, ATC code, PubChem compound ID, LOINC code, official name, common LIS codes and DDDs of both oral and parenteral administration. It also contains all (thousands of) trade names found in PubChem. Use functions like <code><a href="reference/ab_property.html">ab_name()</a></code>, <code><a href="reference/ab_property.html">ab_group()</a></code>, <code><a href="reference/ab_property.html">ab_atc()</a></code>, <code><a href="reference/ab_property.html">ab_loinc()</a></code> and <code><a href="reference/ab_property.html">ab_tradenames()</a></code> to look up values. The <code>ab_*</code> functions use <code><a href="reference/as.ab.html">as.ab()</a></code> internally so they support the same intelligent rules to guess the most probable result. For example, <code><a href="reference/ab_property.html">ab_name("Fluclox")</a></code>, <code><a href="reference/ab_property.html">ab_name("Floxapen")</a></code> and <code><a href="reference/ab_property.html">ab_name("J01CF05")</a></code> will all return <code>"Flucloxacillin"</code>. These functions can again be used to add new variables to your data.</li>
|
||||
</ul>
|
||||
@@ -464,7 +462,7 @@
|
||||
<li>
|
||||
<p>It <strong>analyses the data</strong> with convenient functions that use well-known methods.</p>
|
||||
<ul>
|
||||
<li>Calculate the microbial susceptibility or resistance (and even co-resistance) with the <code><a href="reference/proportion.html">susceptibility()</a></code> and <code><a href="reference/proportion.html">resistance()</a></code> functions, or be even more specific with the <code><a href="reference/proportion.html">proportion_R()</a></code>, <code><a href="reference/proportion.html">proportion_IR()</a></code>, <code><a href="reference/proportion.html">proportion_I()</a></code>, <code><a href="reference/proportion.html">proportion_SI()</a></code> and <code><a href="reference/proportion.html">proportion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><a href="reference/count.html">count_resistant()</a></code>, <code><a href="reference/count.html">count_susceptible()</a></code> and <code><a href="reference/count.html">count_all()</a></code> functions. All these functions can be used with the <code>dplyr</code> package (e.g. in conjunction with <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>)</li>
|
||||
<li>Calculate the microbial susceptibility or resistance (and even co-resistance) with the <code><a href="reference/proportion.html">susceptibility()</a></code> and <code><a href="reference/proportion.html">resistance()</a></code> functions, or be even more specific with the <code><a href="reference/proportion.html">proportion_R()</a></code>, <code><a href="reference/proportion.html">proportion_IR()</a></code>, <code><a href="reference/proportion.html">proportion_I()</a></code>, <code><a href="reference/proportion.html">proportion_SI()</a></code> and <code><a href="reference/proportion.html">proportion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><a href="reference/count.html">count_resistant()</a></code>, <code><a href="reference/count.html">count_susceptible()</a></code> and <code><a href="reference/count.html">count_all()</a></code> functions. All these functions can be used with the <code>dplyr</code> package (e.g. in conjunction with <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>)</li>
|
||||
<li>Plot AMR results with <code><a href="reference/ggplot_rsi.html">geom_rsi()</a></code>, a function made for the <code>ggplot2</code> package</li>
|
||||
<li>Predict antimicrobial resistance for the nextcoming years using logistic regression models with the <code><a href="reference/resistance_predict.html">resistance_predict()</a></code> function</li>
|
||||
</ul>
|
||||
@@ -486,7 +484,7 @@
|
||||
</div>
|
||||
<div id="copyright" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#copyright" class="anchor"></a>Copyright</h3>
|
||||
<a href="#copyright" class="anchor" aria-hidden="true"></a>Copyright</h3>
|
||||
<p>This R package is free, open-source software and licensed under the <a href="./LICENSE-text.html">GNU General Public License v2.0 (GPL-2)</a>. In a nutshell, this means that this package:</p>
|
||||
<ul>
|
||||
<li><p>May be used for commercial purposes</p></li>
|
||||
@@ -515,7 +513,7 @@
|
||||
|
||||
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
|
||||
<div class="links">
|
||||
<h2>Links</h2>
|
||||
<h2 data-toc-skip>Links</h2>
|
||||
<ul class="list-unstyled">
|
||||
<li>Download from CRAN at <br><a href="https://cloud.r-project.org/package=AMR">https://cloud.r-project.org/package=AMR</a>
|
||||
</li>
|
||||
@@ -525,22 +523,26 @@
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
|
||||
<div class="license">
|
||||
<h2>License</h2>
|
||||
<h2 data-toc-skip>License</h2>
|
||||
<ul class="list-unstyled">
|
||||
<li>
|
||||
<a href="https://www.r-project.org/Licenses/GPL-2">GPL-2</a> | file <a href="LICENSE-text.html">LICENSE</a>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
|
||||
|
||||
<div class="citation">
|
||||
<h2>Citation</h2>
|
||||
<h2 data-toc-skip>Citation</h2>
|
||||
<ul class="list-unstyled">
|
||||
<li><a href="authors.html">Citing AMR</a></li>
|
||||
</ul>
|
||||
</div>
|
||||
|
||||
<div class="developers">
|
||||
<h2>Developers</h2>
|
||||
<h2 data-toc-skip>Developers</h2>
|
||||
<ul class="list-unstyled">
|
||||
<li>
|
||||
<a href="https://www.rug.nl/staff/m.s.berends/">Matthijs S. Berends</a> <br><small class="roles"> Author, maintainer </small> <a href="https://orcid.org/0000-0001-7620-1800" target="orcid.widget" aria-label="ORCID"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
|
||||
@@ -554,20 +556,24 @@
|
||||
<a href="https://www.rug.nl/staff/c.j.albers/">Casper J. Albers</a> <br><small class="roles"> Author, thesis advisor </small> <a href="https://orcid.org/0000-0002-9213-6743" target="orcid.widget" aria-label="ORCID"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
|
||||
<li>
|
||||
<a href="https://www.rug.nl/staff/c.glasner/">Corinna Glasner</a> <br><small class="roles"> Author, thesis advisor </small> <a href="https://orcid.org/0000-0003-1241-1328" target="orcid.widget" aria-label="ORCID"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
|
||||
<li><a href="authors.html">All authors...</a></li>
|
||||
<li><a href="authors.html">More on authors...</a></li>
|
||||
</ul>
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
||||
<footer><div class="copyright">
|
||||
<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/">Alexander 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>
|
||||
<p></p>
|
||||
<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/" class="external-link">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/" class="external-link">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/" class="external-link">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/" class="external-link">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/" class="external-link">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/" class="external-link">Corinna Glasner</a>.</p>
|
||||
</div>
|
||||
|
||||
<div class="pkgdown">
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
|
||||
<p></p>
|
||||
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 1.6.1.9001.</p>
|
||||
</div>
|
||||
|
||||
</footer>
|
||||
@@ -576,5 +582,7 @@
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
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