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AMR
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v2.1.1

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dr. M.S. (Matthijs) Berends 2023-10-22 15:51:27 +02:00
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commit 4c11a7bd9c
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CRAN-SUBMISSION
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Version: 2.1.0
Date: 2023-07-16 07:05:11 UTC
SHA: 7a4628b73f91aad903f841c4275c8a68eea318b8
Version: 2.1.1
Date: 2023-10-20 16:05:16 UTC
SHA: ca72a646d041f7f096c4e196e8ae2fb2b176019c

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DESCRIPTION
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Package: AMR
Version: 2.1.0.9004
Version: 2.1.1
Date: 2023-10-20
Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR)

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NEWS.md
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# AMR 2.1.0.9004
# AMR 2.1.1
* Fix for selecting first isolates using the phenotype-based method
* This included too many isolates when patients had altering antibiograms within the same bacterial species

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R/aa_amr-package.R
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#'
#' The `AMR` package is a [free and open-source](https://msberends.github.io/AMR/#copyright) R package with [zero dependencies](https://en.wikipedia.org/wiki/Dependency_hell) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. [Many different researchers](https://msberends.github.io/AMR/authors.html) from around the globe are continually helping us to make this a successful and durable project!
#'
#' This work was published in the Journal of Statistical Software (Volume 104(3); \doi{jss.v104.i03}) and formed the basis of two PhD theses (\doi{10.33612/diss.177417131} and \doi{10.33612/diss.192486375}).
#' This work was published in the Journal of Statistical Software (Volume 104(3); \doi{10.18637/jss.v104.i03}) and formed the basis of two PhD theses (\doi{10.33612/diss.177417131} and \doi{10.33612/diss.192486375}).
#'
#' After installing this package, R knows [**`r format_included_data_number(AMR::microorganisms)` microorganisms**](https://msberends.github.io/AMR/reference/microorganisms.html) (updated `r format(TAXONOMY_VERSION$GBIF$accessed_date, "%B %Y")`) and all [**`r format_included_data_number(nrow(AMR::antibiotics) + nrow(AMR::antivirals))` antibiotic, antimycotic and antiviral drugs**](https://msberends.github.io/AMR/reference/antibiotics.html) by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl).
#' After installing this package, R knows [**`r format_included_data_number(AMR::microorganisms)` microorganisms**](https://msberends.github.io/AMR/reference/microorganisms.html) (updated `r format(TAXONOMY_VERSION$GBIF$accessed_date, "%B %Y")`) and all [**`r format_included_data_number(nrow(AMR::antibiotics) + nrow(AMR::antivirals))` antibiotic, antimycotic and antiviral drugs**](https://msberends.github.io/AMR/reference/antibiotics.html) by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the public [University of Groningen](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl).
#'
#' The `AMR` package is available in `r vector_and(vapply(FUN.VALUE = character(1), LANGUAGES_SUPPORTED_NAMES, function(x) x$exonym), quotes = FALSE, sort = FALSE)`. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
#' @section Reference Data Publicly Available:
@ -44,7 +44,7 @@
#' @source
#' To cite AMR in publications use:
#'
#' Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C (2022). "AMR: An R Package for Working with Antimicrobial Resistance Data." _Journal of Statistical Software_, *104*(3), 1-31. \doi{10.18637/jss.v104.i03}.
#' Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C (2022). "AMR: An R Package for Working with Antimicrobial Resistance Data." _Journal of Statistical Software_, *104*(3), 1-31. \doi{10.18637/jss.v104.i03}
#'
#' A BibTeX entry for LaTeX users is:
#'

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R/mic.R
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@ -161,9 +161,6 @@ valid_mic_levels <- c(
#' if (require("ggplot2")) {
#' autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "nl") # Dutch
#' }
#' if (require("ggplot2")) {
#' autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "uk") # Ukrainian
#' }
as.mic <- function(x, na.rm = FALSE) {
meet_criteria(x, allow_NA = TRUE)
meet_criteria(na.rm, allow_class = "logical", has_length = 1)

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R/plot.R
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@ -65,7 +65,7 @@
#' # when providing the microorganism and antibiotic, colours will show interpretations:
#' plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "uk")
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "nl")
#'
#' \donttest{
#' if (require("ggplot2")) {

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_pkgdown.yml
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@ -145,6 +145,12 @@ navbar:
href: "https://github.com/msberends/AMR"
reference:
- title: "Introduction to the package"
desc: >
Please find the introduction to (and some general information about) our package here.
contents:
- "`AMR`"
- title: "Preparing data: microorganisms"
desc: >
These functions are meant to get taxonomically valid properties of microorganisms from any input, but
@ -229,7 +235,6 @@ reference:
Some pages about our package and its external sources. Be sure to read our [How To's](./../articles/index.html)
for more information about how to work with functions in this package.
contents:
- "`AMR`"
- "`example_isolates`"
- "`microorganisms`"
- "`microorganisms.codes`"

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man/AMR.Rd
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\source{
To cite AMR in publications use:
Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C (2022). "AMR: An R Package for Working with Antimicrobial Resistance Data." \emph{Journal of Statistical Software}, \emph{104}(3), 1-31. \doi{10.18637/jss.v104.i03}.
Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C (2022). "AMR: An R Package for Working with Antimicrobial Resistance Data." \emph{Journal of Statistical Software}, \emph{104}(3), 1-31. \doi{10.18637/jss.v104.i03}
A BibTeX entry for LaTeX users is:
@ -30,9 +30,9 @@ Welcome to the \code{AMR} package.
The \code{AMR} package is a \href{https://msberends.github.io/AMR/#copyright}{free and open-source} R package with \href{https://en.wikipedia.org/wiki/Dependency_hell}{zero dependencies} 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} for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. \href{https://msberends.github.io/AMR/authors.html}{Many different researchers} from around the globe are continually helping us to make this a successful and durable project!
This work was published in the Journal of Statistical Software (Volume 104(3); \doi{jss.v104.i03}) and formed the basis of two PhD theses (\doi{10.33612/diss.177417131} and \doi{10.33612/diss.192486375}).
This work was published in the Journal of Statistical Software (Volume 104(3); \doi{10.18637/jss.v104.i03}) and formed the basis of two PhD theses (\doi{10.33612/diss.177417131} and \doi{10.33612/diss.192486375}).
After installing this package, R knows \href{https://msberends.github.io/AMR/reference/microorganisms.html}{\strong{~52 000 microorganisms}} (updated December 2022) and all \href{https://msberends.github.io/AMR/reference/antibiotics.html}{\strong{~600 antibiotic, antimycotic and antiviral drugs}} by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). \strong{It was designed to work in any setting, including those with very limited resources}. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the \href{https://www.rug.nl}{University of Groningen}, in collaboration with non-profit organisations \href{https://www.certe.nl}{Certe Medical Diagnostics and Advice Foundation} and \href{https://www.umcg.nl}{University Medical Center Groningen}.
After installing this package, R knows \href{https://msberends.github.io/AMR/reference/microorganisms.html}{\strong{~52 000 microorganisms}} (updated December 2022) and all \href{https://msberends.github.io/AMR/reference/antibiotics.html}{\strong{~600 antibiotic, antimycotic and antiviral drugs}} by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). \strong{It was designed to work in any setting, including those with very limited resources}. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the public \href{https://www.rug.nl}{University of Groningen}, in collaboration with non-profit organisations \href{https://www.certe.nl}{Certe Medical Diagnostics and Advice Foundation} and \href{https://www.umcg.nl}{University Medical Center Groningen}.
The \code{AMR} package is available in English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
}

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man/as.mic.Rd
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@ -114,9 +114,6 @@ if (require("ggplot2")) {
if (require("ggplot2")) {
autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "nl") # Dutch
}
if (require("ggplot2")) {
autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "uk") # Ukrainian
}
}
\seealso{
\code{\link[=as.sir]{as.sir()}}

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man/plot.Rd
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@ -154,7 +154,7 @@ plot(some_sir_values)
# when providing the microorganism and antibiotic, colours will show interpretations:
plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "uk")
plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "nl")
\donttest{
if (require("ggplot2")) {