v2.1.1

CRAN-SUBMISSION

@@ -1,3 +1,3 @@
-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

DESCRIPTION

@@ -1,5 +1,5 @@
 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)

NEWS.md

@@ -1,4 +1,4 @@
-# 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

R/aa_amr-package.R

@@ -34,17 +34,17 @@
 #'
 #' 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:
 #' All data sets in this `AMR` package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
 #' @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:
 #'

R/mic.R

@@ -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)

R/plot.R

@@ -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")) {

_pkgdown.yml

@@ -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`"