check for 2.0

man/AMR.Rd

@@ -30,11 +30,11 @@ 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); \href{https://doi.org/10.18637/jss.v104.i03}{DOI 10.18637/jss.v104.i03}) and formed the basis of two PhD theses (\href{https://doi.org/10.33612/diss.177417131}{DOI 10.33612/diss.177417131} and \href{https://doi.org/10.33612/diss.192486375}{DOI 10.33612/diss.192486375}).
+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}).
 
-After installing this package, R knows \href{https://msberends.github.io/AMR/reference/microorganisms.html}{\strong{~52 000}} (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 breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. 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 breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. 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}.
 
-The \code{AMR} package is available in English, Chinese, Danish, Dutch, French, German, Greek, Italian, Japanese, Polish, Portuguese, Russian, Spanish, Swedish, Turkish and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
+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.
 }
 \section{Reference Data Publicly Available}{
 

man/add_custom_antimicrobials.Rd

@@ -18,7 +18,7 @@ With \code{\link[=add_custom_antimicrobials]{add_custom_antimicrobials()}} you c
 \details{
 \strong{Important:} Due to how \R works, the \code{\link[=add_custom_antimicrobials]{add_custom_antimicrobials()}} function has to be run in every \R session - added antimicrobials are not stored between sessions and are thus lost when \R is exited.
 
-There are two ways to automate this process:
+There are two ways to circumvent this and automate the process of adding antimicrobials:
 
 \strong{Method 1:} Using the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_custom_ab}}, which is the preferred method. To use this method:
 \enumerate{
@@ -32,7 +32,7 @@ options(AMR_custom_ab = "~/my_custom_ab.rds")
 Upon package load, this file will be loaded and run through the \code{\link[=add_custom_antimicrobials]{add_custom_antimicrobials()}} function.
 }
 
-\strong{Method 2:} Loading the antimicrobial additions directly from your \code{.Rprofile} file. An important downside is that this requires the \code{AMR} package to be installed or else this method will fail. To use this method:
+\strong{Method 2:} Loading the antimicrobial additions directly from your \code{.Rprofile} file. Note that the definitions will be stored in a user-specific \R file, which is a suboptimal workflow. To use this method:
 \enumerate{
 \item Edit the \code{.Rprofile} file using e.g. \code{utils::file.edit("~/.Rprofile")}.
 \item Add a text like below and save the file:

man/add_custom_microorganisms.Rd

@@ -20,7 +20,7 @@ This function will fill in missing taxonomy for you, if specific taxonomic colum
 
 \strong{Important:} Due to how \R works, the \code{\link[=add_custom_microorganisms]{add_custom_microorganisms()}} function has to be run in every \R session - added microorganisms are not stored between sessions and are thus lost when \R is exited.
 
-There are two ways to automate this process:
+There are two ways to circumvent this and automate the process of adding microorganisms:
 
 \strong{Method 1:} Using the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_custom_mo}}, which is the preferred method. To use this method:
 \enumerate{
@@ -34,7 +34,7 @@ options(AMR_custom_mo = "~/my_custom_mo.rds")
 Upon package load, this file will be loaded and run through the \code{\link[=add_custom_microorganisms]{add_custom_microorganisms()}} function.
 }
 
-\strong{Method 2:} Loading the microorganism directly from your \code{.Rprofile} file. An important downside is that this requires the \code{AMR} package to be installed or else this method will fail. To use this method:
+\strong{Method 2:} Loading the microorganism directly from your \code{.Rprofile} file. Note that the definitions will be stored in a user-specific \R file, which is a suboptimal workflow. To use this method:
 \enumerate{
 \item Edit the \code{.Rprofile} file using e.g. \code{utils::file.edit("~/.Rprofile")}.
 \item Add a text like below and save the file:
@@ -47,7 +47,7 @@ Upon package load, this file will be loaded and run through the \code{\link[=add
 }\if{html}{\out{</div>}}
 }
 
-Use \code{\link[=clear_custom_microorganisms]{clear_custom_microorganisms()}} to clear the previously added antimicrobials.
+Use \code{\link[=clear_custom_microorganisms]{clear_custom_microorganisms()}} to clear the previously added microorganisms.
 }
 \examples{
 \donttest{

man/antibiotic_class_selectors.Rd

@@ -299,7 +299,7 @@ if (require("dplyr")) {
     select(penicillins()) # only the 'J01CA01' column will be selected
 }
 if (require("dplyr")) {
-  # with recent versions of dplyr this is all equal:
+  # with recent versions of dplyr, this is all equal:
   x <- example_isolates[carbapenems() == "R", ]
   y <- example_isolates \%>\% filter(carbapenems() == "R")
   z <- example_isolates \%>\% filter(if_all(carbapenems(), ~ .x == "R"))
@@ -310,29 +310,33 @@ if (require("dplyr")) {
 # data.table --------------------------------------------------------------
 
 # data.table is supported as well, just use it in the same way as with
-# base R, but add `with = FALSE` if using a single AB selector:
+# base R, but add `with = FALSE` if using a single AB selector.
 
 if (require("data.table")) {
   dt <- as.data.table(example_isolates)
 
-  print(
-    dt[, carbapenems()] # incorrect, returns column *names*
-  )
-  print(
-    dt[, carbapenems(), with = FALSE] # so `with = FALSE` is required
-  )
-  
-  # for multiple selections or AB selectors, `with = FALSE` is not needed:
-  print(
-    dt[, c("mo", aminoglycosides())]
-  )
-  print(
-    dt[, c(carbapenems(), aminoglycosides())]
-  )
-  
-  # row filters are also supported:
-  print(dt[any(carbapenems() == "S"), ])
-  print(dt[any(carbapenems() == "S"), penicillins(), with = FALSE])
+  # this does not work, it returns column *names*
+  dt[, carbapenems()]
+}
+if (require("data.table")) {
+  # so `with = FALSE` is required
+  dt[, carbapenems(), with = FALSE]
+}
+
+# for multiple selections or AB selectors, `with = FALSE` is not needed:
+if (require("data.table")) {
+  dt[, c("mo", aminoglycosides())]
+}
+if (require("data.table")) {
+  dt[, c(carbapenems(), aminoglycosides())]
+}
+
+# row filters are also supported:
+if (require("data.table")) {
+  dt[any(carbapenems() == "S"), ]
+}
+if (require("data.table")) {
+  dt[any(carbapenems() == "S"), penicillins(), with = FALSE]
 }
 }
 }