(v2.1.1.9123) add EFF code to antibiotics data set

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 2.1.1.9122
-Date: 2024-12-20
+Version: 2.1.1.9123
+Date: 2025-01-15
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)
   data analysis and to work with microbial and antimicrobial properties by

NAMESPACE

@@ -296,6 +296,7 @@ export(not_intrinsic_resistant)
 export(oxazolidinones)
 export(pca)
 export(penicillins)
+export(phenicols)
 export(polymyxins)
 export(proportion_I)
 export(proportion_IR)

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 2.1.1.9122
+# AMR 2.1.1.9123
 
 *(this beta version will eventually become v3.0. We're happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using [the instructions here](https://msberends.github.io/AMR/#latest-development-version).)*
 
@@ -47,8 +47,9 @@ This package now supports not only tools for AMR data analysis in clinical setti
 * `antibiotics` data set
   * Added "clindamycin inducible screening" as `CLI1`. Since clindamycin is a lincosamide, the antibiotic selector `lincosamides()` now contains the argument `only_treatable = TRUE` (similar to other antibiotic selectors that contain non-treatable drugs)
   * Added Amorolfine (`AMO`, D01AE16), which is now also part of the `antifungals()` selector
+  * Added Efflux (`EFF`), to allow mapping to AMRFinderPlus
 * Antibiotic selectors
-  * Added selectors `nitrofurans()` and `rifamycins()`
+  * Added selectors `nitrofurans()`, `phenicols()`, and `rifamycins()`
   * When using antibiotic selectors (such as `aminoglycosides()`) that exclude non-treatable drugs (such as gentamicin-high), the function now always returns a warning that these can be included using `only_treatable = FALSE`
   * All selectors can now be run as a separate command to retrieve a vector of all possible antimicrobials that the selector can select
 * MICs

PythonPackage/AMR/AMR.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
-Metadata-Version: 2.1
+Metadata-Version: 2.2
 Name: AMR
-Version: 2.1.1.9122
+Version: 2.1.1.9123
 Summary: A Python wrapper for the AMR R package
 Home-page: https://github.com/msberends/AMR
 Author: Matthijs Berends
@@ -14,6 +14,17 @@ Description-Content-Type: text/markdown
 Requires-Dist: rpy2
 Requires-Dist: numpy
 Requires-Dist: pandas
+Dynamic: author
+Dynamic: author-email
+Dynamic: classifier
+Dynamic: description
+Dynamic: description-content-type
+Dynamic: home-page
+Dynamic: license
+Dynamic: project-url
+Dynamic: requires-dist
+Dynamic: requires-python
+Dynamic: summary
 
 ---
 title: "AMR for Python"

PythonPackage/AMR/AMR/__init__.py

@@ -47,6 +47,7 @@
 from .functions import nitrofurans
 from .functions import oxazolidinones
 from .functions import penicillins
+from .functions import phenicols
 from .functions import polymyxins
 from .functions import quinolones
 from .functions import rifamycins

PythonPackage/AMR/AMR/functions.py

@@ -171,6 +171,9 @@ def oxazolidinones(only_sir_columns = False, *args, **kwargs):
 def penicillins(only_sir_columns = False, *args, **kwargs):
     """See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
     return convert_to_python(amr_r.penicillins(only_sir_columns = False, *args, **kwargs))
+def phenicols(only_sir_columns = False, *args, **kwargs):
+    """See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
+    return convert_to_python(amr_r.phenicols(only_sir_columns = False, *args, **kwargs))
 def polymyxins(only_sir_columns = False, *args, **kwargs):
     """See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
     return convert_to_python(amr_r.polymyxins(only_sir_columns = False, *args, **kwargs))

PythonPackage/AMR/setup.py

@@ -2,7 +2,7 @@
 
 setup(
     name='AMR',
-    version='2.1.1.9122',
+    version='2.1.1.9123',
     packages=find_packages(),
     install_requires=[
         'rpy2',

R/ab.R

@@ -687,3 +687,30 @@ get_translate_ab <- function(translate_ab) {
     translate_ab
   }
 }
+
+create_AB_AV_lookup <- function(df) {
+  new_df <- df
+  new_df$generalised_name <- generalise_antibiotic_name(new_df$name)
+  new_df$generalised_synonyms <- lapply(new_df$synonyms, generalise_antibiotic_name)
+  if ("abbreviations" %in% colnames(df)) {
+    new_df$generalised_abbreviations <- lapply(new_df$abbreviations, generalise_antibiotic_name)
+  }
+  new_df$generalised_loinc <- lapply(new_df$loinc, generalise_antibiotic_name)
+  new_df$generalised_all <- unname(lapply(
+    as.list(as.data.frame(
+      t(new_df[,
+               c(
+                 colnames(new_df)[colnames(new_df) %in% c("ab", "av", "atc", "cid", "name")],
+                 colnames(new_df)[colnames(new_df) %like% "generalised"]
+               ),
+               drop = FALSE
+      ]),
+      stringsAsFactors = FALSE
+    )),
+    function(x) {
+      x <- generalise_antibiotic_name(unname(unlist(x)))
+      x[x != ""]
+    }
+  ))
+  new_df[, colnames(new_df)[colnames(new_df) %like% "^generalised"]]
+}

R/ab_selectors.R

@@ -48,7 +48,7 @@
 #' `r paste0(" * ", na.omit(sapply(DEFINED_AB_GROUPS, function(ab) ifelse(tolower(gsub("^AB_", "", ab)) %in% ls(envir = asNamespace("AMR")), paste0("[", tolower(gsub("^AB_", "", ab)), "()] can select: \\cr ", vector_and(paste0(ab_name(eval(parse(text = ab), envir = asNamespace("AMR")), language = NULL, tolower = TRUE), " (", eval(parse(text = ab), envir = asNamespace("AMR")), ")"), quotes = FALSE, sort = TRUE)), character(0)), USE.NAMES = FALSE)), "\n", collapse = "")`
 #' @rdname antibiotic_class_selectors
 #' @name antibiotic_class_selectors
-#' @return When used inside selecting or filtering, this returns a [character] vector of column names, with additional class `"ab_selector"`. When used individually, this returns an ['ab' vector][as.ab()] with all possible antimicrobial that the function would be able to select or filter.
+#' @return When used inside selecting or filtering, this returns a [character] vector of column names, with additional class `"ab_selector"`. When used individually, this returns an ['ab' vector][as.ab()] with all possible antimicrobials that the function would be able to select or filter.
 #' @export
 #' @inheritSection AMR Reference Data Publicly Available
 #' @examples
@@ -418,6 +418,13 @@ penicillins <- function(only_sir_columns = FALSE, ...) {
   ab_select_exec("penicillins", only_sir_columns = only_sir_columns)
 }
 
+#' @rdname antibiotic_class_selectors
+#' @export
+phenicols <- function(only_sir_columns = FALSE, ...) {
+  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  ab_select_exec("phenicols", only_sir_columns = only_sir_columns)
+}
+
 #' @rdname antibiotic_class_selectors
 #' @export
 polymyxins <- function(only_sir_columns = FALSE, only_treatable = TRUE, ...) {
@@ -675,17 +682,16 @@ ab_select_exec <- function(function_name,
   }
 
   if (is.null(vars_df)) {
-    # no data found, no antimicrobials, so no input. Can happen if users run e.g. `aminoglycosides()` as a separate command.
+    # no data found, no antimicrobials, so no input. Happens if users run e.g. `aminoglycosides()` as a separate command.
     examples <- paste0(
-      ", e.g.:\n",
       "  ", AMR_env$bullet_icon, " your_data %>% select(", function_name, "())\n",
       "  ", AMR_env$bullet_icon, " your_data %>% select(column_a, column_b, ", function_name, "())\n",
       "  ", AMR_env$bullet_icon, " your_data %>% filter(any(", function_name, "() == \"R\"))\n",
       "  ", AMR_env$bullet_icon, " your_data[, ", function_name, "()]\n",
-      "  ", AMR_env$bullet_icon, " your_data[, c(\"column_a\", \"column_b\", ", function_name, "())]"
-    )
-    message_("The function `" , function_name, "()` should be used inside a `dplyr` verb or `data.frame` call",
-             examples, "\n\nNow returning a vector of all possible antimicrobials that `" , function_name, "()` can select.")
+      "  ", AMR_env$bullet_icon, " your_data[, c(\"column_a\", \"column_b\", ", function_name, "())]")
+    message_("The function `" , function_name, "()` should be used inside a `dplyr` verb or `data.frame` call, e.g.:\n",
+             examples,
+             "\n\nNow returning a vector of all possible antimicrobials that `" , function_name, "()` can select.")
     return(sort(abx))
   }
 

R/zzz.R

@@ -200,10 +200,14 @@ AMR_env$cli_abort <- import_fn("cli_abort", "cli", error_on_fail = FALSE)
   if (pkg_is_available("tibble")) {
     try(loadNamespace("tibble"), silent = TRUE)
   }
-
+  
   # reference data - they have additional data to improve algorithm speed
   # they cannot be part of R/sysdata.rda since CRAN thinks it would make the package too large (+3 MB)
-  AMR_env$AB_lookup <- cbind(AMR::antibiotics, AB_LOOKUP)
+  if (NROW(AB_LOOKUP) != NROW(AMR::antibiotics)) {
+    # antibiotics data set was updated - run create_AB_AV_lookup() again
+    AB_LOOKUP <- create_AB_AV_lookup(AMR::antibiotics)
+  }
+  AMR_env$AB_lookup <- cbind(AMR::antibiotics, AB_LOOKUP)  
   AMR_env$AV_lookup <- cbind(AMR::antivirals, AV_LOOKUP)
 }
 

data-raw/_pre_commit_checks.R

@@ -101,7 +101,7 @@ create_species_cons_cops <- function(type = c("CoNS", "CoPS")) {
   # - Becker et al. 2019, PMID 30872103
   # - Becker et al. 2020, PMID 32056452
   # this function returns class <mo>
-  MO_staph <- AMR::microorganisms
+  MO_staph <- microorganisms
   MO_staph <- MO_staph[which(MO_staph$genus == "Staphylococcus"), , drop = FALSE]
   if (type == "CoNS") {
     MO_staph[
@@ -152,12 +152,12 @@ create_species_cons_cops <- function(type = c("CoNS", "CoPS")) {
 }
 pre_commit_lst$MO_CONS <- create_species_cons_cops("CoNS")
 pre_commit_lst$MO_COPS <- create_species_cons_cops("CoPS")
-pre_commit_lst$MO_STREP_ABCG <- AMR::microorganisms$mo[which(AMR::microorganisms$genus == "Streptococcus" &
-  tolower(AMR::microorganisms$species) %in% c(
+pre_commit_lst$MO_STREP_ABCG <- microorganisms$mo[which(microorganisms$genus == "Streptococcus" &
+  tolower(microorganisms$species) %in% c(
     "pyogenes", "agalactiae", "dysgalactiae", "equi", "canis",
     "group a", "group b", "group c", "group g"
   ))]
-pre_commit_lst$MO_LANCEFIELD <- AMR::microorganisms$mo[which(AMR::microorganisms$mo %like% "^(B_STRPT_PYGN(_|$)|B_STRPT_AGLC(_|$)|B_STRPT_(DYSG|EQUI)(_|$)|B_STRPT_ANGN(_|$)|B_STRPT_(DYSG|CANS)(_|$)|B_STRPT_SNGN(_|$)|B_STRPT_SLVR(_|$))")]
+pre_commit_lst$MO_LANCEFIELD <- microorganisms$mo[which(microorganisms$mo %like% "^(B_STRPT_PYGN(_|$)|B_STRPT_AGLC(_|$)|B_STRPT_(DYSG|EQUI)(_|$)|B_STRPT_ANGN(_|$)|B_STRPT_(DYSG|CANS)(_|$)|B_STRPT_SNGN(_|$)|B_STRPT_SLVR(_|$))")]
 pre_commit_lst$MO_WHO_PRIORITY_GENERA <- c(
   # World Health Organization's (WHO) Priority Pathogen List (some are from the group Enterobacteriaceae)
   "Acinetobacter",
@@ -419,6 +419,9 @@ pre_commit_lst$AB_OXAZOLIDINONES <- antibiotics %>%
 pre_commit_lst$AB_PENICILLINS <- antibiotics %>%
   filter(group %like% "penicillin") %>%
   pull(ab)
+pre_commit_lst$AB_PHENICOLS <- antibiotics %>%
+  filter(group %like% "phenicol" | atc_group1 %like% "phenicol" | atc_group2 %like% "phenicol") %>%
+  pull(ab)
 pre_commit_lst$AB_POLYMYXINS <- antibiotics %>%
   filter(group %like% "polymyxin") %>%
   pull(ab)
@@ -445,34 +448,9 @@ pre_commit_lst$AB_BETALACTAMS_WITH_INHIBITOR <- antibiotics %>%
   pull(ab)
 # this will be used for documentation:
 pre_commit_lst$DEFINED_AB_GROUPS <- sort(names(pre_commit_lst)[names(pre_commit_lst) %like% "^AB_" & names(pre_commit_lst) != "AB_LOOKUP"])
-create_AB_AV_lookup <- function(df) {
-  new_df <- df
-  new_df$generalised_name <- generalise_antibiotic_name(new_df$name)
-  new_df$generalised_synonyms <- lapply(new_df$synonyms, generalise_antibiotic_name)
-  if ("abbreviations" %in% colnames(df)) {
-    new_df$generalised_abbreviations <- lapply(new_df$abbreviations, generalise_antibiotic_name)
-  }
-  new_df$generalised_loinc <- lapply(new_df$loinc, generalise_antibiotic_name)
-  new_df$generalised_all <- unname(lapply(
-    as.list(as.data.frame(
-      t(new_df[,
-        c(
-          colnames(new_df)[colnames(new_df) %in% c("ab", "av", "atc", "cid", "name")],
-          colnames(new_df)[colnames(new_df) %like% "generalised"]
-        ),
-        drop = FALSE
-      ]),
-      stringsAsFactors = FALSE
-    )),
-    function(x) {
-      x <- generalise_antibiotic_name(unname(unlist(x)))
-      x[x != ""]
-    }
-  ))
-  new_df[, colnames(new_df)[colnames(new_df) %like% "^generalised"]]
-}
-pre_commit_lst$AB_LOOKUP <- create_AB_AV_lookup(AMR::antibiotics)
-pre_commit_lst$AV_LOOKUP <- create_AB_AV_lookup(AMR::antivirals)
+
+pre_commit_lst$AB_LOOKUP <- create_AB_AV_lookup(antibiotics)
+pre_commit_lst$AV_LOOKUP <- create_AB_AV_lookup(antivirals)
 
 # Export to package as internal data ----
 # usethis::use_data() must receive unquoted object names, which is not flexible at all.
@@ -521,8 +499,8 @@ changed_md5 <- function(object) {
 
 # give official names to ABs and MOs
 clin_break <- clinical_breakpoints %>%
-  mutate(mo_name = mo_name(mo, language = NULL, keep_synonyms = TRUE, info = FALSE), .after = mo) %>%
-  mutate(ab_name = ab_name(ab, language = NULL), .after = ab)
+  mutate(mo_name = microorganisms$fullname[match(mo, microorganisms$mo)], .after = mo) %>%
+  mutate(ab_name = antibiotics$name[match(ab, antibiotics$ab)], .after = ab)
 if (changed_md5(clin_break)) {
   usethis::ui_info(paste0("Saving {usethis::ui_value('clinical_breakpoints')} to {usethis::ui_value('data-raw/')}"))
   write_md5(clin_break)

data-raw/ab.md5

@@ -1 +1 @@
-6f6b49606c2c51f8344fbb9e186a3ad3
+33a6626c9ac1ca6c5c13ad96588d11e5