add strep groups to ABCG

.github/workflows/check-old.yaml

@@ -49,7 +49,7 @@ jobs:
           # Test all old versions of R >= 3.0, we support them all!
           # For these old versions, dependencies and vignettes will not be checked.
           # For recent R versions, see check-recent.yaml (r-lib and tidyverse support the latest 5 major R releases).
-          - {os: windows-latest, r: '3.5', allowfail: true}
+          # - {os: windows-latest, r: '3.5', allowfail: true} # always fails, horrible with UTF-8
           - {os: ubuntu-latest, r: '3.4', allowfail: false}
           - {os: ubuntu-latest, r: '3.3', allowfail: false}
           - {os: ubuntu-latest, r: '3.2', allowfail: false}

R/sir.R

@@ -941,7 +941,7 @@ as_sir_method <- function(method_short,
     mo_current <- df_unique[i, "mo", drop = TRUE]
     uti_current <- df_unique[i, "uti", drop = TRUE]
     if (is.na(uti_current)) {
-      # preference, so no filter on UTIs
+      # no preference, so no filter on UTIs
       rows <- which(df$mo == mo_current)
     } else {
       rows <- which(df$mo == mo_current & df$uti == uti_current)
@@ -957,10 +957,10 @@ as_sir_method <- function(method_short,
     mo_current_rank <- AMR_env$MO_lookup$rank[match(mo_current, AMR_env$MO_lookup$mo)]
     mo_current_name <- AMR_env$MO_lookup$fullname[match(mo_current, AMR_env$MO_lookup$mo)]
     if (mo_current %in% AMR::microorganisms.groups$mo) {
-      # get the species group
-      mo_current_species_group <- AMR::microorganisms.groups$mo_group[match(mo_current, AMR::microorganisms.groups$mo)]
+      # get the species group (might be more than 1 entry)
+      mo_current_species_group <- AMR::microorganisms.groups$mo_group[which(AMR::microorganisms.groups$mo == mo_current)]
     } else {
-      mo_current_species_group <- mo_current
+      mo_current_species_group <- NULL
     }
     mo_current_other <- structure("UNKNOWN", class = c("mo", "character"))
     # formatted for notes
@@ -977,7 +977,7 @@ as_sir_method <- function(method_short,
     # (this will prefer species breakpoints over order breakpoints)
     breakpoints_current <- breakpoints %pm>%
       subset(mo %in% c(
-        mo_current_genus, mo_current_family,
+        mo_current, mo_current_genus, mo_current_family,
         mo_current_order, mo_current_class,
         mo_current_species_group,
         mo_current_other

data-raw/reproduction_of_clinical_breakpoints.R

@@ -297,6 +297,9 @@ breakpoints_new[which(breakpoints_new$breakpoint_R == 257), "breakpoint_R"] <- 2
 breakpoints_new[which(breakpoints_new$breakpoint_R == 513), "breakpoint_R"] <- 512
 breakpoints_new[which(breakpoints_new$breakpoint_R == 1025), "breakpoint_R"] <- 1024
 
+# fix streptococci in WHONET table of EUCAST: Strep A, B, C and G now includes all streptococci:
+clinical_breakpoints$mo[clinical_breakpoints$mo == "B_STRPT" & clinical_breakpoints$ref_tbl %like% "strep.* a.* b.*c.*g"] <- as.mo("B_STRPT_ABCG")
+
 # WHONET adds one log2 level to the R breakpoint for their software, e.g. in AMC in Enterobacterales:
 # EUCAST 2022 guideline: S <= 8 and R > 8
 #           WHONET file: S <= 8 and R >= 16

data-raw/reproduction_of_microorganisms.groups.R

@@ -112,7 +112,7 @@ microorganisms.groups <- whonet_organisms %>%
                    mo = microorganisms$mo[which(microorganisms$mo %like% "^B_STRPT_SLVR(_|$)")])) %>%
   # and for EUCAST: Strep group A, B, C, G
   bind_rows(tibble(mo_group = as.mo("Streptococcus Group A, B, C, G"),
-                   mo = microorganisms$mo[which(microorganisms$mo %like% "^B_STRPT_(PYGN|AGLC|DYSG|EQUI|CANS)(_|$)")])) %>%
+                   mo = microorganisms$mo[which(microorganisms$mo %like% "^B_STRPT_(PYGN|AGLC|DYSG|EQUI|CANS|GRPA|GRPB|GRPC|GRPG)(_|$)")])) %>%
   # HACEK is:
   # - Haemophilus species
   # - Aggregatibacter species
@@ -133,8 +133,8 @@ microorganisms.groups <- whonet_organisms %>%
   bind_rows(tibble(mo_group = as.mo("B_MYCBC_RGM"),
                    mo = paste("Mycobacterium", c( "abscessus abscessus", "abscessus bolletii", "abscessus massiliense", "agri", "aichiense", "algericum", "alvei", "anyangense", "arabiense", "aromaticivorans", "aubagnense", "aubagnense", "aurum", "austroafricanum", "bacteremicum", "boenickei", "bourgelatii", "brisbanense", "brumae", "canariasense", "celeriflavum", "chelonae", "chitae", "chlorophenolicum", "chubuense", "confluentis", "cosmeticum", "crocinum", "diernhoferi", "duvalii", "elephantis", "fallax", "flavescens", "fluoranthenivorans", "fortuitum", "franklinii", "frederiksbergense", "gadium", "gilvum", "goodii", "hassiacum", "hippocampi", "hodleri", "holsaticum", "houstonense", "immunogenum", "insubricum", "iranicum", "komossense", "litorale", "llatzerense", "madagascariense", "mageritense", "monacense", "moriokaense", "mucogenicum", "mucogenicum", "murale", "neoaurum", "neworleansense", "novocastrense", "obuense", "pallens", "parafortuitum", "peregrinum", "phlei", "phocaicum", "phocaicum", "porcinum", "poriferae", "psychrotolerans", "pyrenivorans", "rhodesiae", "rufum", "rutilum", "salmoniphilum", "sediminis", "senegalense", "septicum", "setense", "smegmatis", "sphagni", "thermoresistibile", "tokaiense", "vaccae", "vanbaalenii", "wolinskyi")) %>% as.mo(keep_synonyms = TRUE))) %>%
   # add full names
-  mutate(mo_group_name = mo_name(mo_group, keep_synonyms = TRUE),
-         mo_name = mo_name(mo, keep_synonyms = TRUE)) %>% 
+  mutate(mo_group_name = mo_name(mo_group, keep_synonyms = TRUE, language = NULL),
+         mo_name = mo_name(mo, keep_synonyms = TRUE, language = NULL)) %>% 
   arrange(mo_group_name, mo_name) %>% 
   filter(mo_group != mo) %>% 
   distinct() %>% 
@@ -146,30 +146,3 @@ class(microorganisms.groups$mo) <- c("mo", "character")
 usethis::use_data(microorganisms.groups, internal = FALSE, overwrite = TRUE, compress = "xz", version = 2)
 rm(microorganisms.groups)
 devtools::load_all()
-
-
-# 
-# microorganisms <- microorganisms %>% 
-#   mutate(mo = as.character(mo)) %>% 
-#   bind_rows(
-#     microorganisms %>% filter(mo == "B_STRPT_HAEM") %>% 
-#       mutate(mo = as.character(mo),
-#              mo = "B_STRPT_ABCG",
-#              fullname = "Streptococcus Group A, B, C, G",
-#              species = "Group A, B, C, G")) %>% 
-#   arrange(fullname) %>% 
-#   dataset_UTF8_to_ASCII()
-# 
-# microorganisms$rank[which(microorganisms$fullname %like% "^Streptococcus Group")] <- "species group"
-# microorganisms$lpsn_parent[which(microorganisms$fullname %like% "^Streptococcus Group")] <- 517118
-# microorganisms$gbif_parent[which(microorganisms$fullname %like% "^Streptococcus Group")] <- 3223465
-# microorganisms$ref[which(microorganisms$fullname %like% "^Streptococcus Group")] <- "Lancefield, 1933"
-# microorganisms$prevalence[which(microorganisms$fullname %like% "^Streptococcus Group")] <- 1.5
-# microorganisms$oxygen_tolerance[which(microorganisms$fullname %like% "^Streptococcus Group")] <- "likely facultative anaerobe"
-# 
-
-
-class(microorganisms$mo) <- c("mo", "character")
-usethis::use_data(microorganisms, internal = FALSE, overwrite = TRUE, compress = "xz", version = 2)
-rm(microorganisms)
-devtools::load_all()

vignettes/datasets.Rmd

@@ -49,7 +49,6 @@ download_txt <- function(filename) {
   excel <- paste0(filename, ".xlsx")
   feather <- paste0(filename, ".feather")
   parquet <- paste0(filename, ".parquet")
-  sas <- paste0(filename, ".sas")
   xpt <- paste0(filename, ".xpt")
   spss <- paste0(filename, ".sav")
   stata <- paste0(filename, ".dta")
@@ -70,7 +69,6 @@ download_txt <- function(filename) {
     file.exists(excel),
     file.exists(feather),
     file.exists(parquet),
-    file.exists(sas),
     file.exists(xpt),
     file.exists(spss),
     file.exists(stata)
@@ -82,7 +80,6 @@ download_txt <- function(filename) {
       create_txt(excel, "xlsx", "Microsoft Excel workbook", file.exists(excel)),
       create_txt(feather, "feather", "Apache Feather file", file.exists(feather)),
       create_txt(parquet, "parquet", "Apache Parquet file", file.exists(parquet)),
-      create_txt(sas, "sas", "SAS data (SAS) file", file.exists(sas)),
       create_txt(xpt, "xpt", "SAS transport (XPT) file", file.exists(xpt)),
       create_txt(spss, "sav", "IBM SPSS Statistics data file", file.exists(spss)),
       create_txt(stata, "dta", "Stata DTA file", file.exists(stata))