mirror of https://github.com/msberends/AMR.git
algoritm improvement, removed all Catabacter except for C. hongkongensis
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2
NEWS.md
2
NEWS.md
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@ -25,7 +25,7 @@
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* Introduction to AMR as a vignette
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#### Changed
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* Added 231 microorganisms to the `microorganisms` data set and removed the few viruses it contained, now *n* = 2,669 (2,230 bacteria, 285 fungi/yeasts, 153 parasites, 1 other)
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* Added almost 200 microorganisms to the `microorganisms` data set and removed the few viruses it contained
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* Added three antimicrobial agents to the `antibiotics` data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)
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* Added 163 trade names to the `antibiotics` data set, it now contains 298 different trade names in total, e.g.:
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```r
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4
R/data.R
4
R/data.R
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@ -122,8 +122,8 @@
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#' Data set with human pathogenic microorganisms
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#'
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#' A data set containing 2,669 (potential) human pathogenic microorganisms. MO codes can be looked up using \code{\link{guess_mo}}.
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#' @format A \code{\link{tibble}} with 2,669 observations and 10 variables:
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#' A data set containing 2,630 (potential) human pathogenic microorganisms. MO codes can be looked up using \code{\link{guess_mo}}.
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#' @format A \code{\link{tibble}} with 2,630 observations and 10 variables:
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#' \describe{
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#' \item{\code{mo}}{ID of microorganism}
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#' \item{\code{bactsys}}{Bactsyscode of microorganism}
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21
R/mo.R
21
R/mo.R
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@ -131,7 +131,7 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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# remove 'empty' genus and species values
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x <- gsub("(no MO)", "", x, fixed = TRUE)
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# remove dots and other non-text in case of "E. coli" except spaces
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x <- gsub("[^a-zA-Z0-9 ]+", "", x)
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x <- gsub("[^a-zA-Z0-9/ \\-]+", "", x)
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# but spaces before and after should be omitted
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x <- trimws(x, which = "both")
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x_trimmed <- x
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@ -146,6 +146,12 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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x_withspaces_start <- paste0('^', x_withspaces)
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x_withspaces <- paste0('^', x_withspaces, '$')
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# print(x)
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# print(x_withspaces_all)
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# print(x_withspaces_start)
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# print(x_withspaces)
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# print(x_backup)
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for (i in 1:length(x)) {
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if (identical(x_trimmed[i], "")) {
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# empty values
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@ -195,6 +201,11 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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x[i] <- 'PSEAER'
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next
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}
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if (x_backup[i] %like% '^l.*pneum.*' & !x_backup[i] %like% '^l.*non.*pneum.*') {
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# avoid detection of Legionella non pneumophila in case of Legionella pneumophila
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x[i] <- 'LEGPNE'
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next
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}
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# CoNS and CoPS in different languages (support for German, Dutch, Spanish, Portuguese)
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if (tolower(x[i]) %like% '[ck]oagulas[ea] negatie?[vf]'
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@ -250,6 +261,12 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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x[i] <- found[1L]
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next
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}
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# try the same, now based on genus + species
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found <- MOs[which(paste(MOs$genus, MOs$species) %like% x_withspaces[i]),]$mo
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if (length(found) > 0) {
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x[i] <- found[1L]
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next
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}
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# try any match keeping spaces, not ending with $
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found <- MOs[which(MOs$fullname %like% x_withspaces_start[i]),]$mo
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if (length(found) > 0) {
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@ -329,7 +346,7 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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failures <- failures[!failures %in% c(NA, NULL, NaN)]
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if (length(failures) > 0) {
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warning("These values could not be coerced to a valid mo: ",
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warning("These ", length(failures) , " values could not be coerced to a valid mo: ",
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paste('"', unique(failures), '"', sep = "", collapse = ', '),
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".",
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call. = FALSE)
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@ -159,7 +159,7 @@ mo_shortname <- function(x, Becker = FALSE, Lancefield = FALSE, language = NULL)
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# return G. species
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result <- paste0(substr(mo_genus(x), 1, 1), ". ", suppressWarnings(mo_species(x)))
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}
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result[result %in% c(". ")] <- ""
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result[result %in% c(". ", "(. ")] <- ""
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mo_translate(result, language = language)
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}
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@ -224,6 +224,7 @@ mo_translate <- function(x, language) {
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language == "de" ~ x %>%
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gsub("Coagulase Negative Staphylococcus","Koagulase-negative Staphylococcus", ., fixed = TRUE) %>%
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gsub("Coagulase Positive Staphylococcus","Koagulase-positive Staphylococcus", ., fixed = TRUE) %>%
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gsub("Beta-haemolytic Streptococcus", "Beta-h\u00e4molytischer Streptococcus", ., fixed = TRUE) %>%
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gsub("(no MO)", "(kein MO)", ., fixed = TRUE) %>%
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gsub("Negative rods", "Negative St\u00e4bchen", ., fixed = TRUE) %>%
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gsub("Negative cocci", "Negative Kokken", ., fixed = TRUE) %>%
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@ -244,6 +245,7 @@ mo_translate <- function(x, language) {
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language == "nl" ~ x %>%
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gsub("Coagulase Negative Staphylococcus","Coagulase-negatieve Staphylococcus", ., fixed = TRUE) %>%
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gsub("Coagulase Positive Staphylococcus","Coagulase-positieve Staphylococcus", ., fixed = TRUE) %>%
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gsub("Beta-haemolytic Streptococcus", "Beta-hemolytische Streptococcus", ., fixed = TRUE) %>%
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gsub("(no MO)", "(geen MO)", ., fixed = TRUE) %>%
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gsub("Negative rods", "Negatieve staven", ., fixed = TRUE) %>%
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gsub("Negative cocci", "Negatieve kokken", ., fixed = TRUE) %>%
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@ -264,6 +266,7 @@ mo_translate <- function(x, language) {
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language == "es" ~ x %>%
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gsub("Coagulase Negative Staphylococcus","Staphylococcus coagulasa negativo", ., fixed = TRUE) %>%
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gsub("Coagulase Positive Staphylococcus","Staphylococcus coagulasa positivo", ., fixed = TRUE) %>%
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gsub("Beta-haemolytic Streptococcus", "Streptococcus Beta-hemol\u00edtico", ., fixed = TRUE) %>%
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gsub("(no MO)", "(sin MO)", ., fixed = TRUE) %>%
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gsub("Negative rods", "Bacilos negativos", ., fixed = TRUE) %>%
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gsub("Negative cocci", "Cocos negativos", ., fixed = TRUE) %>%
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@ -284,6 +287,7 @@ mo_translate <- function(x, language) {
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language == "pt" ~ x %>%
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gsub("Coagulase Negative Staphylococcus","Staphylococcus coagulase negativo", ., fixed = TRUE) %>%
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gsub("Coagulase Positive Staphylococcus","Staphylococcus coagulase positivo", ., fixed = TRUE) %>%
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gsub("Beta-haemolytic Streptococcus", "Streptococcus Beta-hemol\u00edtico", ., fixed = TRUE) %>%
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gsub("(no MO)", "(sem MO)", ., fixed = TRUE) %>%
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gsub("Negative rods", "Bacilos negativos", ., fixed = TRUE) %>%
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gsub("Negative cocci", "Cocos negativos", ., fixed = TRUE) %>%
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@ -388,7 +388,7 @@ antibiotics # A tibble: 423 x 18
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# Dataset with bacteria codes and properties like gram stain and
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# aerobic/anaerobic
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microorganisms # A tibble: 2,669 x 10
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microorganisms # A tibble: 2,630 x 10
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```
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## Copyright
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Binary file not shown.
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@ -4,7 +4,7 @@
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\name{microorganisms}
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\alias{microorganisms}
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\title{Data set with human pathogenic microorganisms}
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\format{A \code{\link{tibble}} with 2,669 observations and 10 variables:
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\format{A \code{\link{tibble}} with 2,630 observations and 10 variables:
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\describe{
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\item{\code{mo}}{ID of microorganism}
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\item{\code{bactsys}}{Bactsyscode of microorganism}
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@ -21,7 +21,7 @@
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microorganisms
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}
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\description{
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A data set containing 2,669 (potential) human pathogenic microorganisms. MO codes can be looked up using \code{\link{guess_mo}}.
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A data set containing 2,630 (potential) human pathogenic microorganisms. MO codes can be looked up using \code{\link{guess_mo}}.
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}
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\seealso{
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\code{\link{guess_mo}} \code{\link{antibiotics}} \code{\link{microorganisms.umcg}}
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@ -4,9 +4,7 @@ test_that("as.mo works", {
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library(dplyr)
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MOs <- AMR::microorganisms %>% filter(!is.na(mo))
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expect_identical(as.character(MOs$mo), as.character(as.mo(MOs$mo)))
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expect_identical(MOs$fullname, mo_fullname(MOs$fullname, language = "en"))
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expect_identical(
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as.character(as.mo(c("E. coli", "H. influenzae"))),
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@ -21,6 +19,9 @@ test_that("as.mo works", {
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expect_equal(as.character(as.mo("K. pneu rhino")), "KLEPNERH") # K. pneumoniae subspp. rhinoscleromatis
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expect_equal(as.character(as.mo("Bartonella")), "BAR")
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expect_equal(as.character(as.mo("C. difficile")), "CLODIF")
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expect_equal(as.character(as.mo("L. pneumophila")), "LEGPNE")
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expect_equal(as.character(as.mo("L. non pneumophila")), "LEGNON")
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expect_equal(as.character(as.mo("S. beta-haemolytic")), "STCHAE")
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expect_equal(as.character(as.mo("S. pyo")), "STCPYO") # not Actinomyces pyogenes
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@ -22,4 +22,27 @@ test_that("mo_property works", {
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expect_equal(mo_gramstain("E. coli", language = "nl"), "Negatieve staven")
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expect_error(mo_type("E. coli", language = "INVALID"))
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# test integrity
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library(dplyr)
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MOs <- AMR::microorganisms %>% filter(!is.na(mo))
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expect_identical(MOs$fullname, mo_fullname(MOs$fullname, language = "en"))
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mo_clean <- MOs$mo
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mo_from_shortname <- as.mo(mo_shortname(mo_clean))
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mo_clean <- mo_clean[nchar(mo_from_shortname) == 6 &
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!is.na(mo_from_shortname) &
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!mo_from_shortname %like% "...SPP"]
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mo_from_shortname <- mo_from_shortname[nchar(mo_from_shortname) == 6 &
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!is.na(mo_from_shortname) &
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!mo_from_shortname %like% "...SPP"]
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tb <- tibble(a = substr(mo_clean, 1, 6),
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b = mo_from_shortname,
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c = a == b,
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d = mo_shortname(a),
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e = mo_shortname(b),
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f = d == e)
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expect_gt(sum(tb$c) / nrow(tb), 0.9) # more than 90% of MO code should be identical
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expect_identical(sum(tb$f), nrow(tb)) # all shortnames should be identical
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})
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