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AI improvements for microorganisms

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dr. M.S. (Matthijs) Berends
2018-09-09 12:11:44 +02:00
parent 936198372e
commit 4816419f0c
5 changed files with 39 additions and 37 deletions
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30
R/mo.R
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@ -110,6 +110,7 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
if (NCOL(x) > 2) {
stop('`x` can be 2 columns at most', call. = FALSE)
}
x[is.null(x)] <- NA
# support tidyverse selection like: df %>% select(colA)
if (!is.vector(x)) {
@ -127,6 +128,8 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
x_backup <- x
# translate to English for supported languages of mo_property
x <- gsub("(Gruppe|gruppe|groep|grupo)", "group", x)
# remove 'empty' genus and species values
x <- gsub("(no MO)", "", x, fixed = TRUE)
# remove dots and other non-text in case of "E. coli" except spaces
x <- gsub("[^a-zA-Z0-9 ]+", "", x)
# but spaces before and after should be omitted
@ -144,11 +147,9 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
x_withspaces <- paste0('^', x_withspaces, '$')
for (i in 1:length(x)) {
if (identical(x_trimmed[i], "")) {
# empty values
x[i] <- NA
#failures <- c(failures, x_backup[i])
next
}
if (x_backup[i] %in% AMR::microorganisms$mo) {
@ -161,6 +162,11 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
x[i] <- x_trimmed[i]
next
}
if (x_backup[i] %in% AMR::microorganisms$fullname) {
# is exact match in fullname
x[i] <- AMR::microorganisms[which(AMR::microorganisms$fullname == x_backup[i]), ]$mo[1]
next
}
if (tolower(x[i]) == '^e.*coli$') {
# avoid detection of Entamoeba coli in case of E. coli
@ -173,7 +179,7 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
next
}
if (tolower(x[i]) == '^c.*difficile$') {
# avoid detection of Clostridium difficile in case of C. difficile
# avoid detection of Catabacter difficile in case of C. difficile
x[i] <- 'CLODIF'
next
}
@ -189,16 +195,18 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
x[i] <- 'PSEAER'
next
}
if (tolower(x[i]) %like% 'coagulase negative'
| tolower(x[i]) %like% 'cns'
| tolower(x[i]) %like% 'cons') {
# CoNS and CoPS in different languages (support for German, Dutch, Spanish, Portuguese)
if (tolower(x[i]) %like% '[ck]oagulas[ea] negatie?[vf]'
| tolower(x_trimmed[i]) %like% '[ck]oagulas[ea] negatie?[vf]'
| tolower(x[i]) %like% '[ck]o?ns[^a-z]?$') {
# coerce S. coagulase negative
x[i] <- 'STACNS'
next
}
if (tolower(x[i]) %like% 'coagulase positive'
| tolower(x[i]) %like% 'cps'
| tolower(x[i]) %like% 'cops') {
if (tolower(x[i]) %like% '[ck]oagulas[ea] positie?[vf]'
| tolower(x_trimmed[i]) %like% '[ck]oagulas[ea] positie?[vf]'
| tolower(x[i]) %like% '[ck]o?ps[^a-z]?$') {
# coerce S. coagulase positive
x[i] <- 'STACPS'
next
@ -381,6 +389,10 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
x[x == "STCSAL"] <- "STCGRK" # S. salivarius
}
# for the returned genera without species (like "ESC"), add species (like "ESCSPP") where the input contained it
indices <- unique(x_input) %like% "[A-Z]{3}SPP" & !x %like% "[A-Z]{3}SPP"
x[indices] <- paste0(x[indices], 'SPP')
# left join the found results to the original input values (x_input)
df_found <- data.frame(input = as.character(unique(x_input)),
found = x,