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added prevalence column and alterted as.mo algorith to use it, added ab_name as alias

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dr. M.S. (Matthijs) Berends
2018-09-16 16:43:29 +02:00
parent b0ca49d68d
commit b792a2754e
16 changed files with 101 additions and 79 deletions
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49
R/mo.R
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@ -33,12 +33,12 @@
#'
#' Use the \code{\link{mo_property}} functions to get properties based on the returned code, see Examples.
#'
#' Some exceptions have been built in to get more logical results, based on prevalence of human pathogens. These are:
#' Thus function uses Artificial Intelligence (AI) to help getting more logical results, based on type of input and known prevalence of human pathogens. For example:
#' \itemize{
#' \item{\code{"E. coli"} will return the ID of \emph{Escherichia coli} and not \emph{Entamoeba coli}, although the latter would alphabetically come first}
#' \item{\code{"H. influenzae"} will return the ID of \emph{Haemophilus influenzae} and not \emph{Haematobacter influenzae}}
#' \item{\code{"H. influenzae"} will return the ID of \emph{Haemophilus influenzae} and not \emph{Haematobacter influenzae} for the same reason}
#' \item{Something like \code{"p aer"} will return the ID of \emph{Pseudomonas aeruginosa} and not \emph{Pasteurella aerogenes}}
#' \item{Something like \code{"stau"} or \code{"staaur"} will return the ID of \emph{Staphylococcus aureus} and not \emph{Staphylococcus auricularis}}
#' \item{Something like \code{"stau"} or \code{"S aur"} will return the ID of \emph{Staphylococcus aureus} and not \emph{Staphylococcus auricularis}}
#' }
#' Moreover, this function also supports ID's based on only Gram stain, when the species is not known. \cr
#' For example, \code{"Gram negative rods"} and \code{"GNR"} will both return the ID of a Gram negative rod: \code{GNR}.
@ -47,7 +47,7 @@
#'
#' [2] Lancefield RC \strong{A serological differentiation of human and other groups of hemolytic streptococci}. 1933. J Exp Med. 57(4): 571–95. \url{https://dx.doi.org/10.1084/jem.57.4.571}
#' @export
#' @importFrom dplyr %>% pull left_join
#' @importFrom dplyr %>% pull left_join arrange
#' @return Character (vector) with class \code{"mo"}. Unknown values will return \code{NA}.
#' @seealso \code{\link{microorganisms}} for the dataframe that is being used to determine ID's.
#' @examples
@ -118,7 +118,10 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
}
}
MOs <- AMR::microorganisms %>% filter(!mo %like% '^_FAM') # dont search in those
MOs <- AMR::microorganisms %>%
arrange(prevalence) %>% # more expected result on multiple findings
filter(!mo %like% '^_FAM', # don't search in those
(nchar(mo) > 3 | mo %in% c("GNR", "GPR", "GNC", "GPC"))) # no genera
failures <- character(0)
x_input <- x
@ -144,11 +147,11 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
x_withspaces_start <- paste0('^', x_withspaces)
x_withspaces <- paste0('^', x_withspaces, '$')
# print(x)
# print(x_withspaces_all)
# print(x_withspaces_start)
# print(x_withspaces)
# print(x_backup)
# cat(paste0('x "', x, '"\n'))
# cat(paste0('x_withspaces_all "', x_withspaces_all, '"\n'))
# cat(paste0('x_withspaces_start "', x_withspaces_start, '"\n'))
# cat(paste0('x_withspaces "', x_withspaces, '"\n'))
# cat(paste0('x_backup "', x_backup, '"\n'))
for (i in 1:length(x)) {
if (identical(x_trimmed[i], "")) {
@ -201,7 +204,7 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
next
}
if (toupper(x_trimmed[i]) == 'VRE') {
x[i] <- 'ENC'
x[i] <- 'ENCSPP'
next
}
if (toupper(x_trimmed[i]) == 'MRPA') {
@ -234,6 +237,13 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
next
}
# try any match with genus, keeping spaces, not ending with $ ----
found <- MOs[which(MOs$genus %like% x_withspaces_start[i] & MOs$mo %like% 'SPP$'),]$mo
if (length(found) > 0) {
x[i] <- found[1L]
next
}
# try any match keeping spaces, not ending with $ ----
found <- MOs[which(MOs$fullname %like% x_withspaces_start[i]),]$mo
if (length(found) > 0) {
@ -297,19 +307,6 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
}
# avoid detection of Staphylococcus auricularis in case of S. aureus ----
x[x == "STAAUC" & toupper(x_backup) != "STAAUC" & !x_backup %like% 'auri'] <- "STAAUR"
# avoid detection of Entamoeba coli in case of E. coli ----
x[x == "ENMCOL" & toupper(x_backup) != "ENMCOL" & !x_backup %like% '^ent?'] <- "ESCCOL"
# avoid detection of Haematobacter influenzae in case of H. influenzae ----
x[x == "HABINF" & toupper(x_backup) != "HABINF" & !x_backup %like% '^haema'] <- "HAEINF"
# avoid detection of Pasteurella aerogenes in case of P. aeruginosa ----
x[x == "PASAER" & toupper(x_backup) != "PASAER" & !(x_backup %like% '^pas?' | x_backup %like% 'aero')] <- "PSEAER"
# avoid detection of Legionella non pneumophila in case of Legionella pneumophila ----
x[x == "LEGNON" & toupper(x_backup) != "LEGNON" & !x_backup %like% 'non'] <- "LEGPNE"
# avoid detection of Streptobacillus in case of Streptococcus ----
x[x == "STB" & toupper(x_backup) != "STB" & !x_backup %like% 'streptob'] <- "STC"
failures <- failures[!failures %in% c(NA, NULL, NaN)]
if (length(failures) > 0) {
warning("These ", length(failures) , " values could not be coerced to a valid mo: ",
@ -376,7 +373,9 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
# for the returned genera without species, add species ----
# like "ESC" -> "ESCSPP", but only where the input contained it
indices <- unique(x_input) %like% "[A-Z]{3}SPP" & !x %like% "[A-Z]{3}SPP"
indices <- nchar(unique(x)) == 3 & !x %like% "[A-Z]{3}SPP" & !x %in% c("GNR", "GPR", "GNC", "GPC",
"GNS", "GPS", "GNK", "GPK")
indices <- indices[!is.na(indices)]
x[indices] <- paste0(x[indices], 'SPP')
# left join the found results to the original input values (x_input)