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AMR/R/custom_microorganisms.R

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# ==================================================================== #
# TITLE #
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# CITE AS #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. #
# doi:10.18637/jss.v104.i03 #
# #
# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
# #
# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Add Custom Microorganisms to This Package
#'
#' With [add_custom_microorganisms()] you can add your own custom microorganisms to the `AMR` package, such the non-taxonomic outcome of laboratory analysis.
#' @param x a [data.frame] resembling the [microorganisms] data set, at least containing column "genus" (case-insensitive)
#' @details This function will fill in missing taxonomy for you, if specific taxonomic columns are missing, see *Examples*.
#'
#' **Important:** Due to how \R works, the [add_custom_microorganisms()] function has to be run in every \R session - added microorganisms are not stored between sessions and are thus lost when \R is exited.
#'
#' There are two ways to automate this process:
#'
#' **Method 1:** Save the microorganisms to a local or remote file (can even be the internet). To use this method:
#'
#' 1. Create a data set in the structure of the [microorganisms] data set (containing at the very least column "genus") and save it with [saveRDS()] to a location of choice, e.g. `"~/my_custom_mo.rds"`, or any remote location.
#'
#' 2. Set the file location to the `AMR_custom_mo` \R option: `options(AMR_custom_mo = "~/my_custom_mo.rds")`. This can even be a remote file location, such as an https URL. Since options are not saved between \R sessions, it is best to save this option to the `.Rprofile` file so that it will loaded on start-up of \R. To do this, open the `.Rprofile` file using e.g. `utils::file.edit("~/.Rprofile")`, add this text and save the file:
#'
#' ```r
#' # Add custom microorganism codes:
#' options(AMR_custom_mo = "~/my_custom_mo.rds")
#' ```
#'
#' Upon package load, this file will be loaded and run through the [add_custom_microorganisms()] function.
#'
#' **Method 2:** Save the microorganism directly to your `.Rprofile` file. An important downside is that this requires to load the `AMR` package at every start-up. To use this method:
#'
#' 1. Edit the `.Rprofile` file using e.g. `utils::file.edit("~/.Rprofile")`.
#'
#' 2. Add a text like below and save the file:
#'
#' ```r
#' # Add custom antibiotic drug codes:
#' library(AMR)
#' add_custom_microorganisms(
#' data.frame(genus = "Enterobacter",
#' species = "asburiae/cloacae")
#' )
#' ```
#'
#' Use [clear_custom_microorganisms()] to clear the previously added antimicrobials.
#' @seealso [add_custom_antimicrobials()] to add custom antimicrobials to this package.
#' @rdname add_custom_microorganisms
#' @export
#' @examples
#' \donttest{
#'
#' # a combination of species is not formal taxonomy, so
#' # this will result in only "Enterobacter asburiae":
#' mo_name("Enterobacter asburiae/cloacae")
#'
#' # now add a custom entry - it will be considered by as.mo() and
#' # all mo_*() functions
#' add_custom_microorganisms(
#' data.frame(genus = "Enterobacter",
#' species = "asburiae/cloacae"
#' )
#' )
#'
#' # E. asburiae/cloacae is now a new microorganism:
#' mo_name("Enterobacter asburiae/cloacae")
#'
#' # its code:
#' as.mo("Enterobacter asburiae/cloacae")
#'
#' # all internal algorithms will work as well:
#' mo_name("Ent asburia cloacae")
#'
#' # and even the taxonomy was added based on the genus!
#' mo_family("E. asburiae/cloacae")
#' mo_gramstain("Enterobacter asburiae/cloacae")
#'
#' mo_info("Enterobacter asburiae/cloacae")
#'
#'
#' # the function tries to be forgiving:
#' add_custom_microorganisms(
#' data.frame(GENUS = "ESCHERICHIA / KLEBSIELLA",
#' SPECIES = "SPECIES"))
#' mo_name("ESCHERICHIA / KLEBSIELLA")
#' mo_family("Escherichia/Klebsiella")
#'
#' add_custom_microorganisms(
#' data.frame(genus = "Citrobacter", species = "freundii complex"))
#' mo_name("C. freundii complex")
#' mo_gramstain("C. freundii complex")
#' }
add_custom_microorganisms <- function(x) {
meet_criteria(x, allow_class = "data.frame")
stop_ifnot("genus" %in% tolower(colnames(x)), paste0("`x` must contain column 'genus'."))
# remove any extra class/type, such as grouped tbl, or data.table:
x <- as.data.frame(x, stringsAsFactors = FALSE)
colnames(x) <- tolower(colnames(x))
# rename 'name' to 'fullname' if it's in the data set
if ("name" %in% colnames(x) && !"fullname" %in% colnames(x)) {
colnames(x)[colnames(x) == "name"] <- "fullname"
}
# keep only columns available in the microorganisms data set
x <- x[, colnames(AMR_env$MO_lookup)[colnames(AMR_env$MO_lookup) %in% colnames(x)], drop = FALSE]
# clean the input ----
for (col in c("genus", "species", "subspecies")) {
if (!col %in% colnames(x)) {
x[, col] <- ""
}
if (is.factor(x[, col, drop = TRUE])) {
x[, col] <- as.character(x[, col, drop = TRUE])
}
col_ <- x[, col, drop = TRUE]
col_ <- tolower(trimws2(col_))
col_[col_ %like% "(sub)?species"] <- ""
col_ <- gsub(" *([/-]) *", "\\1", col_, perl = TRUE)
# groups are in our taxonomic table with a capital G, and complexes might be added by the user
col_ <- gsub(" group( |$)", " Group\\1", col_, perl = TRUE)
col_ <- gsub(" complex( |$)", " Complex\\1", col_, perl = TRUE)
col_[is.na(col_)] <- ""
if (col == "genus") {
substr(col_, 1, 1) <- toupper(substr(col_, 1, 1))
col_ <- gsub("/([a-z])", "/\\U\\1", col_, perl = TRUE)
stop_if(any(col_ == ""), "the 'genus' column cannot be empty")
stop_if(any(col_ %like% " "), "the 'genus' column must not contain spaces")
}
x[, col] <- col_
}
if ("rank" %in% colnames(x)) {
stop_ifnot(all(x$rank %in% AMR_env$MO_lookup$rank),
"the 'rank' column can only contain these values: ", vector_or(AMR_env$MO_lookup$rank))
} else {
x$rank <- ifelse(x$subspecies != "", "subspecies",
ifelse(x$species != "", "species",
ifelse(x$genus != "", "genus",
stop("in add_custom_microorganisms(): only microorganisms up to the genus level can be added",
call. = FALSE))))
}
x$source <- "Added by user"
if (!"fullname" %in% colnames(x)) {
x$fullname <- trimws2(paste(x$genus, x$species, x$subspecies))
}
if (!"kingdom" %in% colnames(x)) x$kingdom <- ""
if (!"phylum" %in% colnames(x)) x$phylum <- ""
if (!"class" %in% colnames(x)) x$class <- ""
if (!"order" %in% colnames(x)) x$order <- ""
if (!"family" %in% colnames(x)) x$family <- ""
x$kingdom[is.na(x$kingdom)] <- ""
x$phylum[is.na(x$phylum)] <- ""
x$class[is.na(x$class)] <- ""
x$order[is.na(x$order)] <- ""
x$family[is.na(x$family)] <- ""
for (col in colnames(x)) {
if (is.factor(x[, col, drop = TRUE])) {
x[, col] <- as.character(x[, col, drop = TRUE])
}
if (is.list(AMR_env$MO_lookup[, col, drop = TRUE])) {
x[, col] <- as.list(x[, col, drop = TRUE])
}
}
# fill in taxonomy based on genus
genus_to_check <- gsub("^(.*)[^a-zA-Z].*", "\\1", x$genus, perl = TRUE)
x$kingdom[which(x$kingdom == "" & genus_to_check != "")] <- AMR_env$MO_lookup$kingdom[match(genus_to_check[which(x$kingdom == "" & genus_to_check != "")], AMR_env$MO_lookup$genus)]
x$phylum[which(x$phylum == "" & genus_to_check != "")] <- AMR_env$MO_lookup$phylum[match(genus_to_check[which(x$phylum == "" & genus_to_check != "")], AMR_env$MO_lookup$genus)]
x$class[which(x$class == "" & genus_to_check != "")] <- AMR_env$MO_lookup$class[match(genus_to_check[which(x$class == "" & genus_to_check != "")], AMR_env$MO_lookup$genus)]
x$order[which(x$order == "" & genus_to_check != "")] <- AMR_env$MO_lookup$order[match(genus_to_check[which(x$order == "" & genus_to_check != "")], AMR_env$MO_lookup$genus)]
x$family[which(x$family == "" & genus_to_check != "")] <- AMR_env$MO_lookup$family[match(genus_to_check[which(x$family == "" & genus_to_check != "")], AMR_env$MO_lookup$genus)]
# fill in other columns that are used in internal algorithms
x$status <- "accepted"
x$prevalence <- 1
x$ref <- paste("Self-added,", format(Sys.Date(), "%Y"))
x$kingdom_index <- AMR_env$MO_lookup$kingdom_index[match(genus_to_check, AMR_env$MO_lookup$genus)]
# complete missing kingdom index, so mo_matching_score() will not return NA
x$kingdom_index[is.na(x$kingdom_index)] <- 1
x$fullname_lower <- tolower(x$fullname)
x$full_first <- substr(x$fullname_lower, 1, 1)
x$species_first <- tolower(substr(x$species, 1, 1))
x$subspecies_first <- tolower(substr(x$subspecies, 1, 1))
if (!"mo" %in% colnames(x)) {
# create the mo code
x$mo <- NA_character_
}
x$mo <- trimws2(as.character(x$mo))
x$mo[x$mo == ""] <- NA_character_
current <- sum(AMR_env$MO_lookup$source == "Added by user", na.rm = TRUE)
x$mo[is.na(x$mo)] <- paste0("CUSTOM",
seq.int(from = current + 1, to = current + nrow(x), by = 1),
"_",
toupper(unname(abbreviate(gsub(" +", " _ ",
gsub("[^A-Za-z0-9-]", " ",
trimws2(paste(x$genus, x$species, x$subspecies)))),
minlength = 10))))
stop_if(anyDuplicated(c(as.character(AMR_env$MO_lookup$mo), x$mo)), "MO codes must be unique and not match existing MO codes of the AMR package")
# add to package ----
AMR_env$custom_mo_codes <- c(AMR_env$custom_mo_codes, x$mo)
class(AMR_env$MO_lookup$mo) <- "character"
new_df <- AMR_env$MO_lookup[0, , drop = FALSE][seq_len(NROW(x)), , drop = FALSE]
rownames(new_df) <- NULL
list_cols <- vapply(FUN.VALUE = logical(1), new_df, is.list)
for (l in which(list_cols)) {
# prevent binding NULLs in lists, replace with NA
new_df[, l] <- as.list(NA_character_)
}
for (col in colnames(x)) {
# assign new values
new_df[, col] <- x[, col, drop = TRUE]
}
# clear previous coercions
suppressMessages(mo_reset_session())
AMR_env$MO_lookup <- unique(rbind(AMR_env$MO_lookup, new_df))
class(AMR_env$MO_lookup$mo) <- c("mo", "character")
if (nrow(x) <= 3) {
message_("Added ", vector_and(italicise(x$fullname), quotes = FALSE), " to the internal `microorganisms` data set.")
} else {
message_("Added ", nr2char(nrow(x)), " records to the internal `microorganisms` data set.")
}
}
#' @rdname add_custom_microorganisms
#' @export
clear_custom_microorganisms <- function() {
n <- nrow(AMR_env$MO_lookup)
AMR_env$MO_lookup <- create_MO_lookup()
n2 <- nrow(AMR_env$MO_lookup)
AMR_env$custom_mo_codes <- character(0)
AMR_env$mo_previously_coerced <- AMR_env$mo_previously_coerced[which(AMR_env$mo_previously_coerced$mo %in% AMR_env$MO_lookup$mo), , drop = FALSE]
AMR_env$mo_uncertainties <- AMR_env$mo_uncertainties[0, , drop = FALSE]
message_("Cleared ", nr2char(n - n2), " custom record", ifelse(n - n2 > 1, "s", ""), " from the internal `microorganisms` data set.")
}
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