mirror of https://github.com/msberends/AMR.git
213 lines
10 KiB
R
213 lines
10 KiB
R
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# ==================================================================== #
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# TITLE #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
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# #
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# SOURCE #
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# https://github.com/msberends/AMR #
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# #
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# CITE AS #
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# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
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# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
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# Data. Journal of Statistical Software, 104(3), 1-31. #
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# doi:10.18637/jss.v104.i03 #
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# #
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# Developed at the University of Groningen and the University Medical #
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# Center Groningen in The Netherlands, in collaboration with many #
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# colleagues from around the world, see our website. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
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# Visit our website for the full manual and a complete tutorial about #
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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#' Add Custom Microorganisms to This Package
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#'
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#' With [add_custom_microorganisms()] you can add your own custom antimicrobial drug codes to the `AMR` package.
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#' @param x a [data.frame] resembling the [microorganisms] data set, at least containing columns "mo", "genus" and "species"
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#' @details This function will fill in missing taxonomy for you, if specific taxonomic columns are missing, see *Examples*.
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#'
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#' **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.
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#'
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#' There are two ways to automate this process:
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#'
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#' **Method 1:** Save the microorganisms to a local or remote file (can even be the internet). To use this method:
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#'
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#' 1. Create a data set in the structure of the [microorganisms] data set (containing at the very least columns "ab" and "name") and save it with [saveRDS()] to a location of choice, e.g. `"~/my_custom_mo.rds"`, or any remote location.
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#'
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#' 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:
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#'
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#' ```r
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#' # Add custom microorganism codes:
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#' options(AMR_custom_mo = "~/my_custom_mo.rds")
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#' ```
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#'
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#' Upon package load, this file will be loaded and run through the [add_custom_microorganisms()] function.
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#'
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#' **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:
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#'
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#' 1. Edit the `.Rprofile` file using e.g. `utils::file.edit("~/.Rprofile")`.
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#'
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#' 2. Add a text like below and save the file:
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#'
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#' ```r
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#' # Add custom antibiotic drug codes:
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#' library(AMR)
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#' add_custom_microorganisms(
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#' data.frame(mo = "ENT_ASB_CLO",
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#' genus = "Enterobacter",
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#' species = "asburiae/cloacae")
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#' )
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#' ```
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#'
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#' Use [clear_custom_microorganisms()] to clear the previously added antimicrobials.
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#' @seealso [add_custom_antimicrobials()] to add custom antimicrobials to this package.
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#' @rdname add_custom_microorganisms
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#' @export
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#' @examples
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#' \donttest{
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#'
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#' # a combination of species is not formal taxonomy, so
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#' # this will result in only "Enterobacter asburiae":
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#' mo_name("Enterobacter asburiae/cloacae")
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#'
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#' # now add a custom entry - it will be considered by as.mo() and
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#' # all mo_*() functions
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#' add_custom_microorganisms(
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#' data.frame(mo = "ENT_ASB_CLO",
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#' genus = "Enterobacter",
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#' species = "asburiae/cloacae"
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#' )
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#' )
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#'
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#' # "ENT_ASB_CLO" is now a new microorganism:
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#' mo_name("Enterobacter asburiae/cloacae")
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#' as.mo("ent_asb_clo")
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#' mo_name("ent_asb_clo")
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#' # all internal algorithms will work as well:
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#' mo_name("Ent asburia cloacae")
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#'
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#' # and even the taxonomy was added based on the genus!
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#' mo_family("ent_asb_clo")
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#' mo_gramstain("Enterobacter asburiae/cloacae")
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#'
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#' mo_info("ent_asb_clo")
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#' }
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add_custom_microorganisms <- function(x) {
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meet_criteria(x, allow_class = "data.frame")
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required_cols <- c("mo", "genus", "species")
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stop_ifnot(
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all(required_cols %in% colnames(x)),
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paste0("`x` must contain columns ", vector_and(required_cols, sort = FALSE), ".")
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)
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stop_if(
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any(x$mo %in% AMR_env$MO_lookup$mo),
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"Microorganism code(s) ", vector_and(x$mo[x$mo %in% AMR_env$MO_lookup$mo]), " already exist in the internal `microorganisms` data set."
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)
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# remove any extra class/type, such as grouped tbl, or data.table:
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x <- as.data.frame(x, stringsAsFactors = FALSE)
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# rename 'name' to 'fullname' if it's in the data set
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if ("name" %in% colnames(x) && !"fullname" %in% colnames(x)) {
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colnames(x)[colnames(x) == "name"] <- "fullname"
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}
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# keep only columns available in the microorganisms data set
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x <- x[, colnames(AMR_env$MO_lookup)[colnames(AMR_env$MO_lookup) %in% colnames(x)], drop = FALSE]
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# clean the input ----
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if (!"subspecies" %in% colnames(x)) {
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x$subspecies <- NA_character_
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}
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x$genus <- trimws2(x$genus)
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x$species <- trimws2(x$species)
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x$subspecies <- trimws2(x$subspecies)
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x$genus[x$genus == ""] <- NA_character_
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x$species[x$species == ""] <- NA_character_
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x$subspecies[x$subspecies == ""] <- NA_character_
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stop_if(any(x$genus[!is.na(x$genus)] %like% " "),
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"the 'genus' column must not contain spaces")
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stop_if(any(x$species[!is.na(x$species)] %like% " "),
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"the 'species' column must not contain spaces")
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stop_if(any(x$subspecies[!is.na(x$subspecies)] %like% " "),
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"the 'subspecies' column must not contain spaces")
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if ("rank" %in% colnames(x)) {
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stop_ifnot(all(x$rank %in% AMR_env$MO_lookup$rank),
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"the 'rank' column can only contain these values: ", vector_or(AMR_env$MO_lookup$rank))
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} else {
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x$rank <- ifelse(!is.na(x$subspecies), "subspecies",
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ifelse(!is.na(x$species), "species",
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ifelse(!is.na(x$genus), "genus",
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stop("in add_custom_microorganisms(): the 'genus' column cannot be empty",
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call. = FALSE))))
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}
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if (!"fullname" %in% colnames(x)) {
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x$fullname <- paste(x$genus, x$species, x$subspecies)
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x$fullname <- gsub(" NA", "", x$fullname)
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}
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if (!"kingdom" %in% colnames(x)) x$kingdom <- NA_character_
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if (!"phylum" %in% colnames(x)) x$phylum <- NA_character_
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if (!"class" %in% colnames(x)) x$class <- NA_character_
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if (!"order" %in% colnames(x)) x$order <- NA_character_
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if (!"family" %in% colnames(x)) x$family <- NA_character_
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for (col in colnames(x)) {
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if (is.list(AMR_env$MO_lookup[, col, drop = TRUE])) {
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x[, col] <- as.list(x[, col, drop = TRUE])
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}
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}
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# fill in other columns
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x$status <- "accepted"
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x$prevalence <- 1
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x$kingdom <- AMR_env$MO_lookup$kingdom[match(x$genus, AMR_env$MO_lookup$genus)]
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x$phylum <- AMR_env$MO_lookup$phylum[match(x$genus, AMR_env$MO_lookup$genus)]
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x$class <- AMR_env$MO_lookup$class[match(x$genus, AMR_env$MO_lookup$genus)]
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x$order <- AMR_env$MO_lookup$order[match(x$genus, AMR_env$MO_lookup$genus)]
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x$family <- AMR_env$MO_lookup$family[match(x$genus, AMR_env$MO_lookup$genus)]
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x$kingdom_index <- AMR_env$MO_lookup$kingdom_index[match(x$genus, AMR_env$MO_lookup$genus)]
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x$fullname_lower <- tolower(x$fullname)
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x$full_first <- substr(x$fullname_lower, 1, 1)
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x$species_first <- tolower(substr(x$species, 1, 1))
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x$subspecies_first <- tolower(substr(x$subspecies, 1, 1))
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# add to pacakge ----
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AMR_env$custom_mo_codes <- c(AMR_env$custom_mo_codes, x$mo)
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class(AMR_env$MO_lookup$mo) <- "character"
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new_df <- AMR_env$MO_lookup[0, , drop = FALSE][seq_len(NROW(x)), , drop = FALSE]
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rownames(new_df) <- NULL
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list_cols <- vapply(FUN.VALUE = logical(1), new_df, is.list)
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for (l in which(list_cols)) {
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# prevent binding NULLs in lists, replace with NA
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new_df[, l] <- as.list(NA_character_)
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}
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for (col in colnames(x)) {
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# assign new values
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new_df[, col] <- x[, col, drop = TRUE]
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}
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AMR_env$MO_lookup <- unique(rbind(AMR_env$MO_lookup, new_df))
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AMR_env$mo_previously_coerced <- AMR_env$mo_previously_coerced[which(!AMR_env$mo_previously_coerced$mo %in% new_df$mo), , drop = FALSE]
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class(AMR_env$MO_lookup$mo) <- c("mo", "character")
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message_("Added ", nr2char(nrow(x)), " record", ifelse(nrow(x) > 1, "s", ""), " to the internal `microorganisms` data set.")
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}
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#' @rdname add_custom_microorganisms
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#' @export
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clear_custom_microorganisms <- function() {
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n <- nrow(AMR_env$MO_lookup)
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AMR_env$MO_lookup <- create_MO_lookup()
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n2 <- nrow(AMR_env$MO_lookup)
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AMR_env$custom_mo_codes <- character(0)
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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]
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AMR_env$mo_uncertainties <- AMR_env$mo_uncertainties[0, , drop = FALSE]
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message_("Cleared ", nr2char(n - n2), " custom record", ifelse(n - n2 > 1, "s", ""), " from the internal `microorganisms` data set.")
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}
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