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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/ #
# ==================================================================== #
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#' Add Custom Microorganisms
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#'
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#' With [add_custom_microorganisms()] you can add your own custom microorganisms, such the non-taxonomic outcome of laboratory analysis.
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#' @param x a [data.frame] resembling the [microorganisms] data set, at least containing column "genus" (case-insensitive)
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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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#'
#' **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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#' There are two ways to automate this process:
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#'
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#' **Method 1:** Using the option [`AMR_custom_mo`][AMR-options], which is the preferred method. 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 column "genus") 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 option [`AMR_custom_mo`][AMR-options]: `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 be 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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#'
#' ```r
#' # Add custom microorganism codes:
#' options(AMR_custom_mo = "~/my_custom_mo.rds")
#' ```
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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:** Loading the microorganism directly from your `.Rprofile` file. An important downside is that this requires the `AMR` package to be installed or else this method will fail. To use this method:
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#'
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#' 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:
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#' AMR::add_custom_microorganisms(
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#' data.frame(genus = "Enterobacter",
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#' species = "asburiae/cloacae")
#' )
#' ```
#'
#' Use [clear_custom_microorganisms()] to clear the previously added antimicrobials.
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#' @seealso [add_custom_antimicrobials()] to add custom antimicrobials.
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#' @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(
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#' data.frame(
#' genus = "Enterobacter",
#' species = "asburiae/cloacae"
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#' )
#' )
#'
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#' # E. asburiae/cloacae is now a new microorganism:
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#' mo_name("Enterobacter asburiae/cloacae")
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#'
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#' # its code:
#' as.mo("Enterobacter asburiae/cloacae")
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#'
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#' # all internal algorithms will work as well:
#' 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("E. asburiae/cloacae")
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#' mo_gramstain("Enterobacter asburiae/cloacae")
#'
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#' mo_info("Enterobacter asburiae/cloacae")
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#'
#'
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#' # the function tries to be forgiving:
#' add_custom_microorganisms(
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#' data.frame(
#' GENUS = "BACTEROIDES / PARABACTEROIDES SLASHLINE",
#' SPECIES = "SPECIES"
#' )
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#' )
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#' mo_name("BACTEROIDES / PARABACTEROIDES")
#' mo_rank("BACTEROIDES / PARABACTEROIDES")
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#'
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#' # taxonomy still works, although a slashline genus was given as input:
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#' mo_family("Bacteroides/Parabacteroides")
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#'
#'
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#' # for groups and complexes, set them as species or subspecies:
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#' add_custom_microorganisms(
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#' data.frame(
#' genus = "Citrobacter",
#' species = c("freundii", "braakii complex"),
#' subspecies = c("complex", "")
#' )
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#' )
#' mo_name(c("C. freundii complex", "C. braakii complex"))
#' mo_species(c("C. freundii complex", "C. braakii complex"))
#' mo_gramstain(c("C. freundii complex", "C. braakii complex"))
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#' }
add_custom_microorganisms <- function ( x ) {
meet_criteria ( x , allow_class = " data.frame" )
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stop_ifnot ( " genus" %in% tolower ( colnames ( x ) ) , paste0 ( " `x` must contain column 'genus'." ) )
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add_MO_lookup_to_AMR_env ( )
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# remove any extra class/type, such as grouped tbl, or data.table:
x <- as.data.frame ( x , stringsAsFactors = FALSE )
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colnames ( x ) <- tolower ( colnames ( x ) )
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# 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 ]
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# clean the input ----
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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 ]
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col_ <- tolower ( col_ )
col_ <- gsub ( " slashline" , " " , col_ , fixed = TRUE )
col_ <- trimws2 ( col_ )
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col_ [col_ %like% " (sub)?species" ] <- " "
col_ <- gsub ( " *([/-]) *" , " \\1" , col_ , perl = TRUE )
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# groups are in our taxonomic table with a capital G
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col_ <- gsub ( " group( |$)" , " Group\\1" , col_ , perl = TRUE )
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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_
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}
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# if subspecies is a group or complex, add it to the species and empty the subspecies
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x $ species [which ( x $ subspecies %in% c ( " group" , " Group" , " complex" ) ) ] <- paste (
x $ species [which ( x $ subspecies %in% c ( " group" , " Group" , " complex" ) ) ] ,
x $ subspecies [which ( x $ subspecies %in% c ( " group" , " Group" , " complex" ) ) ]
)
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x $ subspecies [which ( x $ subspecies %in% c ( " group" , " Group" , " complex" ) ) ] <- " "
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if ( " rank" %in% colnames ( x ) ) {
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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 )
)
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} else {
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x $ rank <- ifelse ( x $ subspecies != " " , " subspecies" ,
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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
)
)
)
)
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}
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x $ source <- " Added by user"
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if ( ! " fullname" %in% colnames ( x ) ) {
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x $ fullname <- trimws2 ( paste ( x $ genus , x $ species , x $ subspecies ) )
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}
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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 <- " "
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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 ) ] <- " "
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for ( col in colnames ( x ) ) {
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if ( is.factor ( x [ , col , drop = TRUE ] ) ) {
x [ , col ] <- as.character ( x [ , col , drop = TRUE ] )
}
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if ( is.list ( AMR_env $ MO_lookup [ , col , drop = TRUE ] ) ) {
x [ , col ] <- as.list ( x [ , col , drop = TRUE ] )
}
}
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# 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 ) ]
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# fill in other columns that are used in internal algorithms
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x $ prevalence <- NA_real_
x $ prevalence [which ( genus_to_check != " " ) ] <- AMR_env $ MO_lookup $ prevalence [match ( genus_to_check [which ( genus_to_check != " " ) ] , AMR_env $ MO_lookup $ genus ) ]
x $ prevalence [is.na ( x $ prevalence ) ] <- 1.25
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x $ status <- " accepted"
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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
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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 ) )
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if ( ! " mo" %in% colnames ( x ) ) {
# create the mo code
x $ mo <- NA_character_
}
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x $ mo <- trimws2 ( as.character ( x $ mo ) )
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x $ mo [x $ mo == " " ] <- NA_character_
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current <- sum ( AMR_env $ MO_lookup $ source == " Added by user" , na.rm = TRUE )
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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
) ) )
)
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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" )
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# add to package ----
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AMR_env $ custom_mo_codes <- c ( AMR_env $ custom_mo_codes , x $ mo )
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 ]
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 ]
}
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# clear previous coercions
suppressMessages ( mo_reset_session ( ) )
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AMR_env $ MO_lookup <- unique ( rbind2 ( AMR_env $ MO_lookup , new_df ) )
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class ( AMR_env $ MO_lookup $ mo ) <- c ( " mo" , " character" )
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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." )
}
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}
#' @rdname add_custom_microorganisms
#' @export
clear_custom_microorganisms <- function ( ) {
n <- nrow ( AMR_env $ MO_lookup )
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# reset
AMR_env $ MO_lookup <- NULL
add_MO_lookup_to_AMR_env ( )
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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." )
}