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98 lines
5.7 KiB
R
98 lines
5.7 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 CODE: #
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# https://github.com/msberends/AMR #
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# #
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# PLEASE CITE THIS SOFTWARE AS: #
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# Berends MS, Luz CF, Friedrich AW, et al. (2022). #
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# AMR: An R Package for Working with Antimicrobial Resistance Data. #
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# Journal of Statistical Software, 104(3), 1-31. #
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# https://doi.org/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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#' Filter Top *n* Microorganisms
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#'
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#' This function filters a data set to include only the top *n* microorganisms based on a specified property, such as taxonomic family or genus. For example, it can filter a data set to the top 3 species, or to any species in the top 5 genera, or to the top 3 species in each of the top 5 genera.
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#' @param x a data frame containing microbial data
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#' @param n an integer specifying the maximum number of unique values of the `property` to include in the output
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#' @param property a character string indicating the microorganism property to use for filtering. Must be one of the column names of the [microorganisms] data set: `r vector_or(colnames(microorganisms), sort = FALSE, quotes = TRUE)`. If `NULL`, the raw values from `col_mo` will be used without transformation.
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#' @param n_for_each an optional integer specifying the maximum number of rows to retain for each value of the selected property. If `NULL`, all rows within the top *n* groups will be included.
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#' @param col_mo A character string indicating the column in `x` that contains microorganism names or codes. Defaults to the first column of class [`mo`]. Values will be coerced using [as.mo()].
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#' @param ... Additional arguments passed on to [mo_property()] when `property` is not `NULL`.
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#' @details This function is useful for preprocessing data before creating [antibiograms][antibiograms()] or other analyses that require focused subsets of microbial data. For example, it can filter a data set to only include isolates from the top 10 species.
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#' @export
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#' @seealso [mo_property()], [as.mo()], [antibiogram()]
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#' @examples
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#' # filter to the top 3 species:
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#' top_n_microorganisms(example_isolates,
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#' n = 3)
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#'
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#' # filter to any species in the top 5 genera:
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#' top_n_microorganisms(example_isolates,
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#' n = 5, property = "genus")
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#'
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#' # filter to the top 3 species in each of the top 5 genera:
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#' top_n_microorganisms(example_isolates,
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#' n = 5, property = "genus", n_for_each = 3)
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top_n_microorganisms <- function(x, n, property = "fullname", n_for_each = NULL, col_mo = NULL, ...) {
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meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
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meet_criteria(n, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE, is_positive = TRUE)
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meet_criteria(property, allow_class = "character", has_length = 1, is_in = colnames(AMR::microorganisms))
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meet_criteria(n_for_each, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE, is_positive = TRUE, allow_NULL = TRUE)
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meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
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if (is.null(col_mo)) {
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col_mo <- search_type_in_df(x = x, type = "mo", info = TRUE)
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stop_if(is.null(col_mo), "`col_mo` must be set")
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}
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x.bak <- x
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x[, col_mo] <- as.mo(x[, col_mo, drop = TRUE], keep_synonyms = TRUE)
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if (is.null(property)) {
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x$prop_val <- x[[col_mo]]
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} else {
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x$prop_val <- mo_property(x[[col_mo]], property = property, ...)
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}
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counts <- sort(table(x$prop_val), decreasing = TRUE)
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n <- as.integer(n)
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if (length(counts) < n) {
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n <- length(counts)
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}
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count_values <- names(counts)[seq_len(n)]
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filtered_rows <- which(x$prop_val %in% count_values)
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if (!is.null(n_for_each)) {
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n_for_each <- as.integer(n_for_each)
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filtered_x <- x[filtered_rows, , drop = FALSE]
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filtered_rows <- do.call(
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c,
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lapply(split(filtered_x, filtered_x$prop_val), function(group) {
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top_values <- names(sort(table(group[[col_mo]]), decreasing = TRUE)[seq_len(n_for_each)])
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top_values <- top_values[!is.na(top_values)]
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which(x[[col_mo]] %in% top_values)
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})
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)
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}
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x.bak[filtered_rows, , drop = FALSE]
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}
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