mirror of https://github.com/msberends/AMR.git
229 lines
9.3 KiB
R
Executable File
229 lines
9.3 KiB
R
Executable File
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Data Analysis for R #
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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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# LICENCE #
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# (c) 2018-2022 Berends MS, Luz CF et al. #
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# Developed at the University of Groningen, the Netherlands, in #
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# collaboration with non-profit organisations Certe Medical #
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# Diagnostics & Advice, and University Medical Center Groningen. #
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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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#' Count Available Isolates
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#'
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#' @description These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in `summarise()` from the `dplyr` package and also support grouped variables, see *Examples*.
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#'
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#' [count_resistant()] should be used to count resistant isolates, [count_susceptible()] should be used to count susceptible isolates.
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#' @inheritSection lifecycle Stable Lifecycle
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#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with [as.rsi()] if needed.
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#' @inheritParams proportion
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#' @inheritSection as.rsi Interpretation of R and S/I
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#' @details These functions are meant to count isolates. Use the [resistance()]/[susceptibility()] functions to calculate microbial resistance/susceptibility.
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#'
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#' The function [count_resistant()] is equal to the function [count_R()]. The function [count_susceptible()] is equal to the function [count_SI()].
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#'
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#' The function [n_rsi()] is an alias of [count_all()]. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to `n_distinct()`. Their function is equal to `count_susceptible(...) + count_resistant(...)`.
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#'
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#' The function [count_df()] takes any variable from `data` that has an [`rsi`] class (created with [as.rsi()]) and counts the number of S's, I's and R's. It also supports grouped variables. The function [rsi_df()] works exactly like [count_df()], but adds the percentage of S, I and R.
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#' @inheritSection proportion Combination Therapy
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#' @seealso [`proportion_*`][proportion] to calculate microbial resistance and susceptibility.
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#' @return An [integer]
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#' @rdname count
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#' @name count
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#' @export
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#' @inheritSection AMR Read more on Our Website!
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#' @examples
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#' # example_isolates is a data set available in the AMR package.
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#' ?example_isolates
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#'
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#' count_resistant(example_isolates$AMX) # counts "R"
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#' count_susceptible(example_isolates$AMX) # counts "S" and "I"
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#' count_all(example_isolates$AMX) # counts "S", "I" and "R"
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#'
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#' # be more specific
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#' count_S(example_isolates$AMX)
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#' count_SI(example_isolates$AMX)
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#' count_I(example_isolates$AMX)
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#' count_IR(example_isolates$AMX)
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#' count_R(example_isolates$AMX)
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#'
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#' # Count all available isolates
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#' count_all(example_isolates$AMX)
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#' n_rsi(example_isolates$AMX)
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#'
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#' # n_rsi() is an alias of count_all().
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#' # Since it counts all available isolates, you can
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#' # calculate back to count e.g. susceptible isolates.
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#' # These results are the same:
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#' count_susceptible(example_isolates$AMX)
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#' susceptibility(example_isolates$AMX) * n_rsi(example_isolates$AMX)
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#'
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#' \donttest{
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#' if (require("dplyr")) {
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#' example_isolates %>%
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#' group_by(hospital_id) %>%
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#' summarise(R = count_R(CIP),
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#' I = count_I(CIP),
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#' S = count_S(CIP),
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#' n1 = count_all(CIP), # the actual total; sum of all three
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#' n2 = n_rsi(CIP), # same - analogous to n_distinct
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#' total = n()) # NOT the number of tested isolates!
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#'
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#' # Number of available isolates for a whole antibiotic class
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#' # (i.e., in this data set columns GEN, TOB, AMK, KAN)
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#' example_isolates %>%
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#' group_by(hospital_id) %>%
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#' summarise(across(aminoglycosides(), n_rsi))
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#'
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#' # Count co-resistance between amoxicillin/clav acid and gentamicin,
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#' # so we can see that combination therapy does a lot more than mono therapy.
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#' # Please mind that `susceptibility()` calculates percentages right away instead.
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#' example_isolates %>% count_susceptible(AMC) # 1433
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#' example_isolates %>% count_all(AMC) # 1879
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#'
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#' example_isolates %>% count_susceptible(GEN) # 1399
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#' example_isolates %>% count_all(GEN) # 1855
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#'
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#' example_isolates %>% count_susceptible(AMC, GEN) # 1764
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#' example_isolates %>% count_all(AMC, GEN) # 1936
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#'
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#' # Get number of S+I vs. R immediately of selected columns
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#' example_isolates %>%
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#' select(AMX, CIP) %>%
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#' count_df(translate = FALSE)
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#'
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#' # It also supports grouping variables
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#' example_isolates %>%
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#' select(hospital_id, AMX, CIP) %>%
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#' group_by(hospital_id) %>%
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#' count_df(translate = FALSE)
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#' }
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#' }
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count_resistant <- function(..., only_all_tested = FALSE) {
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tryCatch(
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rsi_calc(...,
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ab_result = "R",
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only_all_tested = only_all_tested,
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only_count = TRUE),
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error = function(e) stop_(e$message, call = -5))
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}
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#' @rdname count
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#' @export
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count_susceptible <- function(..., only_all_tested = FALSE) {
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tryCatch(
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rsi_calc(...,
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ab_result = c("S", "I"),
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only_all_tested = only_all_tested,
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only_count = TRUE),
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error = function(e) stop_(e$message, call = -5))
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}
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#' @rdname count
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#' @export
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count_R <- function(..., only_all_tested = FALSE) {
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tryCatch(
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rsi_calc(...,
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ab_result = "R",
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only_all_tested = only_all_tested,
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only_count = TRUE),
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error = function(e) stop_(e$message, call = -5))
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}
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#' @rdname count
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#' @export
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count_IR <- function(..., only_all_tested = FALSE) {
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if (message_not_thrown_before("count_IR", entire_session = TRUE)) {
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message_("Using `count_IR()` is discouraged; use `count_resistant()` instead to not consider \"I\" being resistant. This note will be shown once for this session.", as_note = FALSE)
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}
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tryCatch(
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rsi_calc(...,
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ab_result = c("I", "R"),
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only_all_tested = only_all_tested,
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only_count = TRUE),
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error = function(e) stop_(e$message, call = -5))
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}
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#' @rdname count
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#' @export
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count_I <- function(..., only_all_tested = FALSE) {
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tryCatch(
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rsi_calc(...,
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ab_result = "I",
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only_all_tested = only_all_tested,
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only_count = TRUE),
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error = function(e) stop_(e$message, call = -5))
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}
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#' @rdname count
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#' @export
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count_SI <- function(..., only_all_tested = FALSE) {
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tryCatch(
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rsi_calc(...,
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ab_result = c("S", "I"),
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only_all_tested = only_all_tested,
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only_count = TRUE),
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error = function(e) stop_(e$message, call = -5))
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}
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#' @rdname count
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#' @export
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count_S <- function(..., only_all_tested = FALSE) {
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if (message_not_thrown_before("count_S", entire_session = TRUE)) {
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message_("Using `count_S()` is discouraged; use `count_susceptible()` instead to also consider \"I\" being susceptible. This note will be shown once for this session.", as_note = FALSE)
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}
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tryCatch(
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rsi_calc(...,
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ab_result = "S",
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only_all_tested = only_all_tested,
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only_count = TRUE),
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error = function(e) stop_(e$message, call = -5))
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}
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#' @rdname count
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#' @export
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count_all <- function(..., only_all_tested = FALSE) {
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tryCatch(
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rsi_calc(...,
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ab_result = c("S", "I", "R"),
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only_all_tested = only_all_tested,
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only_count = TRUE),
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error = function(e) stop_(e$message, call = -5))
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}
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#' @rdname count
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#' @export
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n_rsi <- count_all
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#' @rdname count
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#' @export
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count_df <- function(data,
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translate_ab = "name",
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language = get_AMR_locale(),
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combine_SI = TRUE,
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combine_IR = FALSE) {
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tryCatch(
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rsi_calc_df(type = "count",
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data = data,
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translate_ab = translate_ab,
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language = language,
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combine_SI = combine_SI,
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combine_IR = combine_IR,
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combine_SI_missing = missing(combine_SI)),
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error = function(e) stop_(e$message, call = -5))
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}
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