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(v0.7.1.9088) bug_drug improvement

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dr. M.S. (Matthijs) Berends
2019-09-25 15:43:22 +02:00
parent 04cd0d25db
commit 99d0fe76dd
19 changed files with 603 additions and 186 deletions
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70
R/bug_drug_combinations.R
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@ -21,15 +21,17 @@
#' Determine bug-drug combinations
#'
#' Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use \code{format} on the result to prettify it to a printable format, see Examples.
#' Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use \code{format} on the result to prettify it to a publicable/printable format, see Examples.
#' @inheritParams eucast_rules
#' @param combine_IR logical to indicate whether values R and I should be summed
#' @param add_ab_group logical to indicate where the group of the antimicrobials must be included as a first column
#' @param remove_intrinsic_resistant logical to indicate that rows with 100\% resistance for all tested antimicrobials must be removed from the table
#' @param FUN the function to call on the \code{mo} column to transform the microorganism IDs, defaults to \code{\link{mo_shortname}}
#' @param ... argumments passed on to \code{FUN}
#' @param translate_ab a character of length 1 containing column names of the \code{\link{antibiotics}} data set
#' @param ... arguments passed on to \code{FUN}
#' @inheritParams rsi_df
#' @inheritParams base::formatC
#' @importFrom dplyr rename
#' @importFrom dplyr %>% rename group_by select mutate filter pull
#' @importFrom tidyr spread
#' @importFrom clean freq
#' @details The function \code{format} calculates the resistance per bug-drug combination. Use \code{combine_IR = FALSE} (default) to test R vs. S+I and \code{combine_IR = TRUE} to test R+I vs. S.
@ -74,9 +76,9 @@ bug_drug_combinations <- function(x,
x <- x %>%
mutate(mo = x %>% pull(col_mo) %>% FUN(...)) %>%
filter(mo %in% (clean::freq(mo) %>%
filter(count >= minimum) %>%
pull(item))) %>%
filter(mo %in% (freq(mo) %>%
filter(count >= minimum) %>%
pull(item))) %>%
group_by(mo) %>%
AMR::rsi_df(translate_ab = FALSE, combine_SI = FALSE) %>%
select(-value) %>%
@ -88,41 +90,73 @@ bug_drug_combinations <- function(x,
structure(.Data = x, class = c("bug_drug_combinations", class(x)))
}
#' @importFrom dplyr everything rename
#' @importFrom dplyr everything rename %>% ungroup group_by summarise mutate_all arrange everything lag
#' @importFrom tidyr spread
#' @exportMethod format.bug_drug_combinations
#' @export
#' @rdname bug_drug_combinations
format.bug_drug_combinations <- function(x,
combine_IR = FALSE,
format.bug_drug_combinations <- function(x,
translate_ab = "name (ab, atc)",
language = get_locale(),
minimum = 30,
combine_SI = TRUE,
combine_IR = FALSE,
add_ab_group = TRUE,
remove_intrinsic_resistant = FALSE,
decimal.mark = getOption("OutDec"),
big.mark = ifelse(decimal.mark == ",", ".", ","),
...) {
if (combine_IR == FALSE) {
if (remove_intrinsic_resistant == TRUE) {
x <- x %>% filter(R != total)
}
if (combine_IR == FALSE | combine_SI == TRUE) {
x$isolates <- x$R
} else {
x$isolates <- x$R + x$I
}
give_ab_name <- function(ab, format, language) {
format <- tolower(format)
ab_txt <- rep(format, length(ab))
for (i in 1:length(ab_txt)) {
ab_txt[i] <- gsub("ab", ab[i], ab_txt[i])
ab_txt[i] <- gsub("cid", ab_cid(ab[i]), ab_txt[i])
ab_txt[i] <- gsub("group", ab_group(ab[i], language = language), ab_txt[i])
ab_txt[i] <- gsub("atc_group1", ab_atc_group1(ab[i], language = language), ab_txt[i])
ab_txt[i] <- gsub("atc_group2", ab_atc_group2(ab[i], language = language), ab_txt[i])
ab_txt[i] <- gsub("atc", ab_atc(ab[i]), ab_txt[i])
ab_txt[i] <- gsub("name", ab_name(ab[i], language = language), ab_txt[i])
ab_txt[i]
}
ab_txt
}
y <- x %>%
filter(total >= minimum) %>%
mutate(ab = as.ab(ab),
ab_txt = give_ab_name(ab = ab, format = translate_ab, language = language)) %>%
group_by(ab, ab_txt, mo) %>%
summarise(isolates = sum(isolates, na.rm = TRUE),
total = sum(total, na.rm = TRUE)) %>%
ungroup() %>%
mutate(txt = paste0(percent(isolates / total, force_zero = TRUE, decimal.mark = decimal.mark, big.mark = big.mark),
" (", trimws(format(isolates, big.mark = big.mark)), "/",
trimws(format(total, big.mark = big.mark)), ")")) %>%
select(ab, mo, txt) %>%
select(ab, ab_txt, mo, txt) %>%
spread(mo, txt) %>%
mutate_all(~ifelse(is.na(.), "", .)) %>%
mutate(ab_group = ab_group(ab),
ab = paste0(ab_name(ab), " (", as.ab(ab), ", ", ab_atc(ab), ")")) %>%
select(ab_group, ab, everything()) %>%
arrange(ab_group, ab) %>%
mutate(ab_group = ab_group(ab, language = language),
ab_txt) %>%
select(ab_group, ab_txt, everything(), -ab) %>%
arrange(ab_group, ab_txt) %>%
mutate(ab_group = ifelse(ab_group != lag(ab_group) | is.na(lag(ab_group)), ab_group, ""))
if (add_ab_group == FALSE) {
y <- y %>% select(-ab_group) %>% rename("Antibiotic" = ab)
y <- y %>% select(-ab_group) %>% rename("Drug" = ab_txt)
colnames(y)[1] <- translate_AMR(colnames(y)[1], language = get_locale(), only_unknown = FALSE)
} else {
y <- y %>% rename("Group" = ab_group,
"Antibiotic" = ab)
"Drug" = ab_txt)
colnames(y)[1:2] <- translate_AMR(colnames(y)[1:2], language = get_locale(), only_unknown = FALSE)
}
y
@ -133,5 +167,5 @@ format.bug_drug_combinations <- function(x,
#' @importFrom crayon blue
print.bug_drug_combinations <- function(x, ...) {
print(as.data.frame(x, stringsAsFactors = FALSE))
message(blue("NOTE: Use 'format()' on this result to get a format that is ready for export or printing."))
message(blue("NOTE: Use 'format()' on this result to get a publicable/printable format."))
}