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(v1.6.0.9047) filter_ab_class() fixes

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parent
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6920c0be41
  1. 3
      .github/workflows/check.yaml
  2. 2
      DESCRIPTION
  3. 18
      NEWS.md
  4. 41
      R/aa_helper_functions.R
  5. 8
      R/ab_class_selectors.R
  6. 18
      R/eucast_rules.R
  7. 64
      R/filter_ab_class.R
  8. 4
      R/pca.R
  9. BIN
      data-raw/AMR_latest.tar.gz
  10. 6
      data-raw/_install_deps.R
  11. BIN
      data-raw/tinytest_1.2.4.patched.tar.gz
  12. BIN
      data-raw/tinytest_1.2.4.tar.gz
  13. 2
      docs/404.html
  14. 2
      docs/LICENSE-text.html
  15. 2
      docs/articles/datasets.html
  16. 2
      docs/articles/index.html
  17. 2
      docs/authors.html
  18. 16
      docs/index.html
  19. 126
      docs/news/index.html
  20. 2
      docs/pkgdown.yml
  21. 2
      docs/reference/antibiotic_class_selectors.html
  22. 6
      docs/reference/filter_ab_class.html
  23. 2
      docs/reference/index.html
  24. 2
      docs/survey.html
  25. 14
      index.md
  26. 2
      inst/tinytest/test-ab_class_selectors.R
  27. 4
      man/eucast_rules.Rd
  28. 8
      man/filter_ab_class.Rd
  29. 4
      man/mdro.Rd

3
.github/workflows/check.yaml

@ -127,6 +127,7 @@ jobs: @@ -127,6 +127,7 @@ jobs:
tar -xf data-raw/AMR_latest.tar.gz
rm -rf AMR/vignettes
Rscript -e "writeLines(readLines('AMR/DESCRIPTION')[!grepl('VignetteBuilder', readLines('AMR/DESCRIPTION'))], 'AMR/DESCRIPTION')"
cat AMR/DESCRIPTION
shell: bash
- name: Run R CMD check
@ -140,7 +141,7 @@ jobs: @@ -140,7 +141,7 @@ jobs:
R_LIBS_USER_GH_ACTIONS: ${{ env.R_LIBS_USER }}
R_RUN_TINYTEST: true
run: |
R CMD check --no-manual --no-vignettes AMR
R CMD check --no-manual --no-vignettes --no-build-vignettes --ignore-vignettes AMR
shell: bash
- name: Show unit tests output

2
DESCRIPTION

@ -1,5 +1,5 @@ @@ -1,5 +1,5 @@
Package: AMR
Version: 1.6.0.9044
Version: 1.6.0.9047
Date: 2021-05-18
Title: Antimicrobial Resistance Data Analysis
Authors@R: c(

18
NEWS.md

@ -1,4 +1,4 @@ @@ -1,4 +1,4 @@
# `AMR` 1.6.0.9044
# `AMR` 1.6.0.9047
## <small>Last updated: 18 May 2021</small>
### New
@ -43,11 +43,23 @@ @@ -43,11 +43,23 @@
* Updated `skimr::skim()` usage for MIC values to also include 25th and 75th percentiles
* Fix for plotting missing MIC/disk diffusion values
* Updated join functions to always use `dplyr` join functions if the `dplyr` package is installed - now also preserving grouped variables
* Fix for filtering on antibiotic classes (such as `filter_cephalosporins()`), which now also supports dplyr groups
* Updates for filtering on antibiotic classes (e.g., using `filter_carbapenems()`):
* Support for dplyr groups
* Support for base R row filtering:
```r
dim(example_isolates)
#> [1] 2000 49
example_isolates[filter_carbapenems(), ]
#> ℹ Applying `filter_carbapenems()`: values in any of columns 'IPM' (imipenem)
#> or 'MEM' (meropenem) are either "R", "S" or "I"
#> [1] 962 49
```
* Antibiotic class selectors (such as `cephalosporins()`) now maintain the column order from the original data
* Fix for selecting columns using `fluoroquinolones()`
### Other
* All unit tests are now processed by the `tinytest` package, instead of the `testthat` package. The `testthat` package unfortunately requires tons of dependencies that are also heavy and only usable for recent R versions, defeating the purpose to test our package under less recent R versions. On the contrary, the `tinytest` package is very lightweight and dependency-free.
* All unit tests are now processed by the `tinytest` package, instead of the `testthat` package. The `testthat` package unfortunately requires tons of dependencies that are also heavy and only usable for recent R versions, disallowing developers to test a package under any R 3.* version. On the contrary, the `tinytest` package is very lightweight and dependency-free.
# `AMR` 1.6.0

41
R/aa_helper_functions.R

@ -493,14 +493,30 @@ dataset_UTF8_to_ASCII <- function(df) { @@ -493,14 +493,30 @@ dataset_UTF8_to_ASCII <- function(df) {
}
# for eucast_rules() and mdro(), creates markdown output with URLs and names
create_ab_documentation <- function(ab) {
create_eucast_ab_documentation <- function() {
x <- trimws(unique(toupper(unlist(strsplit(eucast_rules_file$then_change_these_antibiotics, ",")))))
ab <- character()
for (val in x) {
if (val %in% ls(envir = asNamespace("AMR"))) {
# antibiotic group names, as defined in data-raw/_internals.R, such as `CARBAPENEMS`
val <- eval(parse(text = val), envir = asNamespace("AMR"))
} else if (val %in% AB_lookup$ab) {
# separate drugs, such as `AMX`
val <- as.ab(val)
} else {
stop_("antimicrobial agent (group) not found in EUCAST rules file: ", val.bak, call = FALSE)
}
ab <- c(ab, val)
}
ab <- unique(ab)
atcs <- ab_atc(ab)
# only keep ABx with an ATC code:
ab <- ab[!is.na(atcs)]
ab_names <- ab_name(ab, language = NULL, tolower = TRUE)
ab <- ab[order(ab_names)]
ab_names <- ab_names[order(ab_names)]
atcs <- ab_atc(ab)
atcs[!is.na(atcs)] <- paste0("[", atcs[!is.na(atcs)], "](", ab_url(ab[!is.na(atcs)]), ")")
atcs[is.na(atcs)] <- "no ATC code"
out <- paste0(ab_names, " (`", ab, "`, ", atcs, ")", collapse = ", ")
atc_txt <- paste0("[", atcs[!is.na(atcs)], "](", ab_url(ab), ")")
out <- paste0(ab_names, " (`", ab, "`, ", atc_txt, ")", collapse = ", ")
substr(out, 1, 1) <- toupper(substr(out, 1, 1))
out
}
@ -638,9 +654,10 @@ meet_criteria <- function(object, @@ -638,9 +654,10 @@ meet_criteria <- function(object,
object <- tolower(object)
is_in <- tolower(is_in)
}
stop_ifnot(all(object %in% is_in, na.rm = TRUE), "argument `", obj_name,
"` must be ",
ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1, "either ", ""),
stop_ifnot(all(object %in% is_in, na.rm = TRUE), "argument `", obj_name, "` ",
ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
"must be either ",
"must only contain values "),
vector_or(is_in, quotes = !isTRUE(any(c("double", "numeric", "integer") %in% allow_class))),
ifelse(allow_NA == TRUE, ", or NA", ""),
call = call_depth)
@ -696,7 +713,7 @@ get_current_data <- function(arg_name, call) { @@ -696,7 +713,7 @@ get_current_data <- function(arg_name, call) {
}
}
if (as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.2) {
if (current_R_older_than(3.2)) {
# R-3.0 and R-3.1 do not have an `x` element in the call stack, rendering this function useless
if (is.na(arg_name)) {
# like in carbapenems() etc.
@ -1157,6 +1174,10 @@ time_track <- function(name = NULL) { @@ -1157,6 +1174,10 @@ time_track <- function(name = NULL) {
paste("(until now:", trimws(round(as.numeric(Sys.time()) * 1000) - pkg_env$time_start), "ms)")
}
current_R_older_than <- function(version) {
as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < version
}
# prevent dependency on package 'backports' ----
# these functions were not available in previous versions of R (last checked: R 4.0.5)
# see here for the full list: https://github.com/r-lib/backports
@ -1205,7 +1226,7 @@ lengths <- function(x, use.names = TRUE) { @@ -1205,7 +1226,7 @@ lengths <- function(x, use.names = TRUE) {
vapply(x, length, FUN.VALUE = NA_integer_, USE.NAMES = use.names)
}
if (as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.1) {
if (current_R_older_than(3.1)) {
# R-3.0 does not contain these functions, set them here to prevent installation failure
# (required for extension of the <mic> class)
cospi <- function(...) 1

8
R/ab_class_selectors.R

@ -183,7 +183,7 @@ ab_selector <- function(ab_class, @@ -183,7 +183,7 @@ ab_selector <- function(ab_class,
meet_criteria(function_name, allow_class = "character", has_length = 1, .call_depth = 1)
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1, .call_depth = 1)
if (as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.2) {
if (current_R_older_than(3.2)) {
warning_("antibiotic class selectors such as ", function_name,
"() require R version 3.2 or later - you have ", R.version.string,
call = FALSE)
@ -229,11 +229,9 @@ ab_selector <- function(ab_class, @@ -229,11 +229,9 @@ ab_selector <- function(ab_class,
need_name <- tolower(gsub("[^a-zA-Z]", "", agents)) != tolower(gsub("[^a-zA-Z]", "", agents_names))
agents_formatted[need_name] <- paste0(agents_formatted[need_name],
" (", agents_names[need_name], ")")
message_("Selecting ", ab_group, ": ",
message_("Applying `", function_name, "()`: selecting ",
ifelse(length(agents) == 1, "column ", "columns "),
vector_and(agents_formatted, quotes = FALSE),
as_note = FALSE,
extra_indent = 6)
vector_and(agents_formatted, quotes = FALSE))
}
remember_thrown_message(function_name)
}

18
R/eucast_rules.R

@ -93,9 +93,9 @@ format_eucast_version_nr <- function(version, markdown = TRUE) { @@ -93,9 +93,9 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
#' @section Antibiotics:
#' To define antibiotics column names, leave as it is to determine it automatically with [guess_ab_col()] or input a text (case-insensitive), or use `NULL` to skip a column (e.g. `TIC = NULL` to skip ticarcillin). Manually defined but non-existing columns will be skipped with a warning.
#'
#' The following antibiotics are used for the functions [eucast_rules()] and [mdro()]. These are shown below in the format 'name (`antimicrobial ID`, [ATC code](https://www.whocc.no/atc/structure_and_principles/))', sorted alphabetically:
#' The following antibiotics are eligible for the functions [eucast_rules()] and [mdro()]. These are shown below in the format 'name (`antimicrobial ID`, [ATC code](https://www.whocc.no/atc/structure_and_principles/))', sorted alphabetically:
#'
#' `r create_ab_documentation(c("AMC", "AMK", "AMP", "AMX", "APL", "APX", "ATM", "AVB", "AVO", "AZD", "AZL", "AZM", "BAM", "BPR", "CAC", "CAT", "CAZ", "CCP", "CCV", "CCX", "CDC", "CDR", "CDZ", "CEC", "CED", "CEI", "CEM", "CEP", "CFM", "CFM1", "CFP", "CFR", "CFS", "CFZ", "CHE", "CHL", "CIC", "CID", "CIP", "CLI", "CLM", "CLO", "CLR", "CMX", "CMZ", "CND", "COL", "CPD", "CPI", "CPL", "CPM", "CPO", "CPR", "CPT", "CPX", "CRB", "CRD", "CRN", "CRO", "CSL", "CTB", "CTC", "CTF", "CTL", "CTS", "CTT", "CTX", "CTZ", "CXM", "CYC", "CZA", "CZD", "CZO", "CZP", "CZX", "DAL", "DAP", "DIC", "DIR", "DIT", "DIX", "DIZ", "DKB", "DOR", "DOX", "ENX", "EPC", "ERY", "ETP", "FEP", "FLC", "FLE", "FLR1", "FOS", "FOV", "FOX", "FOX1", "FUS", "GAT", "GEM", "GEN", "GRX", "HAP", "HET", "IPM", "ISE", "JOS", "KAN", "LEN", "LEX", "LIN", "LNZ", "LOM", "LOR", "LTM", "LVX", "MAN", "MCM", "MEC", "MEM", "MET", "MEV", "MEZ", "MFX", "MID", "MNO", "MTM", "NAC", "NAF", "NAL", "NEO", "NET", "NIT", "NOR", "NOV", "NVA", "OFX", "OLE", "ORI", "OXA", "PAZ", "PEF", "PEN", "PHE", "PHN", "PIP", "PLB", "PME", "PNM", "PRC", "PRI", "PRL", "PRP", "PRU", "PVM", "QDA", "RAM", "RFL", "RID", "RIF", "ROK", "RST", "RXT", "SAM", "SBC", "SDI", "SDM", "SIS", "SLF", "SLF1", "SLF10", "SLF11", "SLF12", "SLF13", "SLF2", "SLF3", "SLF4", "SLF5", "SLF6", "SLF7", "SLF8", "SLF9", "SLT1", "SLT2", "SLT3", "SLT4", "SLT5", "SLT6", "SMX", "SPI", "SPX", "SRX", "STR", "STR1", "SUD", "SUL", "SUT", "SXT", "SZO", "TAL", "TAZ", "TCC", "TCM", "TCY", "TEC", "TEM", "TGC", "THA", "TIC", "TIO", "TLT", "TLV", "TMP", "TMX", "TOB", "TRL", "TVA", "TZD", "TZP", "VAN"))`
#' `r create_eucast_ab_documentation()`
#' @aliases EUCAST
#' @rdname eucast_rules
#' @export
@ -317,21 +317,23 @@ eucast_rules <- function(x, @@ -317,21 +317,23 @@ eucast_rules <- function(x,
# Some helper functions ---------------------------------------------------
get_antibiotic_columns <- function(x, cols_ab) {
x <- strsplit(x, ", *")[[1]]
x <- trimws(unique(toupper(unlist(strsplit(x, ",")))))
x_new <- character()
for (val in x) {
if (toupper(val) %in% ls(envir = asNamespace("AMR"))) {
if (val %in% ls(envir = asNamespace("AMR"))) {
# antibiotic group names, as defined in data-raw/_internals.R, such as `CARBAPENEMS`
val <- eval(parse(text = toupper(val)), envir = asNamespace("AMR"))
} else if (toupper(val) %in% AB_lookup$ab) {
val <- eval(parse(text = val), envir = asNamespace("AMR"))
} else if (val %in% AB_lookup$ab) {
# separate drugs, such as `AMX`
val <- as.ab(val)
} else {
stop_("antimicrobial agent (group) not found in EUCAST rules file: ", val, call = FALSE)
stop_("unknown antimicrobial agent (group) in EUCAST rules file: ", val, call = FALSE)
}
x_new <- c(x_new, val)
}
cols_ab[match(x_new, names(cols_ab))]
x_new <- unique(x_new)
out <- cols_ab[match(x_new, names(cols_ab))]
out[!is.na(out)]
}
get_antibiotic_names <- function(x) {
x <- x %pm>%

64
R/filter_ab_class.R

@ -40,9 +40,12 @@ @@ -40,9 +40,12 @@
#' @seealso [antibiotic_class_selectors()] for the `select()` equivalent.
#' @export
#' @examples
#' filter_aminoglycosides(example_isolates)
#'
#' x <- filter_carbapenems(example_isolates)
#' \donttest{
#' # base R filter options (requires R >= 3.2)
#' example_isolates[filter_carbapenems(), ]
#' example_isolates[which(filter_carbapenems() & mo_is_gram_negative()), ]
#'
#' if (require("dplyr")) {
#'
#' # filter on isolates that have any result for any aminoglycoside
@ -78,6 +81,7 @@ @@ -78,6 +81,7 @@
#' example_isolates %>% filter_carbapenems("R", "all")
#' example_isolates %>% filter(across(carbapenems(), ~. == "R"))
#' example_isolates %>% filter(across(carbapenems(), function(x) x == "R"))
#' example_isolates %>% filter(filter_carbapenems("R", "all"))
#' }
#' }
filter_ab_class <- function(x,
@ -90,15 +94,29 @@ filter_ab_class <- function(x, @@ -90,15 +94,29 @@ filter_ab_class <- function(x,
if (is.null(.call_depth)) {
.call_depth <- 0
}
.fn <- list(...)$`.fn`
if (is.null(.fn)) {
.fn <- "filter_ab_class"
}
return_only_row_indices <- FALSE
if (missing(x) || is_null_or_grouped_tbl(x)) {
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
# is also fix for using a grouped df as input (a dot as first argument)
x <- get_current_data(arg_name = "x", call = -2 - .call_depth)
return_only_row_indices <- TRUE
}
meet_criteria(x, allow_class = "data.frame", .call_depth = .call_depth)
meet_criteria(ab_class, allow_class = "character", has_length = 1, .call_depth = .call_depth)
meet_criteria(result, allow_class = "character", has_length = c(1, 2, 3), allow_NULL = TRUE, .call_depth = .call_depth)
if (!is.null(result)) {
result <- toupper(result)
}
meet_criteria(result, allow_class = "character", has_length = c(1, 2, 3), is_in = c("S", "I", "R"), allow_NULL = TRUE, .call_depth = .call_depth)
meet_criteria(scope, allow_class = "character", has_length = 1, is_in = c("all", "any"), .call_depth = .call_depth)
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1, .call_depth = .call_depth)
check_dataset_integrity()
# save to return later
x.bak <- x
x <- as.data.frame(x, stringsAsFactors = FALSE)
@ -109,9 +127,6 @@ filter_ab_class <- function(x, @@ -109,9 +127,6 @@ filter_ab_class <- function(x,
# make result = "SI" works too:
result <- unlist(strsplit(result, ""))
stop_ifnot(all(result %in% c("S", "I", "R")), "`result` must be one or more of: 'S', 'I', 'R'")
stop_ifnot(all(scope %in% c("any", "all")), "`scope` must be one of: 'any', 'all'")
# get all columns in data with names that resemble antibiotics
ab_in_data <- get_column_abx(x, info = FALSE, only_rsi_columns = only_rsi_columns, sort = FALSE)
@ -180,16 +195,18 @@ filter_ab_class <- function(x, @@ -180,16 +195,18 @@ filter_ab_class <- function(x,
agents_formatted[need_name] <- paste0(agents_formatted[need_name],
" (", agents_names[need_name], ")")
message_("Filtering on ", ab_group, ": ", scope,
message_("Applying `", .fn, "()`: ", scope,
vector_or(agents_formatted, quotes = FALSE, last_sep = scope_txt),
operator, " ", vector_or(result, quotes = TRUE),
as_note = FALSE,
extra_indent = 6)
operator, " ", vector_or(result, quotes = TRUE))
x_transposed <- as.list(as.data.frame(t(x[, agents, drop = FALSE]), stringsAsFactors = FALSE))
filtered <- vapply(FUN.VALUE = logical(1), x_transposed, function(y) scope_fn(y %in% result, na.rm = TRUE))
# this returns the original data with the filtering, also preserving attributes (such as dplyr groups)
x.bak[which(filtered), , drop = FALSE]
if (return_only_row_indices == TRUE) {
filtered
} else {
# this returns the original data with the filtering, also preserving attributes (such as dplyr groups)
x.bak[which(filtered), , drop = FALSE]
}
}
#' @rdname filter_ab_class
@ -205,6 +222,7 @@ filter_aminoglycosides <- function(x, @@ -205,6 +222,7 @@ filter_aminoglycosides <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_aminoglycosides",
...)
}
@ -221,6 +239,7 @@ filter_betalactams <- function(x, @@ -221,6 +239,7 @@ filter_betalactams <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_betalactams",
...)
}
#' @rdname filter_ab_class
@ -236,6 +255,7 @@ filter_carbapenems <- function(x, @@ -236,6 +255,7 @@ filter_carbapenems <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_carbapenems",
...)
}
@ -252,6 +272,7 @@ filter_cephalosporins <- function(x, @@ -252,6 +272,7 @@ filter_cephalosporins <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_cephalosporins",
...)
}
@ -268,6 +289,7 @@ filter_1st_cephalosporins <- function(x, @@ -268,6 +289,7 @@ filter_1st_cephalosporins <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_1st_cephalosporins",
...)
}
@ -284,6 +306,7 @@ filter_2nd_cephalosporins <- function(x, @@ -284,6 +306,7 @@ filter_2nd_cephalosporins <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_2nd_cephalosporins",
...)
}
@ -300,6 +323,7 @@ filter_3rd_cephalosporins <- function(x, @@ -300,6 +323,7 @@ filter_3rd_cephalosporins <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_3rd_cephalosporins",
...)
}
@ -316,6 +340,7 @@ filter_4th_cephalosporins <- function(x, @@ -316,6 +340,7 @@ filter_4th_cephalosporins <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_4th_cephalosporins",
...)
}
@ -332,6 +357,7 @@ filter_5th_cephalosporins <- function(x, @@ -332,6 +357,7 @@ filter_5th_cephalosporins <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_5th_cephalosporins",
...)
}
@ -348,6 +374,7 @@ filter_fluoroquinolones <- function(x, @@ -348,6 +374,7 @@ filter_fluoroquinolones <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_fluoroquinolones",
...)
}
@ -364,6 +391,7 @@ filter_glycopeptides <- function(x, @@ -364,6 +391,7 @@ filter_glycopeptides <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_glycopeptides",
...)
}
@ -380,6 +408,7 @@ filter_macrolides <- function(x, @@ -380,6 +408,7 @@ filter_macrolides <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_macrolides",
...)
}
@ -396,6 +425,7 @@ filter_oxazolidinones <- function(x, @@ -396,6 +425,7 @@ filter_oxazolidinones <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_oxazolidinones",
...)
}
@ -412,6 +442,7 @@ filter_penicillins <- function(x, @@ -412,6 +442,7 @@ filter_penicillins <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_penicillins",
...)
}
@ -428,6 +459,7 @@ filter_tetracyclines <- function(x, @@ -428,6 +459,7 @@ filter_tetracyclines <- function(x,
scope = scope,
only_rsi_columns = only_rsi_columns,
.call_depth = 1,
.fn = "filter_tetracyclines",
...)
}
@ -448,7 +480,7 @@ find_ab_group <- function(ab_class) { @@ -448,7 +480,7 @@ find_ab_group <- function(ab_class) {
subset(group %like% ab_class |
atc_group1 %like% ab_class |
atc_group2 %like% ab_class) %pm>%
pm_pull(group) %pm>%
pm_pull(group) %pm>%
unique() %pm>%
tolower() %pm>%
sort() %pm>%
@ -466,7 +498,9 @@ find_ab_names <- function(ab_group, n = 3) { @@ -466,7 +498,9 @@ find_ab_names <- function(ab_group, n = 3) {
antibiotics$ab %unlike% "[0-9]$"), ]$name
if (length(drugs) < n) {
# now try it all
drugs <- antibiotics[which(antibiotics$group %like% ab_group &
drugs <- antibiotics[which((antibiotics$group %like% ab_group |
antibiotics$atc_group1 %like% ab_group |
antibiotics$atc_group2 %like% ab_group) &
antibiotics$ab %unlike% "[0-9]$"), ]$name
}
vector_or(ab_name(sample(drugs, size = min(n, length(drugs)), replace = FALSE),

4
R/pca.R

@ -106,7 +106,7 @@ pca <- function(x, @@ -106,7 +106,7 @@ pca <- function(x,
tryCatch(colnames(x) <- as.character(dots)[2:length(dots)],
error = function(e) warning("column names could not be set"))
# keep only [numeric] columns
# keep only numeric columns
x <- x[, vapply(FUN.VALUE = logical(1), x, function(y) is.numeric(y))]
# bind the data set with the non-numeric columns
x <- cbind(x.bak[, vapply(FUN.VALUE = logical(1), x.bak, function(y) !is.numeric(y) & !all(is.na(y))), drop = FALSE], x)
@ -120,7 +120,7 @@ pca <- function(x, @@ -120,7 +120,7 @@ pca <- function(x,
message_("Columns selected for PCA: ", vector_and(font_bold(colnames(pca_data), collapse = NULL), quotes = TRUE),
". Total observations available: ", nrow(pca_data), ".")
if (as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.4) {
if (current_R_older_than(3.4)) {
# stats::prcomp prior to 3.4.0 does not have the 'rank.' argument
pca_model <- prcomp(pca_data, retx = retx, center = center, scale. = scale., tol = tol)
} else {

BIN
data-raw/AMR_latest.tar.gz

Binary file not shown.

6
data-raw/_install_deps.R

@ -26,11 +26,9 @@ @@ -26,11 +26,9 @@
install.packages("data-raw/AMR_latest.tar.gz", dependencies = FALSE)
# some old R instances have trouble installing tinytest, so we ship it too
# R < 3.2 does not contain trimws(), which is part of this script and of a tinytest script
trimws <- AMR:::trimws
install.packages("data-raw/tinytest_1.2.4.tar.gz")
install.packages("data-raw/tinytest_1.2.4.patched.tar.gz")
pkg_suggests <- trimws(unlist(strsplit(packageDescription("AMR")$Suggests, ",(\n)?")))
pkg_suggests <- AMR:::trimws(unlist(strsplit(packageDescription("AMR")$Suggests, ",(\n)?")))
to_install <- pkg_suggests[!pkg_suggests %in% rownames(utils::installed.packages())]
to_update <- as.data.frame(utils::old.packages(repos = "https://cran.rstudio.com/"), stringsAsFactors = FALSE)

BIN
data-raw/tinytest_1.2.4.patched.tar.gz

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BIN
data-raw/tinytest_1.2.4.tar.gz

Binary file not shown.

2
docs/404.html

@ -81,7 +81,7 @@ @@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="https://msberends.github.io/AMR//index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9044</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9047</span>
</span>
</div>

2
docs/LICENSE-text.html

@ -81,7 +81,7 @@ @@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9044</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9047</span>
</span>
</div>

2
docs/articles/datasets.html

@ -39,7 +39,7 @@ @@ -39,7 +39,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9044</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9047</span>
</span>
</div>

2
docs/articles/index.html

@ -81,7 +81,7 @@ @@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9044</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9047</span>
</span>
</div>

2
docs/authors.html

@ -81,7 +81,7 @@ @@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9044</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9047</span>
</span>
</div>

16
docs/index.html

@ -42,7 +42,7 @@ @@ -42,7 +42,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9044</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9047</span>
</span>
</div>
@ -221,13 +221,13 @@ @@ -221,13 +221,13 @@
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>bacteria <span class="op">=</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">bacteria</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
<span class="co">#&gt; NOTE: Using column 'mo' as input for mo_is_gram_negative()</span>
<span class="co">#&gt; NOTE: Using column 'mo' as input for mo_is_intrinsic_resistant()</span>
<span class="co">#&gt; NOTE: Determining intrinsic resistance based on 'EUCAST Expert Rules' and</span>
<span class="co">#&gt; 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2 (2020).</span>
<span class="co">#&gt; Selecting aminoglycosides: columns 'AMK' (amikacin), 'GEN' (gentamicin), </span>
<span class="co">#&gt; 'KAN' (kanamycin) and 'TOB' (tobramycin)</span>
<span class="co">#&gt; Selecting carbapenems: columns 'IPM' (imipenem) and 'MEM' (meropenem)</span></code></pre></div>
<span class="co">#&gt; Using column 'mo' as input for mo_is_gram_negative()</span>
<span class="co">#&gt; Using column 'mo' as input for mo_is_intrinsic_resistant()</span>
<span class="co">#&gt; Determining intrinsic resistance based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic</span>
<span class="co">#&gt; Resistance and Unusual Phenotypes' v3.2 (2020)</span>
<span class="co">#&gt; ℹ Applying `aminoglycosides()`: selecting columns 'AMK' (amikacin), 'GEN' (gentamicin), 'KAN'</span>
<span class="co">#&gt; (kanamycin) and 'TOB' (tobramycin)</span>
<span class="co">#&gt; ℹ Applying `carbapenems()`: selecting columns 'IPM' (imipenem) and 'MEM' (meropenem)</span></code></pre></div>
<p>With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (<code><a href="reference/mo_property.html">mo_is_gram_negative()</a></code> and <code><a href="reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>) and a column selection on two antibiotic groups (<code><a href="reference/antibiotic_class_selectors.html">aminoglycosides()</a></code> and <code><a href="reference/antibiotic_class_selectors.html">carbapenems()</a></code>), the reference data about <a href="./reference/microorganisms.html">all microorganisms</a> and <a href="./reference/antibiotics.html">all antibiotics</a> in the <code>AMR</code> package make sure you get what you meant:</p>
<table class="table">
<thead><tr class="header">

126
docs/news/index.html

@ -81,7 +81,7 @@ @@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9044</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9047</span>
</span>
</div>
@ -236,9 +236,9 @@ @@ -236,9 +236,9 @@
<small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
</div>
<div id="amr-1609044" class="section level1">
<h1 class="page-header" data-toc-text="1.6.0.9044">
<a href="#amr-1609044" class="anchor"></a><small> Unreleased </small><code>AMR</code> 1.6.0.9044</h1>
<div id="amr-1609047" class="section level1">
<h1 class="page-header" data-toc-text="1.6.0.9047">
<a href="#amr-1609047" class="anchor"></a><small> Unreleased </small><code>AMR</code> 1.6.0.9047</h1>
<div id="last-updated-18-may-2021" class="section level2">
<h2 class="hasAnchor">
<a href="#last-updated-18-may-2021" class="anchor"></a><small>Last updated: 18 May 2021</small>
@ -307,15 +307,33 @@ @@ -307,15 +307,33 @@
<li>Updated <code><a href="https://docs.ropensci.org/skimr/reference/skim.html">skimr::skim()</a></code> usage for MIC values to also include 25th and 75th percentiles</li>
<li>Fix for plotting missing MIC/disk diffusion values</li>
<li>Updated join functions to always use <code>dplyr</code> join functions if the <code>dplyr</code> package is installed - now also preserving grouped variables</li>
<li>Fix for filtering on antibiotic classes (such as <code><a href="../reference/filter_ab_class.html">filter_cephalosporins()</a></code>), which now also supports dplyr groups</li>
<li>Updates for filtering on antibiotic classes (e.g., using <code><a href="../reference/filter_ab_class.html">filter_carbapenems()</a></code>):
<ul>
<li><p>Support for dplyr groups</p></li>
<li>
<p>Support for base R row filtering:</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="https://rdrr.io/r/base/dim.html">dim</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
<span class="co">#&gt; [1] 2000 49</span>
<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="../reference/filter_ab_class.html">filter_carbapenems</a></span><span class="op">(</span><span class="op">)</span>, <span class="op">]</span>
<span class="co">#&gt; ℹ Applying `filter_carbapenems()`: values in any of columns 'IPM' (imipenem)</span>
<span class="co">#&gt; or 'MEM' (meropenem) are either "R", "S" or "I"</span>
<span class="co">#&gt; [1] 962 49</span></code></pre></div>
</li>
</ul>
</li>
<li>Antibiotic class selectors (such as <code><a href="../reference/antibiotic_class_selectors.html">cephalosporins()</a></code>) now maintain the column order from the original data</li>
<li>Fix for selecting columns using <code><a href="../reference/antibiotic_class_selectors.html">fluoroquinolones()</a></code>
</li>
</ul>
</div>
<div id="other" class="section level3">
<h3 class="hasAnchor">
<a href="#other" class="anchor"></a>Other</h3>
<ul>
<li>All unit tests are now processed by the <code>tinytest</code> package, instead of the <code>testthat</code> package. The <code>testthat</code> package unfortunately requires tons of dependencies that are also heavy and only usable for recent R versions, defeating the purpose to test our package under less recent R versions. On the contrary, the <code>tinytest</code> package is very lightweight and dependency-free.</li>
<li>All unit tests are now processed by the <code>tinytest</code> package, instead of the <code>testthat</code> package. The <code>testthat</code> package unfortunately requires tons of dependencies that are also heavy and only usable for recent R versions, disallowing developers to test a package under any R 3.* version. On the contrary, the <code>tinytest</code> package is very lightweight and dependency-free.</li>
</ul>
</div>
</div>
@ -348,7 +366,7 @@ @@ -348,7 +366,7 @@
</li>
<li>
<p>Functions <code><a href="../reference/antibiotic_class_selectors.html">oxazolidinones()</a></code> (an antibiotic selector function) and <code><a href="../reference/filter_ab_class.html">filter_oxazolidinones()</a></code> (an antibiotic filter function) to select/filter on e.g. linezolid and tedizolid</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
<span class="va">x</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">date</span>, <span class="va">hospital_id</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">oxazolidinones</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
@ -361,7 +379,7 @@ @@ -361,7 +379,7 @@
<li><p><code>ggplot()</code> generics for classes <code>&lt;mic&gt;</code> and <code>&lt;disk&gt;</code></p></li>
<li>
<p>Function <code><a href="../reference/mo_property.html">mo_is_yeast()</a></code>, which determines whether a microorganism is a member of the taxonomic class Saccharomycetes or the taxonomic order Saccharomycetales:</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/mo_property.html">mo_kingdom</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Aspergillus"</span>, <span class="st">"Candida"</span><span class="op">)</span><span class="op">)</span>
<span class="co">#&gt; [1] "Fungi" "Fungi"</span>
@ -373,7 +391,7 @@ @@ -373,7 +391,7 @@
<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html">which</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_is_yeast</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>, <span class="op">]</span> <span class="co"># base R</span>
<span class="va">example_isolates</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_is_yeast</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="co"># dplyr</span></code></pre></div>
<p>The <code><a href="../reference/mo_property.html">mo_type()</a></code> function has also been updated to reflect this change:</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/mo_property.html">mo_type</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Aspergillus"</span>, <span class="st">"Candida"</span><span class="op">)</span><span class="op">)</span>
<span class="co"># [1] "Fungi" "Yeasts"</span>
@ -383,7 +401,7 @@ @@ -383,7 +401,7 @@
<li><p>Added Pretomanid (PMD, J04AK08) to the <code>antibiotics</code> data set</p></li>
<li>
<p>MIC values (see <code><a href="../reference/as.mic.html">as.mic()</a></code>) can now be used in any mathematical processing, such as usage inside functions <code><a href="https://rdrr.io/r/base/Extremes.html">min()</a></code>, <code><a href="https://rdrr.io/r/base/Extremes.html">max()</a></code>, <code><a href="https://rdrr.io/r/base/range.html">range()</a></code>, and with binary operators (<code><a href="https://rdrr.io/r/base/Arithmetic.html">+</a></code>, <code><a href="https://rdrr.io/r/base/Arithmetic.html">-</a></code>, etc.). This allows for easy distribution analysis and fast filtering on MIC values:</p>
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/random.html">random_mic</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span>
<span class="va">x</span>
@ -466,7 +484,7 @@ @@ -466,7 +484,7 @@
<ul>
<li>
<p>Functions <code><a href="../reference/get_episode.html">get_episode()</a></code> and <code><a href="../reference/get_episode.html">is_new_episode()</a></code> to determine (patient) episodes which are not necessarily based on microorganisms. The <code><a href="../reference/get_episode.html">get_episode()</a></code> function returns the index number of the episode per group, while the <code><a href="../reference/get_episode.html">is_new_episode()</a></code> function returns values <code>TRUE</code>/<code>FALSE</code> to indicate whether an item in a vector is the start of a new episode. They also support <code>dplyr</code>s grouping (i.e. using <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code>):</p>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
<span class="va">example_isolates</span> <span class="op">%&gt;%</span>
@ -520,7 +538,7 @@ @@ -520,7 +538,7 @@
<code><a href="../reference/mdro.html">mdr_cmi2012()</a></code>,</li>
<li><code><a href="../reference/mdro.html">eucast_exceptional_phenotypes()</a></code></li>
</ul>
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># to select first isolates that are Gram-negative </span>
<span class="co"># and view results of cephalosporins and aminoglycosides:</span>
@ -532,7 +550,7 @@ @@ -532,7 +550,7 @@
</li>
<li>
<p>For antibiotic selection functions (such as <code><a href="../reference/antibiotic_class_selectors.html">cephalosporins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">aminoglycosides()</a></code>) to select columns based on a certain antibiotic group, the dependency on the <code>tidyselect</code> package was removed, meaning that they can now also be used without the need to have this package installed and now also work in base R function calls (they rely on R 3.2 or later):</p>
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># above example in base R:</span>
<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html">which</a></span><span class="op">(</span><span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="op">)</span> <span class="op">&amp;</span> <span class="fu"><a href="../reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>,
@ -582,7 +600,7 @@ @@ -582,7 +600,7 @@
<li>
<p>Data set <code>intrinsic_resistant</code>. This data set contains all bug-drug combinations where the ‘bug’ is intrinsic resistant to the ‘drug’ according to the latest EUCAST insights. It contains just two columns: <code>microorganism</code> and <code>antibiotic</code>.</p>
<p>Curious about which enterococci are actually intrinsic resistant to vancomycin?</p>
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
@ -605,7 +623,7 @@ @@ -605,7 +623,7 @@
<ul>
<li>
<p>Support for using <code>dplyr</code>’s <code><a href="https://dplyr.tidyverse.org/reference/across.html">across()</a></code> to interpret MIC values or disk zone diameters, which also automatically determines the column with microorganism names or codes.</p>
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># until dplyr 1.0.0</span>
<span class="va">your_data</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_if</a></span><span class="op">(</span><span class="va">is.mic</span>, <span class="va">as.rsi</span><span class="op">)</span>
@ -623,7 +641,7 @@ @@ -623,7 +641,7 @@
</li>
<li>
<p>Added intelligent data cleaning to <code><a href="../reference/as.disk.html">as.disk()</a></code>, so numbers can also be extracted from text and decimal numbers will always be rounded up:</p>
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/as.disk.html">as.disk</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"disk zone: 23.4 mm"</span>, <span class="fl">23.4</span><span class="op">)</span><span class="op">)</span>
<span class="co">#&gt; Class &lt;disk&gt;</span>
@ -683,7 +701,7 @@ @@ -683,7 +701,7 @@
<li><p>Function <code><a href="../reference/ab_from_text.html">ab_from_text()</a></code> to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses <code><a href="../reference/as.ab.html">as.ab()</a></code> internally</p></li>
<li>
<p><a href="https://tidyselect.r-lib.org/reference/language.html">Tidyverse selection helpers</a> for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows selection helpers, like <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> and <code><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html">tidyr::pivot_longer()</a></code>:</p>
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
@ -869,7 +887,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -869,7 +887,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline</p></li>
<li>
<p>Interpretation from MIC values (and disk zones) to R/SI can now be used with <code><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at()</a></code> of the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">yourdata</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span><span class="op">(</span><span class="va">antibiotic1</span><span class="op">:</span><span class="va">antibiotic25</span><span class="op">)</span>, <span class="va">as.rsi</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span><span class="op">)</span>
@ -897,7 +915,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -897,7 +915,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Support for LOINC codes in the <code>antibiotics</code> data set. Use <code><a href="../reference/ab_property.html">ab_loinc()</a></code> to retrieve LOINC codes, or use a LOINC code for input in any <code>ab_*</code> function:</p>
<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/ab_property.html">ab_loinc</a></span><span class="op">(</span><span class="st">"ampicillin"</span><span class="op">)</span>
<span class="co">#&gt; [1] "21066-6" "3355-5" "33562-0" "33919-2" "43883-8" "43884-6" "87604-5"</span>
@ -908,7 +926,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -908,7 +926,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>Support for SNOMED CT codes in the <code>microorganisms</code> data set. Use <code><a href="../reference/mo_property.html">mo_snomed()</a></code> to retrieve SNOMED codes, or use a SNOMED code for input in any <code>mo_*</code> function:</p>
<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/mo_property.html">mo_snomed</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span>
<span class="co">#&gt; [1] 115329001 3092008 113961008</span>
@ -972,11 +990,11 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -972,11 +990,11 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>If you were dependent on the old Enterobacteriaceae family e.g. by using in your code:</p>
<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_family</a></span><span class="op">(</span><span class="va">somebugs</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Enterobacteriaceae"</span><span class="op">)</span> <span class="va">...</span></code></pre></div>
<p>then please adjust this to:</p>
<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">somebugs</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Enterobacterales"</span><span class="op">)</span> <span class="va">...</span></code></pre></div>
</li>
@ -990,7 +1008,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -990,7 +1008,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Functions <code><a href="../reference/proportion.html">susceptibility()</a></code> and <code><a href="../reference/proportion.html">resistance()</a></code> as aliases of <code><a href="../reference/proportion.html">proportion_SI()</a></code> and <code><a href="../reference/proportion.html">proportion_R()</a></code>, respectively. These functions were added to make it more clear that “I” should be considered susceptible and not resistant.</p>
<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
<span class="va">example_isolates</span> <span class="op">%&gt;%</span>
@ -1019,7 +1037,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1019,7 +1037,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>More intelligent way of coping with some consonants like “l” and “r”</p></li>
<li>
<p>Added a score (a certainty percentage) to <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code>, that is calculated using the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance</a>:</p>
<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Stafylococcus aureus"</span>,
<span class="st">"staphylokok aureuz"</span><span class="op">)</span><span class="op">)</span>
@ -1077,14 +1095,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1077,14 +1095,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Determination of first isolates now <strong>excludes</strong> all ‘unknown’ microorganisms at default, i.e. microbial code <code>"UNKNOWN"</code>. They can be included with the new argument <code>include_unknown</code>:</p>
<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="va">...</span>, include_unknown <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div>
<p>For WHONET users, this means that all records/isolates with organism code <code>"con"</code> (<em>contamination</em>) will be excluded at default, since <code>as.mo("con") = "UNKNOWN"</code>. The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.</p>
</li>
<li>
<p>For code consistency, classes <code>ab</code> and <code>mo</code> will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in <code>NA</code>:</p>
<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># how it works in base R:</span>
<span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/factor.html">factor</a></span><span class="op">(</span><span class="st">"A"</span><span class="op">)</span>
@ -1109,7 +1127,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1109,7 +1127,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Function <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> to quickly get a <code>data.frame</code> with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with <code><a href="../reference/mo_property.html">mo_shortname()</a></code> at default:</p>
<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
<span class="co">#&gt; NOTE: Using column `mo` as input for `col_mo`.</span>
@ -1132,13 +1150,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1132,13 +1150,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<span class="co">#&gt; 4 Gram-negative AMX 227 0 405 632</span>
<span class="co">#&gt; NOTE: Use 'format()' on this result to get a publicable/printable format.</span></code></pre></div>
<p>You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R <code><a href="https://rdrr.io/r/base/format.html">format()</a></code> function:</p>
<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="https://rdrr.io/r/base/format.html">format</a></span><span class="op">(</span><span class="va">x</span>, combine_IR <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
</li>
<li>
<p>Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for <code>portion_*</code> functions or <code>count_*</code> functions. This can be used to determine the empiric susceptibility of a combination therapy. A new argument <code>only_all_tested</code> (<strong>which defaults to <code>FALSE</code></strong>) replaces the old <code>also_single_tested</code> and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the <code>portion</code> and <code>count</code> help pages), where the %SI is being determined:</p>
<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># --------------------------------------------------------------------</span>
<span class="co"># only_all_tested = FALSE only_all_tested = TRUE</span>
@ -1160,7 +1178,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1160,7 +1178,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p><code>tibble</code> printing support for classes <code>rsi</code>, <code>mic</code>, <code>disk</code>, <code>ab</code> <code>mo</code>. When using <code>tibble</code>s containing antimicrobial columns, values <code>S</code> will print in green, values <code>I</code> will print in yellow and values <code>R</code> will print in red. Microbial IDs (class <code>mo</code>) will emphasise on the genus and species, not on the kingdom.</p>
<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># (run this on your own console, as this page does not support colour printing)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
@ -1242,7 +1260,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1242,7 +1260,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Function <code><a href="../reference/proportion.html">rsi_df()</a></code> to transform a <code>data.frame</code> to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions <code><a href="../reference/count.html">count_df()</a></code> and <code>portion_df()</code> to immediately show resistance percentages and number of available isolates:</p>
<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op">%&gt;%</span>
@ -1269,7 +1287,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1269,7 +1287,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li>UPEC (Uropathogenic <em>E. coli</em>)</li>
</ul>
<p>All these lead to the microbial ID of <em>E. coli</em>:</p>
<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"UPEC"</span><span class="op">)</span>
<span class="co"># B_ESCHR_COL</span>
@ -1373,7 +1391,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1373,7 +1391,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>when all values are unique it now shows a message instead of a warning</p></li>
<li>
<p>support for boxplots:</p>
<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span> <span class="op">%&gt;%</span>
@ -1466,7 +1484,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1466,7 +1484,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:</p>
<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/filter_ab_class.html">filter_aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>
<span class="fu"><a href="../reference/filter_ab_class.html">filter_carbapenems</a></span><span class="op">(</span><span class="op">)</span>
@ -1480,7 +1498,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1480,7 +1498,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<span class="fu"><a href="../reference/filter_ab_class.html">filter_macrolides</a></span><span class="op">(</span><span class="op">)</span>
<span class="fu"><a href="../reference/filter_ab_class.html">filter_tetracyclines</a></span><span class="op">(</span><span class="op">)</span></code></pre></div>
<p>The <code>antibiotics</code> data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set. For example:</p>
<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span><span class="op">(</span>result <span class="op">=</span> <span class="st">"R"</span><span class="op">)</span>
<span class="co"># Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R</span>
@ -1489,7 +1507,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1489,7 +1507,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions:</p>
<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">ab_property</span> <span class="op">-&gt;</span> <span class="fu">atc_property</span><span class="op">(</span><span class="op">)</span>
<span class="va">ab_name</span> <span class="op">-&gt;</span> <span class="fu">atc_name</span><span class="op">(</span><span class="op">)</span>
@ -1510,7 +1528,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1510,7 +1528,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>New function <code><a href="../reference/age_groups.html">age_groups()</a></code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic AMR data analysis per age group.</p></li>
<li>
<p>New function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><a href="../reference/plot.html">plot()</a></code> function can now be used for resistance prediction calculated with <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>:</p>
<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span><span class="va">septic_patients</span>, col_ab <span class="op">=</span> <span class="st">"amox"</span><span class="op">)</span>
<span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
@ -1518,13 +1536,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/ @@ -1518,13 +1536,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>Functions <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><a href="../reference/AMR-deprecated.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op"