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support for portuguese, language determination based on system
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@ -1,6 +1,6 @@
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Package: AMR
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Version: 0.3.0.9007
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Date: 2018-09-04
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Date: 2018-09-08
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Title: Antimicrobial Resistance Analysis
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Authors@R: c(
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person(
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7
NEWS.md
7
NEWS.md
@ -10,14 +10,16 @@
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* Column names of datasets `microorganisms` and `septic_patients`
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* All old syntaxes will still work with this version, but will throw warnings
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* Functions `as.atc` and `is.atc` to transform/look up antibiotic ATC codes as defined by the WHO. The existing function `guess_atc` is now an alias of `as.atc`.
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* Aliases for existing function `mo_property`: `mo_family`, `mo_genus`, `mo_species`, `mo_subspecies`, `mo_fullname`, `mo_shortname`, `mo_aerobic`, `mo_type` and `mo_gramstain`. The last two functions have a `language` parameter, with support for Spanish, German and Dutch:
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* Aliases for existing function `mo_property`: `mo_family`, `mo_genus`, `mo_species`, `mo_subspecies`, `mo_fullname`, `mo_shortname`, `mo_aerobic`, `mo_type` and `mo_gramstain`. They also come with support for German, Dutch, Spanish and Portuguese, and it defaults to the systems locale:
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```r
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mo_gramstain("E. coli")
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# [1] "Negative rods"
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mo_gramstain("E. coli", language = "de") # "de" = Deutsch / German
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# [1] "Negative Staebchen"
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# [1] "Negative Stäbchen"
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mo_gramstain("E. coli", language = "es") # "es" = Español / Spanish
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# [1] "Bacilos negativos"
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mo_fullname("S. group A") # when run on a on a Portuguese system
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# [1] "Streptococcus grupo A"
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```
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* Function `ab_property` and its aliases: `ab_official`, `ab_tradenames`, `ab_certe`, `ab_umcg`, `ab_official_nl` and `ab_trivial_nl`
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* Introduction to AMR as a vignette
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@ -34,6 +36,7 @@
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ab_atc(c("Bactroban", "Amoxil", "Zithromax", "Floxapen"))
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# [1] "R01AX06" "J01CA04" "J01FA10" "J01CF05"
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```
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* For `first_isolate`, rows will be ignored when there's no species available
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* Function `ratio` is now deprecated and will be removed in a future release, as it is not really the scope of this package
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* Fix for `as.mic` for values ending in zeroes after a real number
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* Tremendous speed improvement for `as.bactid` (now `as.mo`)
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8
R/data.R
8
R/data.R
@ -123,7 +123,7 @@
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#' Data set with human pathogenic microorganisms
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#'
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#' A data set containing 2,669 (potential) human pathogenic microorganisms. MO codes can be looked up using \code{\link{guess_mo}}.
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#' @format A \code{\link{tibble}} with 2,669 observations and 16 variables:
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#' @format A \code{\link{tibble}} with 2,669 observations and 10 variables:
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#' \describe{
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#' \item{\code{mo}}{ID of microorganism}
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#' \item{\code{bactsys}}{Bactsyscode of microorganism}
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@ -135,12 +135,6 @@
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#' \item{\code{aerobic}}{Logical whether bacteria is aerobic}
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#' \item{\code{type}}{Type of microorganism, like \code{"Bacteria"} and \code{"Fungus/yeast"}}
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#' \item{\code{gramstain}}{Gram of microorganism, like \code{"Negative rods"}}
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#' \item{\code{type_de}}{Type of microorganism in German, like \code{"Bakterien"} and \code{"Pilz/Hefe"}}
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#' \item{\code{gramstain_de}}{Gram of microorganism in German, like \code{"Negative Staebchen"}}
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#' \item{\code{type_nl}}{Type of microorganism in Dutch, like \code{"Bacterie"} and \code{"Schimmel/gist"}}
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#' \item{\code{gramstain_nl}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
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#' \item{\code{type_es}}{Type of microorganism in Spanish, like \code{"Bacteria"} and \code{"Hongo/levadura"}}
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#' \item{\code{gramstain_es}}{Gram of microorganism in Spanish, like \code{"Bacilos negativos"}}
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#' }
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# source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
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# new <- microorganisms %>% filter(genus == "Bacteroides") %>% .[1,]
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@ -326,7 +326,8 @@ first_isolate <- function(tbl,
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filter(
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row_number() %>% between(row.start,
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row.end),
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genus != '') %>%
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genus != "",
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species != "") %>%
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nrow()
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)
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@ -373,7 +374,8 @@ first_isolate <- function(tbl,
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real_first_isolate =
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if_else(
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between(row_number(), row.start, row.end)
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& genus != ''
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& genus != ""
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& species != ""
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& (other_pat_or_mo
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| days_diff >= episode_days
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| key_ab_other),
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@ -388,7 +390,8 @@ first_isolate <- function(tbl,
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real_first_isolate =
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if_else(
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between(row_number(), row.start, row.end)
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& genus != ''
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& genus != ""
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& species != ""
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& (other_pat_or_mo
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| days_diff >= episode_days),
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TRUE,
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7
R/mo.R
7
R/mo.R
@ -125,6 +125,8 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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x <- unique(x)
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x_backup <- x
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# translate to English for supported languages of mo_property
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x <- gsub("(Gruppe|gruppe|groep|grupo)", "group", x)
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# remove dots and other non-text in case of "E. coli" except spaces
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x <- gsub("[^a-zA-Z0-9 ]+", "", x)
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# but spaces before and after should be omitted
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@ -170,6 +172,11 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE) {
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x[i] <- 'HAEINF'
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next
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}
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if (tolower(x[i]) == '^c.*difficile$') {
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# avoid detection of Clostridium difficile in case of C. difficile
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x[i] <- 'CLODIF'
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next
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}
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if (tolower(x[i]) == '^st.*au$'
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| tolower(x[i]) == '^stau$'
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| tolower(x[i]) == '^staaur$') {
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208
R/mo_property.R
208
R/mo_property.R
@ -22,12 +22,13 @@
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#' @param x any (vector of) text that can be coerced to a valid microorganism code with \code{\link{as.mo}}
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#' @param property one of the column names of one of the \code{\link{microorganisms}} data set, like \code{"mo"}, \code{"bactsys"}, \code{"family"}, \code{"genus"}, \code{"species"}, \code{"fullname"}, \code{"gramstain"} and \code{"aerobic"}
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#' @inheritParams as.mo
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#' @param language language of the returned text, either one of \code{"en"} (English), \code{"de"} (German) or \code{"nl"} (Dutch)
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#' @param language language of the returned text, defaults to the systems language. Either one of \code{"en"} (English), \code{"de"} (German), \code{"nl"} (Dutch), \code{"es"} (Spanish) or \code{"pt"} (Portuguese).
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#' @source
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#' [1] Becker K \emph{et al.} \strong{Coagulase-Negative Staphylococci}. 2014. Clin Microbiol Rev. 27(4): 870–926. \url{https://dx.doi.org/10.1128/CMR.00109-13}
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#'
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#' [2] Lancefield RC \strong{A serological differentiation of human and other groups of hemolytic streptococci}. 1933. J Exp Med. 57(4): 571–95. \url{https://dx.doi.org/10.1084/jem.57.4.571}
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#' @rdname mo_property
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#' @name mo_property
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#' @return Character or logical (only \code{mo_aerobic})
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#' @export
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#' @importFrom dplyr %>% left_join pull
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@ -44,14 +45,6 @@
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#' mo_gramstain("E. coli") # "Negative rods"
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#' mo_aerobic("E. coli") # TRUE
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#'
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#' # language support for Spanish, German and Dutch
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#' mo_type("E. coli", "es") # "Bakteria"
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#' mo_type("E. coli", "de") # "Bakterien"
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#' mo_type("E. coli", "nl") # "Bacterie"
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#' mo_gramstain("E. coli", "es") # "Bacilos negativos"
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#' mo_gramstain("E. coli", "de") # "Negative Staebchen"
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#' mo_gramstain("E. coli", "nl") # "Negatieve staven"
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#'
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#'
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#' # Abbreviations known in the field
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#' mo_genus("MRSA") # "Staphylococcus"
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@ -95,26 +88,23 @@
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#' mo_fullname("S. pyo", Lancefield = TRUE) # "Streptococcus group A"
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#' mo_shortname("S. pyo") # "S. pyogenes"
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#' mo_shortname("S. pyo", Lancefield = TRUE) # "GAS"
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mo_property <- function(x, property = 'fullname', Becker = FALSE, Lancefield = FALSE) {
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property <- tolower(property[1])
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if (!property %in% colnames(microorganisms)) {
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stop("invalid property: ", property, " - use a column name of the `microorganisms` data set")
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}
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result1 <- as.mo(x = x, Becker = Becker, Lancefield = Lancefield) # this will give a warning if x cannot be coerced
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result2 <- suppressWarnings(
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data.frame(mo = result1, stringsAsFactors = FALSE) %>%
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left_join(AMR::microorganisms, by = "mo") %>%
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pull(property)
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)
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if (property != "aerobic") {
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# will else not retain logical class
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result2[x %in% c("", NA) | result2 %in% c("", NA, "(no MO)")] <- ""
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}
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result2
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}
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#' @rdname mo_property
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#' @export
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#'
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#'
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#' # Language support for German, Dutch, Spanish and Portuguese
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#' mo_type("E. coli", language = "de") # "Bakterium"
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#' mo_type("E. coli", language = "nl") # "Bacterie"
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#' mo_type("E. coli", language = "es") # "Bakteria"
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#' mo_gramstain("E. coli", language = "de") # "Negative Staebchen"
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#' mo_gramstain("E. coli", language = "nl") # "Negatieve staven"
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#' mo_gramstain("E. coli", language = "es") # "Bacilos negativos"
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#' mo_gramstain("Giardia", language = "pt") # "Parasitas"
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#'
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#' mo_fullname("S. pyo",
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#' Lancefield = TRUE,
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#' language = "de") # "Streptococcus Gruppe A"
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#' mo_fullname("S. pyo",
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#' Lancefield = TRUE,
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#' language = "nl") # "Streptococcus groep A"
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mo_family <- function(x) {
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mo_property(x, "family")
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}
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@ -127,34 +117,34 @@ mo_genus <- function(x) {
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#' @rdname mo_property
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#' @export
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mo_species <- function(x, Becker = FALSE, Lancefield = FALSE) {
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mo_property(x, "species", Becker = Becker, Lancefield = Lancefield)
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mo_species <- function(x, Becker = FALSE, Lancefield = FALSE, language = NULL) {
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mo_property(x, "species", Becker = Becker, Lancefield = Lancefield, language = language)
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}
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#' @rdname mo_property
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#' @export
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mo_subspecies <- function(x, Becker = FALSE, Lancefield = FALSE) {
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mo_property(x, "subspecies", Becker = Becker, Lancefield = Lancefield)
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mo_subspecies <- function(x, Becker = FALSE, Lancefield = FALSE, language = NULL) {
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mo_property(x, "subspecies", Becker = Becker, Lancefield = Lancefield, language = language)
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}
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#' @rdname mo_property
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#' @export
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mo_fullname <- function(x, Becker = FALSE, Lancefield = FALSE) {
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mo_property(x, "fullname", Becker = Becker, Lancefield = Lancefield)
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mo_fullname <- function(x, Becker = FALSE, Lancefield = FALSE, language = NULL) {
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mo_property(x, "fullname", Becker = Becker, Lancefield = Lancefield, language = language)
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}
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#' @rdname mo_property
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#' @export
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mo_shortname <- function(x, Becker = FALSE, Lancefield = FALSE) {
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mo_shortname <- function(x, Becker = FALSE, Lancefield = FALSE, language = NULL) {
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if (Becker %in% c(TRUE, "all") | Lancefield == TRUE) {
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res1 <- as.mo(x)
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res2 <- suppressWarnings(as.mo(x, Becker = Becker, Lancefield = Lancefield))
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res2_fullname <- mo_fullname(res2)
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res2_fullname[res2_fullname %like% "\\(CoNS\\)"] <- "CoNS"
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res2_fullname[res2_fullname %like% "\\(CoPS\\)"] <- "CoPS"
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res2_fullname <- gsub("Streptococcus group (.*)",
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"G\\1S",
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res2_fullname) # turn "Streptococcus group A" to "GAS"
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res2_fullname <- gsub("Streptococcus (group|gruppe|Gruppe|groep|grupo) (.)",
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"G\\2S",
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res2_fullname) # turn "Streptococcus group A" and "Streptococcus grupo A" to "GAS"
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res2_fullname[res2_fullname == mo_fullname(x)] <- paste0(substr(mo_genus(res2_fullname), 1, 1),
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". ",
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suppressWarnings(mo_species(res2_fullname)))
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@ -170,20 +160,20 @@ mo_shortname <- function(x, Becker = FALSE, Lancefield = FALSE) {
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result <- paste0(substr(mo_genus(x), 1, 1), ". ", suppressWarnings(mo_species(x)))
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}
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result[result %in% c(". ")] <- ""
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result
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mo_translate(result, language = language)
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}
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#' @rdname mo_property
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#' @export
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mo_type <- function(x, language = "en") {
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mo_property(x, paste0("type", checklang(language)))
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mo_type <- function(x, language = NULL) {
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mo_property(x, "type", language = language)
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}
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#' @rdname mo_property
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#' @export
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mo_gramstain <- function(x, language = "en") {
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mo_property(x, paste0("gramstain", checklang(language)))
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mo_gramstain <- function(x, language = NULL) {
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mo_property(x, "gramstain", language = language)
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}
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#' @rdname mo_property
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@ -192,15 +182,127 @@ mo_aerobic <- function(x) {
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mo_property(x, "aerobic")
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}
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checklang <- function(language) {
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language <- tolower(language[1])
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supported <- c("en", "de", "nl", "es")
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if (!language %in% c(NULL, "", supported)) {
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stop("invalid language: ", language, " - use one of ", paste0("'", sort(supported), "'", collapse = ", "), call. = FALSE)
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#' @rdname mo_property
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#' @export
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mo_property <- function(x, property = 'fullname', Becker = FALSE, Lancefield = FALSE, language = NULL) {
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property <- tolower(property[1])
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if (!property %in% colnames(microorganisms)) {
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stop("invalid property: ", property, " - use a column name of the `microorganisms` data set")
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}
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if (language %in% c(NULL, "", "en")) {
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""
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} else {
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paste0("_", language)
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result1 <- as.mo(x = x, Becker = Becker, Lancefield = Lancefield) # this will give a warning if x cannot be coerced
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result2 <- suppressWarnings(
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data.frame(mo = result1, stringsAsFactors = FALSE) %>%
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left_join(AMR::microorganisms, by = "mo") %>%
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pull(property)
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)
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if (property != "aerobic") {
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# will else not retain `logical` class
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result2[x %in% c("", NA) | result2 %in% c("", NA, "(no MO)")] <- ""
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result2 <- mo_translate(result2, language = language)
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}
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result2
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}
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#' @importFrom dplyr %>% case_when
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mo_translate <- function(x, language) {
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if (is.null(language)) {
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language <- mo_getlangcode()
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} else {
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language <- tolower(language[1])
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}
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if (language %in% c("en", "")) {
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return(x)
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}
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supported <- c("en", "de", "nl", "es", "pt")
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if (!language %in% supported) {
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stop("Unsupported language: '", language, "' - use one of ", paste0("'", sort(supported), "'", collapse = ", "), call. = FALSE)
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}
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case_when(
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# German
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language == "de" ~ x %>%
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gsub("(no MO)", "(kein MO)", ., fixed = TRUE) %>%
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gsub("Negative rods", "Negative St\u00e4bchen", ., fixed = TRUE) %>%
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gsub("Negative cocci", "Negative Kokken", ., fixed = TRUE) %>%
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gsub("Positive rods", "Positive St\u00e4bchen", ., fixed = TRUE) %>%
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gsub("Positive cocci", "Positive Kokken", ., fixed = TRUE) %>%
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gsub("Parasites", "Parasiten", ., fixed = TRUE) %>%
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gsub("Fungi and yeasts", "Pilze und Hefen", ., fixed = TRUE) %>%
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gsub("Bacteria", "Bakterium", ., fixed = TRUE) %>%
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gsub("Fungus/yeast", "Pilz/Hefe", ., fixed = TRUE) %>%
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gsub("Parasite", "Parasit", ., fixed = TRUE) %>%
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gsub("biogroup", "Biogruppe", ., fixed = TRUE) %>%
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gsub("biotype", "Biotyp", ., fixed = TRUE) %>%
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gsub("vegetative", "vegetativ", ., fixed = TRUE) %>%
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gsub("([([ ]*?)group", "\\1Gruppe", .) %>%
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gsub("([([ ]*?)Group", "\\1Gruppe", .),
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# Dutch
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language == "nl" ~ x %>%
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gsub("(no MO)", "(geen MO)", ., fixed = TRUE) %>%
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gsub("Negative rods", "Negatieve staven", ., fixed = TRUE) %>%
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gsub("Negative cocci", "Negatieve kokken", ., fixed = TRUE) %>%
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gsub("Positive rods", "Positieve staven", ., fixed = TRUE) %>%
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gsub("Positive cocci", "Positieve kokken", ., fixed = TRUE) %>%
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gsub("Parasites", "Parasieten", ., fixed = TRUE) %>%
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gsub("Fungi and yeasts", "Schimmels en gisten", ., fixed = TRUE) %>%
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gsub("Bacteria", "Bacterie", ., fixed = TRUE) %>%
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gsub("Fungus/yeast", "Schimmel/gist", ., fixed = TRUE) %>%
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gsub("Parasite", "Parasiet", ., fixed = TRUE) %>%
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gsub("biogroup", "biogroep", ., fixed = TRUE) %>%
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# gsub("biotype", "biotype", ., fixed = TRUE) %>%
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gsub("vegetative", "vegetatief", ., fixed = TRUE) %>%
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gsub("([([ ]*?)group", "\\1groep", .) %>%
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gsub("([([ ]*?)Group", "\\1Groep", .),
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# Spanish
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language == "es" ~ x %>%
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gsub("(no MO)", "(sin MO)", ., fixed = TRUE) %>%
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gsub("Negative rods", "Bacilos negativos", ., fixed = TRUE) %>%
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gsub("Negative cocci", "Cocos negativos", ., fixed = TRUE) %>%
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gsub("Positive rods", "Bacilos positivos", ., fixed = TRUE) %>%
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gsub("Positive cocci", "Cocos positivos", ., fixed = TRUE) %>%
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gsub("Parasites", "Par\u00e1sitos", ., fixed = TRUE) %>%
|
||||
gsub("Fungi and yeasts", "Hongos y levaduras", ., fixed = TRUE) %>%
|
||||
# gsub("Bacteria", "Bacteria", ., fixed = TRUE) %>%
|
||||
gsub("Fungus/yeast", "Hongo/levadura", ., fixed = TRUE) %>%
|
||||
gsub("Parasite", "Par\u00e1sito", ., fixed = TRUE) %>%
|
||||
gsub("biogroup", "biogrupo", ., fixed = TRUE) %>%
|
||||
gsub("biotype", "biotipo", ., fixed = TRUE) %>%
|
||||
gsub("vegetative", "vegetativo", ., fixed = TRUE) %>%
|
||||
gsub("([([ ]*?)group", "\\1grupo", .) %>%
|
||||
gsub("([([ ]*?)Group", "\\1Grupo", .),
|
||||
|
||||
# Portuguese
|
||||
language == "pt" ~ x %>%
|
||||
gsub("(no MO)", "(sem MO)", ., fixed = TRUE) %>%
|
||||
gsub("Negative rods", "Bacilos negativos", ., fixed = TRUE) %>%
|
||||
gsub("Negative cocci", "Cocos negativos", ., fixed = TRUE) %>%
|
||||
gsub("Positive rods", "Bacilos positivos", ., fixed = TRUE) %>%
|
||||
gsub("Positive cocci", "Cocos positivos", ., fixed = TRUE) %>%
|
||||
gsub("Parasites", "Parasitas", ., fixed = TRUE) %>%
|
||||
gsub("Fungi and yeasts", "Cogumelos e leveduras", ., fixed = TRUE) %>%
|
||||
gsub("Bacteria", "Bact\u00e9ria", ., fixed = TRUE) %>%
|
||||
gsub("Fungus/yeast", "Cogumelo/levedura", ., fixed = TRUE) %>%
|
||||
gsub("Parasite", "Parasita", ., fixed = TRUE) %>%
|
||||
gsub("biogroup", "biogrupo", ., fixed = TRUE) %>%
|
||||
gsub("biotype", "bi\u00f3tipo", ., fixed = TRUE) %>%
|
||||
gsub("vegetative", "vegetativo", ., fixed = TRUE) %>%
|
||||
gsub("([([ ]*?)group", "\\1grupo", .) %>%
|
||||
gsub("([([ ]*?)Group", "\\1Grupo", .)
|
||||
)
|
||||
|
||||
}
|
||||
|
||||
#' @importFrom dplyr case_when
|
||||
mo_getlangcode <- function() {
|
||||
sys <- base::Sys.getlocale()
|
||||
case_when(
|
||||
sys %like% '(Deutsch|German|de_)' ~ "de",
|
||||
sys %like% '(Nederlands|Dutch|nl_)' ~ "nl",
|
||||
sys %like% '(Espa.ol|Spanish|es_)' ~ "es",
|
||||
sys %like% '(Portugu.s|Portuguese|pt_)' ~ "pt",
|
||||
TRUE ~ "en"
|
||||
)
|
||||
}
|
||||
|
||||
46
R/zzz.R
46
R/zzz.R
@ -1,3 +1,49 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# AUTHORS #
|
||||
# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# LICENCE #
|
||||
# This program is free software; you can redistribute it and/or modify #
|
||||
# it under the terms of the GNU General Public License version 2.0, #
|
||||
# as published by the Free Software Foundation. #
|
||||
# #
|
||||
# This program is distributed in the hope that it will be useful, #
|
||||
# but WITHOUT ANY WARRANTY; without even the implied warranty of #
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
|
||||
# GNU General Public License for more details. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' The \code{AMR} Package
|
||||
#'
|
||||
#' Welcome to the \code{AMR} package. This page gives some additional contact information abount the authors.
|
||||
#' @details
|
||||
#' This package was intended to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and work with antibiotic properties by using evidence-based methods.
|
||||
#'
|
||||
#' This package was created for academic research by PhD students of the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG).
|
||||
#' @section Authors:
|
||||
#' Matthijs S. Berends[1,2] Christian F. Luz[1], Erwin E.A. Hassing[2], Corinna Glasner[1], Alex W. Friedrich[1], Bhanu Sinha[1] \cr
|
||||
#'
|
||||
#' [1] Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands - \url{rug.nl} \url{umcg.nl} \cr
|
||||
#' [2] Certe Medical Diagnostics & Advice, Groningen, the Netherlands - \url{certe.nl}
|
||||
#' @section Contact us:
|
||||
#' For suggestions, comments or questions, please contact us at:
|
||||
#'
|
||||
#' Matthijs S. Berends \cr
|
||||
#' m.s.berends [at] umcg [dot] nl \cr
|
||||
#' Department of Medical Microbiology, University of Groningen \cr
|
||||
#' University Medical Center Groningen \cr
|
||||
#' Post Office Box 30001 \cr
|
||||
#' 9700 RB Groningen
|
||||
#'
|
||||
#' If you have found a bug, please file a new issue at: \cr
|
||||
#' \url{https://github.com/msberends/AMR/issues}
|
||||
#' @name AMR
|
||||
#' @rdname AMR
|
||||
NULL
|
||||
|
||||
.onLoad <- function(libname, pkgname) {
|
||||
backports::import(pkgname)
|
||||
}
|
||||
|
||||
@ -55,7 +55,7 @@ This `AMR` package basically does four important things:
|
||||
* Use `first_isolate` to identify the first isolates of every patient [using guidelines from the CLSI](https://clsi.org/standards/products/microbiology/documents/m39/) (Clinical and Laboratory Standards Institute).
|
||||
* You can also identify first *weighted* isolates of every patient, an adjusted version of the CLSI guideline. This takes into account key antibiotics of every strain and compares them.
|
||||
* Use `MDRO` (abbreviation of Multi Drug Resistant Organisms) to check your isolates for exceptional resistance with country-specific guidelines or EUCAST rules. Currently, national guidelines for Germany and the Netherlands are supported.
|
||||
* The data set `microorganisms` contains the family, genus, species, subspecies, colloquial name and Gram stain of almost 3,000 potential human pathogenic microorganisms (bacteria, fungi/yeasts and parasites). This enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like `mo_genus`, `mo_family` or `mo_gramstain`. As they use `as.mo` internally, they also use artificial intelligence. For example, `mo_genus("MRSA")` and `mo_genus("S. aureus")` will both return `"Staphylococcus"`. Some functions can return results in Spanish, German and Dutch. These functions can be used to add new variables to your data.
|
||||
* The data set `microorganisms` contains the family, genus, species, subspecies, colloquial name and Gram stain of almost 3,000 potential human pathogenic microorganisms (bacteria, fungi/yeasts and parasites). This enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like `mo_genus`, `mo_family` or `mo_gramstain`. As they use `as.mo` internally, they also use artificial intelligence. For example, `mo_genus("MRSA")` and `mo_genus("S. aureus")` will both return `"Staphylococcus"`. They also come with support for German, Dutch, Spanish and Portuguese. These functions can be used to add new variables to your data.
|
||||
* The data set `antibiotics` contains the ATC code, LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains a total of 298 trade names. Use functions like `ab_official` and `ab_tradenames` to look up values. As the `mo_*` functions use `as.mo` internally, the `ab_*` functions use `as.atc` internally so it uses AI to guess your expected result. For example, `ab_official("Fluclox")`, `ab_official("Floxapen")` and `ab_official("J01CF05")` will all return `"Flucloxacillin"`. These functions can again be used to add new variables to your data.
|
||||
|
||||
3. It **analyses the data** with convenient functions that use well-known methods.
|
||||
@ -384,11 +384,11 @@ septic_patients # A tibble: 2,000 x 49
|
||||
|
||||
# Dataset with ATC antibiotics codes, official names, trade names
|
||||
# and DDDs (oral and parenteral)
|
||||
antibiotics # A tibble: 420 x 18
|
||||
antibiotics # A tibble: 423 x 18
|
||||
|
||||
# Dataset with bacteria codes and properties like gram stain and
|
||||
# aerobic/anaerobic
|
||||
microorganisms # A tibble: 2,453 x 12
|
||||
microorganisms # A tibble: 2,669 x 10
|
||||
```
|
||||
|
||||
## Copyright
|
||||
|
||||
Binary file not shown.
Binary file not shown.
36
man/AMR.Rd
Normal file
36
man/AMR.Rd
Normal file
@ -0,0 +1,36 @@
|
||||
% Generated by roxygen2: do not edit by hand
|
||||
% Please edit documentation in R/zzz.R
|
||||
\name{AMR}
|
||||
\alias{AMR}
|
||||
\title{The \code{AMR} Package}
|
||||
\description{
|
||||
Welcome to the \code{AMR} package. This page gives some additional contact information abount the authors.
|
||||
}
|
||||
\details{
|
||||
This package was intended to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and work with antibiotic properties by using evidence-based methods.
|
||||
|
||||
This package was created for academic research by PhD students of the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG).
|
||||
}
|
||||
\section{Authors}{
|
||||
|
||||
Matthijs S. Berends[1,2] Christian F. Luz[1], Erwin E.A. Hassing[2], Corinna Glasner[1], Alex W. Friedrich[1], Bhanu Sinha[1] \cr
|
||||
|
||||
[1] Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands - \url{rug.nl} \url{umcg.nl} \cr
|
||||
[2] Certe Medical Diagnostics & Advice, Groningen, the Netherlands - \url{certe.nl}
|
||||
}
|
||||
|
||||
\section{Contact us}{
|
||||
|
||||
For suggestions, comments or questions, please contact us at:
|
||||
|
||||
Matthijs S. Berends \cr
|
||||
m.s.berends [at] umcg [dot] nl \cr
|
||||
Department of Medical Microbiology, University of Groningen \cr
|
||||
University Medical Center Groningen \cr
|
||||
Post Office Box 30001 \cr
|
||||
9700 RB Groningen
|
||||
|
||||
If you have found a bug, please file a new issue at: \cr
|
||||
\url{https://github.com/msberends/AMR/issues}
|
||||
}
|
||||
|
||||
@ -44,7 +44,6 @@ Some exceptions have been built in to get more logical results, based on prevale
|
||||
\itemize{
|
||||
\item{\code{"E. coli"} will return the ID of \emph{Escherichia coli} and not \emph{Entamoeba coli}, although the latter would alphabetically come first}
|
||||
\item{\code{"H. influenzae"} will return the ID of \emph{Haemophilus influenzae} and not \emph{Haematobacter influenzae}}
|
||||
\item{Something like \code{"s pyo"} will return the ID of \emph{Streptococcus pyogenes} and not \emph{Actinomyes pyogenes}}
|
||||
\item{Something like \code{"p aer"} will return the ID of \emph{Pseudomonas aeruginosa} and not \emph{Pasteurella aerogenes}}
|
||||
\item{Something like \code{"stau"} or \code{"staaur"} will return the ID of \emph{Staphylococcus aureus} and not \emph{Staphylococcus auricularis}}
|
||||
}
|
||||
|
||||
@ -4,7 +4,7 @@
|
||||
\name{microorganisms}
|
||||
\alias{microorganisms}
|
||||
\title{Data set with human pathogenic microorganisms}
|
||||
\format{A \code{\link{tibble}} with 2,669 observations and 16 variables:
|
||||
\format{A \code{\link{tibble}} with 2,669 observations and 10 variables:
|
||||
\describe{
|
||||
\item{\code{mo}}{ID of microorganism}
|
||||
\item{\code{bactsys}}{Bactsyscode of microorganism}
|
||||
@ -16,12 +16,6 @@
|
||||
\item{\code{aerobic}}{Logical whether bacteria is aerobic}
|
||||
\item{\code{type}}{Type of microorganism, like \code{"Bacteria"} and \code{"Fungus/yeast"}}
|
||||
\item{\code{gramstain}}{Gram of microorganism, like \code{"Negative rods"}}
|
||||
\item{\code{type_de}}{Type of microorganism in German, like \code{"Bakterien"} and \code{"Pilz/Hefe"}}
|
||||
\item{\code{gramstain_de}}{Gram of microorganism in German, like \code{"Negative Staebchen"}}
|
||||
\item{\code{type_nl}}{Type of microorganism in Dutch, like \code{"Bacterie"} and \code{"Schimmel/gist"}}
|
||||
\item{\code{gramstain_nl}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
|
||||
\item{\code{type_es}}{Type of microorganism in Spanish, like \code{"Bacteria"} and \code{"Hongo/levadura"}}
|
||||
\item{\code{gramstain_es}}{Gram of microorganism in Spanish, like \code{"Bacilos negativos"}}
|
||||
}}
|
||||
\usage{
|
||||
microorganisms
|
||||
|
||||
@ -18,32 +18,30 @@
|
||||
[2] Lancefield RC \strong{A serological differentiation of human and other groups of hemolytic streptococci}. 1933. J Exp Med. 57(4): 571–95. \url{https://dx.doi.org/10.1084/jem.57.4.571}
|
||||
}
|
||||
\usage{
|
||||
mo_property(x, property = "fullname", Becker = FALSE,
|
||||
Lancefield = FALSE)
|
||||
|
||||
mo_family(x)
|
||||
|
||||
mo_genus(x)
|
||||
|
||||
mo_species(x, Becker = FALSE, Lancefield = FALSE)
|
||||
mo_species(x, Becker = FALSE, Lancefield = FALSE, language = NULL)
|
||||
|
||||
mo_subspecies(x, Becker = FALSE, Lancefield = FALSE)
|
||||
mo_subspecies(x, Becker = FALSE, Lancefield = FALSE, language = NULL)
|
||||
|
||||
mo_fullname(x, Becker = FALSE, Lancefield = FALSE)
|
||||
mo_fullname(x, Becker = FALSE, Lancefield = FALSE, language = NULL)
|
||||
|
||||
mo_shortname(x, Becker = FALSE, Lancefield = FALSE)
|
||||
mo_shortname(x, Becker = FALSE, Lancefield = FALSE, language = NULL)
|
||||
|
||||
mo_type(x, language = "en")
|
||||
mo_type(x, language = NULL)
|
||||
|
||||
mo_gramstain(x, language = "en")
|
||||
mo_gramstain(x, language = NULL)
|
||||
|
||||
mo_aerobic(x)
|
||||
|
||||
mo_property(x, property = "fullname", Becker = FALSE,
|
||||
Lancefield = FALSE, language = NULL)
|
||||
}
|
||||
\arguments{
|
||||
\item{x}{any (vector of) text that can be coerced to a valid microorganism code with \code{\link{as.mo}}}
|
||||
|
||||
\item{property}{one of the column names of one of the \code{\link{microorganisms}} data set, like \code{"mo"}, \code{"bactsys"}, \code{"family"}, \code{"genus"}, \code{"species"}, \code{"fullname"}, \code{"gramstain"} and \code{"aerobic"}}
|
||||
|
||||
\item{Becker}{a logical to indicate whether \emph{Staphylococci} should be categorised into Coagulase Negative \emph{Staphylococci} ("CoNS") and Coagulase Positive \emph{Staphylococci} ("CoPS") instead of their own species, according to Karsten Becker \emph{et al.} [1].
|
||||
|
||||
This excludes \emph{Staphylococcus aureus} at default, use \code{Becker = "all"} to also categorise \emph{S. aureus} as "CoPS".}
|
||||
@ -52,7 +50,9 @@ mo_aerobic(x)
|
||||
|
||||
This excludes \emph{Enterococci} at default (who are in group D), use \code{Lancefield = "all"} to also categorise all \emph{Enterococci} as group D.}
|
||||
|
||||
\item{language}{language of the returned text, either one of \code{"en"} (English), \code{"de"} (German) or \code{"nl"} (Dutch)}
|
||||
\item{language}{language of the returned text, defaults to the systems language. Either one of \code{"en"} (English), \code{"de"} (German), \code{"nl"} (Dutch), \code{"es"} (Spanish) or \code{"pt"} (Portuguese).}
|
||||
|
||||
\item{property}{one of the column names of one of the \code{\link{microorganisms}} data set, like \code{"mo"}, \code{"bactsys"}, \code{"family"}, \code{"genus"}, \code{"species"}, \code{"fullname"}, \code{"gramstain"} and \code{"aerobic"}}
|
||||
}
|
||||
\value{
|
||||
Character or logical (only \code{mo_aerobic})
|
||||
@ -72,14 +72,6 @@ mo_type("E. coli") # "Bacteria"
|
||||
mo_gramstain("E. coli") # "Negative rods"
|
||||
mo_aerobic("E. coli") # TRUE
|
||||
|
||||
# language support for Spanish, German and Dutch
|
||||
mo_type("E. coli", "es") # "Bakteria"
|
||||
mo_type("E. coli", "de") # "Bakterien"
|
||||
mo_type("E. coli", "nl") # "Bacterie"
|
||||
mo_gramstain("E. coli", "es") # "Bacilos negativos"
|
||||
mo_gramstain("E. coli", "de") # "Negative Staebchen"
|
||||
mo_gramstain("E. coli", "nl") # "Negatieve staven"
|
||||
|
||||
|
||||
# Abbreviations known in the field
|
||||
mo_genus("MRSA") # "Staphylococcus"
|
||||
@ -123,6 +115,23 @@ mo_fullname("S. pyo") # "Streptococcus pyogenes"
|
||||
mo_fullname("S. pyo", Lancefield = TRUE) # "Streptococcus group A"
|
||||
mo_shortname("S. pyo") # "S. pyogenes"
|
||||
mo_shortname("S. pyo", Lancefield = TRUE) # "GAS"
|
||||
|
||||
|
||||
# Language support for German, Dutch, Spanish and Portuguese
|
||||
mo_type("E. coli", language = "de") # "Bakterium"
|
||||
mo_type("E. coli", language = "nl") # "Bacterie"
|
||||
mo_type("E. coli", language = "es") # "Bakteria"
|
||||
mo_gramstain("E. coli", language = "de") # "Negative Staebchen"
|
||||
mo_gramstain("E. coli", language = "nl") # "Negatieve staven"
|
||||
mo_gramstain("E. coli", language = "es") # "Bacilos negativos"
|
||||
mo_gramstain("Giardia", language = "pt") # "Parasitas"
|
||||
|
||||
mo_fullname("S. pyo",
|
||||
Lancefield = TRUE,
|
||||
language = "de") # "Streptococcus Gruppe A"
|
||||
mo_fullname("S. pyo",
|
||||
Lancefield = TRUE,
|
||||
language = "nl") # "Streptococcus groep A"
|
||||
}
|
||||
\seealso{
|
||||
\code{\link{microorganisms}}
|
||||
|
||||
7
tests/testthat/test-data.R
Normal file
7
tests/testthat/test-data.R
Normal file
@ -0,0 +1,7 @@
|
||||
context("data.R")
|
||||
|
||||
test_that("data sets are valid", {
|
||||
# IDs should always be unique
|
||||
expect_identical(nrow(antibiotics), length(unique(antibiotics$atc)))
|
||||
expect_identical(nrow(microorganisms), length(unique(microorganisms$mo)))
|
||||
})
|
||||
@ -10,7 +10,7 @@ test_that("first isolates work", {
|
||||
col_mo = "mo",
|
||||
info = TRUE),
|
||||
na.rm = TRUE),
|
||||
1331)
|
||||
1330)
|
||||
|
||||
# septic_patients contains 1426 out of 2000 first *weighted* isolates
|
||||
expect_equal(
|
||||
@ -24,7 +24,7 @@ test_that("first isolates work", {
|
||||
type = "keyantibiotics",
|
||||
info = TRUE),
|
||||
na.rm = TRUE)),
|
||||
1426)
|
||||
1425)
|
||||
# and 1449 when not ignoring I
|
||||
expect_equal(
|
||||
suppressWarnings(
|
||||
@ -38,7 +38,7 @@ test_that("first isolates work", {
|
||||
type = "keyantibiotics",
|
||||
info = TRUE),
|
||||
na.rm = TRUE)),
|
||||
1449)
|
||||
1448)
|
||||
# and 1430 when using points
|
||||
expect_equal(
|
||||
suppressWarnings(
|
||||
@ -64,7 +64,7 @@ test_that("first isolates work", {
|
||||
info = TRUE,
|
||||
icu_exclude = TRUE),
|
||||
na.rm = TRUE),
|
||||
1176)
|
||||
1175)
|
||||
|
||||
# set 1500 random observations to be of specimen type 'Urine'
|
||||
random_rows <- sample(x = 1:2000, size = 1500, replace = FALSE)
|
||||
|
||||
@ -13,6 +13,7 @@ test_that("as.mo works", {
|
||||
expect_equal(as.character(as.mo("Klebsiella")), "KLE")
|
||||
expect_equal(as.character(as.mo("K. pneu rhino")), "KLEPNERH") # K. pneumoniae subspp. rhinoscleromatis
|
||||
expect_equal(as.character(as.mo("Bartonella")), "BAR")
|
||||
expect_equal(as.character(as.mo("C. difficile")), "CLODIF")
|
||||
|
||||
expect_equal(as.character(as.mo("S. pyo")), "STCPYO") # not Actinomyces pyogenes
|
||||
|
||||
|
||||
@ -6,8 +6,8 @@ test_that("mo_property works", {
|
||||
expect_equal(mo_species("E. coli"), "coli")
|
||||
expect_equal(mo_subspecies("E. coli"), "")
|
||||
expect_equal(mo_fullname("E. coli"), "Escherichia coli")
|
||||
expect_equal(mo_type("E. coli"), "Bacteria")
|
||||
expect_equal(mo_gramstain("E. coli"), "Negative rods")
|
||||
expect_equal(mo_type("E. coli", language = "en"), "Bacteria")
|
||||
expect_equal(mo_gramstain("E. coli", language = "en"), "Negative rods")
|
||||
expect_equal(mo_aerobic("E. coli"), TRUE)
|
||||
|
||||
expect_equal(mo_shortname("MRSA"), "S. aureus")
|
||||
@ -16,8 +16,8 @@ test_that("mo_property works", {
|
||||
expect_equal(mo_shortname("S. aga"), "S. agalactiae")
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expect_equal(mo_shortname("S. aga", Lancefield = TRUE), "GBS")
|
||||
|
||||
expect_equal(mo_type("E. coli", language = "de"), "Bakterien")
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expect_equal(mo_gramstain("E. coli", language = "de"), "Negative Staebchen")
|
||||
expect_equal(mo_type("E. coli", language = "de"), "Bakterium")
|
||||
expect_equal(mo_gramstain("E. coli", language = "de"), "Negative St\u00e4bchen")
|
||||
|
||||
expect_equal(mo_type("E. coli", language = "nl"), "Bacterie")
|
||||
expect_equal(mo_gramstain("E. coli", language = "nl"), "Negatieve staven")
|
||||
|
||||
@ -34,7 +34,7 @@ This `AMR` package basically does four important things:
|
||||
* Use `first_isolate` to identify the first isolates of every patient [using guidelines from the CLSI](https://clsi.org/standards/products/microbiology/documents/m39/) (Clinical and Laboratory Standards Institute).
|
||||
* You can also identify first *weighted* isolates of every patient, an adjusted version of the CLSI guideline. This takes into account key antibiotics of every strain and compares them.
|
||||
* Use `MDRO` (abbreviation of Multi Drug Resistant Organisms) to check your isolates for exceptional resistance with country-specific guidelines or EUCAST rules. Currently, national guidelines for Germany and the Netherlands are supported.
|
||||
* The data set `microorganisms` contains the family, genus, species, subspecies, colloquial name and Gram stain of almost 3,000 potential human pathogenic microorganisms (bacteria, fungi/yeasts and parasites). This enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like `mo_genus`, `mo_family` or `mo_gramstain`. As they use `as.mo` internally, they also use artificial intelligence. For example, `mo_genus("MRSA")` and `mo_genus("S. aureus")` will both return `"Staphylococcus"`. Some functions can return results in Spanish, German and Dutch. These functions can be used to add new variables to your data.
|
||||
* The data set `microorganisms` contains the family, genus, species, subspecies, colloquial name and Gram stain of almost 3,000 potential human pathogenic microorganisms (bacteria, fungi/yeasts and parasites). This enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like `mo_genus`, `mo_family` or `mo_gramstain`. As they use `as.mo` internally, they also use artificial intelligence. For example, `mo_genus("MRSA")` and `mo_genus("S. aureus")` will both return `"Staphylococcus"`. They also come with support for German, Dutch, Spanish and Portuguese. These functions can be used to add new variables to your data.
|
||||
* The data set `antibiotics` contains the ATC code, LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains a total of 298 trade names. Use functions like `ab_official` and `ab_tradenames` to look up values. As the `mo_*` functions use `as.mo` internally, the `ab_*` functions use `as.atc` internally so it uses AI to guess your expected result. For example, `ab_official("Fluclox")`, `ab_official("Floxapen")` and `ab_official("J01CF05")` will all return `"Flucloxacillin"`. These functions can again be used to add new variables to your data.
|
||||
|
||||
3. It **analyses the data** with convenient functions that use well-known methods.
|
||||
|
||||
Loading…
Reference in New Issue
Block a user