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mirror of https://github.com/msberends/AMR.git synced 2024-12-25 07:26:12 +01:00

- Added new function guess_bactid to determine the ID of a microorganism based on genus/species

- Renamed `ablist` to `antibiotics`
- Added support for character vector in join functions
- Altered `%like%` to make it case insensitive
This commit is contained in:
dr. M.S. (Matthijs) Berends 2018-03-19 12:43:22 +01:00
parent 0fec64a240
commit 502a44eb25
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23 changed files with 312 additions and 103 deletions

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@ -1,2 +1,21 @@
# R for travis: see documentation at https://docs.travis-ci.com/user/languages/r
language: r
cache: packages
r:
- 3.0
r_packages:
- covr
after_success:
- Rscript -e 'covr::codecov()'
notifications:
email:
recipients:
- m.s.berends@umcg.nl
- c.f.luz@umcg.nl
on_success: change
on_failure: always

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@ -1,13 +1,14 @@
Package: AMR
Version: 0.1.1
Date: 2018-03-13
Version: 0.1.2
Date: 2018-03-19
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(
given = c("Matthijs", "S."),
family = "Berends",
email = "m.s.berends@umcg.nl",
role = c("aut", "cre")),
role = c("aut", "cre"),
comment = c(ORCID = "0000-0001-7620-1800")),
person(
given = c("Christian", "F."),
family = "Luz",

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@ -19,6 +19,7 @@ export(as.rsi)
export(atc_property)
export(first_isolate)
export(full_join_bactlist)
export(guess_bactid)
export(inner_join_bactlist)
export(interpretive_reading)
export(is.mic)

6
NEWS
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@ -1,3 +1,9 @@
## 0.1.2
- Added new function `guess_bactid` to determine the ID of a microorganism based on genus/species
- Renamed `ablist` to `antibiotics`
- Added support for character vector in join functions
- Altered `%like%` to make it case insensitive
## 0.1.1
- `EUCAST_rules` applies for amoxicillin even if ampicillin is missing
- Edited column names to comply with GLIMS, the laboratory information system

22
R/atc.R
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@ -127,13 +127,13 @@ atc_property <- function(atc_code,
#' Name of an antibiotic
#'
#' Convert antibiotic codes (from a laboratory information system like MOLIS or GLIMS) to a (trivial) antibiotic name or ATC code, or vice versa. This uses the data from \code{\link{ablist}}.
#' Convert antibiotic codes (from a laboratory information system like MOLIS or GLIMS) to a (trivial) antibiotic name or ATC code, or vice versa. This uses the data from \code{\link{antibiotics}}.
#' @param abcode a code or name, like \code{"AMOX"}, \code{"AMCL"} or \code{"J01CA04"}
#' @param from,to type to transform from and to. See \code{\link{ablist}} for its column names.
#' @param from,to type to transform from and to. See \code{\link{antibiotics}} for its column names.
#' @param textbetween text to put between multiple returned texts
#' @param tolower return output as lower case with function \code{\link{tolower}}.
#' @keywords ab antibiotics
#' @source \code{\link{ablist}}
#' @source \code{\link{antibiotics}}
#' @export
#' @importFrom dplyr %>% filter select slice
#' @examples
@ -156,15 +156,15 @@ atc_property <- function(atc_code,
#' # "AMCL"
abname <- function(abcode, from = 'umcg', to = 'official', textbetween = ' + ', tolower = FALSE) {
ablist <- AMR::ablist
colnames(ablist) <- colnames(ablist) %>% tolower()
antibiotics <- AMR::antibiotics
colnames(antibiotics) <- colnames(antibiotics) %>% tolower()
from <- from %>% tolower()
to <- to %>% tolower()
if (!from %in% colnames(ablist) |
!to %in% colnames(ablist)) {
if (!from %in% colnames(antibiotics) |
!to %in% colnames(antibiotics)) {
stop(paste0('Invalid `from` or `to`. Choose one of ',
colnames(ablist) %>% paste(collapse = ","), '.'), call. = FALSE)
colnames(antibiotics) %>% paste(collapse = ","), '.'), call. = FALSE)
}
abcode <- as.character(abcode)
@ -173,9 +173,9 @@ abname <- function(abcode, from = 'umcg', to = 'official', textbetween = ' + ',
drug <- abcode[i]
if (!grepl('+', drug, fixed = TRUE) & !grepl(' en ', drug, fixed = TRUE)) {
# bestaat maar uit 1 middel
if (any(ablist[, from] == drug)) {
if (any(antibiotics[, from] == drug)) {
abcode[i] <-
ablist %>%
antibiotics %>%
filter(.[, from] == drug) %>%
select(to) %>%
slice(1) %>%
@ -205,7 +205,7 @@ abname <- function(abcode, from = 'umcg', to = 'official', textbetween = ' + ',
for (j in 1:length(drug.group)) {
drug.group[j] <-
ablist %>%
antibiotics %>%
filter(.[, from] == drug.group[j]) %>%
select(to) %>%
slice(1) %>%

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@ -18,36 +18,53 @@
#' Dataset with 420 antibiotics
#'
#' A dataset containing all antibiotics with a J0 code, with their DDD's.
#' @format A data.frame with 420 observations and 12 variables:
#' A dataset containing all antibiotics with a J0 code, with their DDD's. Properties were downloaded from the WHO, see Source.
#' @format A data.frame with 420 observations and 16 variables:
#' \describe{
#' \item{\code{atc}}{ATC code, like \code{J01CR02}}
#' \item{\code{molis}}{MOLIS code, like \code{amcl}}
#' \item{\code{umcg}}{UMCG code, like \code{AMCL}}
#' \item{\code{official}}{Official name by the WHO, like \code{"amoxicillin and enzyme inhibitor"}}
#' \item{\code{official}}{Official name by the WHO, like \code{"Amoxicillin and enzyme inhibitor"}}
#' \item{\code{official_nl}}{Official name in the Netherlands, like \code{"Amoxicilline met enzymremmer"}}
#' \item{\code{trivial_nl}}{Trivial name in Dutch, like \code{"Amoxicilline/clavulaanzuur"}}
#' \item{\code{oral_ddd}}{Defined Daily Dose (DDD) according to the WHO, oral treatment}
#' \item{\code{oral_ddd}}{Defined Daily Dose (DDD), oral treatment}
#' \item{\code{oral_units}}{Units of \code{ddd_units}}
#' \item{\code{iv_ddd}}{Defined Daily Dose (DDD) according to the WHO, parenteral treatment}
#' \item{\code{iv_ddd}}{Defined Daily Dose (DDD), parenteral treatment}
#' \item{\code{iv_units}}{Units of \code{iv_ddd}}
#' \item{\code{atc_group1}}{ATC group in Dutch, like \code{"Macroliden, lincosamiden en streptograminen"}}
#' \item{\code{atc_group2}}{Subgroup of \code{atc_group1} in Dutch, like \code{"Macroliden"}}
#' \item{\code{atc_group1}}{ATC group, like \code{"Macrolides, lincosamides and streptogramins"}}
#' \item{\code{atc_group2}}{Subgroup of \code{atc_group1}, like \code{"Macrolides"}}
#' \item{\code{atc_group1_nl}}{ATC group in Dutch, like \code{"Macroliden, lincosamiden en streptograminen"}}
#' \item{\code{atc_group2_nl}}{Subgroup of \code{atc_group1} in Dutch, like \code{"Macroliden"}}
#' \item{\code{useful_gramnegative}}{\code{FALSE} if not useful according to EUCAST, \code{NA} otherwise (see Source)}
#' \item{\code{useful_grampositive}}{\code{FALSE} if not useful according to EUCAST, \code{NA} otherwise (see Source)}
#' }
#' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl} \cr \cr GLIMS (LIS of UMCG) - \url{https://www.umcg.nl} \cr \cr World Health Organization - \url{https://www.whocc.no/atc_ddd_index/}
#' @source - World Health Organization: \url{https://www.whocc.no/atc_ddd_index/} \cr - EUCAST - Expert rules intrinsic exceptional V3.1 \cr - MOLIS (LIS of Certe): \url{https://www.certe.nl} \cr - GLIMS (LIS of UMCG): \url{https://www.umcg.nl}
#' @seealso \code{\link{bactlist}}
# todo:
# ablist <- ablist %>% mutate(useful_gramnegative = if_else(atc_group2 == 'Tetracyclines', FALSE, TRUE))
# ablist <- ablist %>% mutate(useful_gramnegative = if_else(atc_group2 %like% 'Glycopept', FALSE, useful_gramnegative))
# Tbl1 Enterobacteriaceae are also intrinsically resistant to benzylpenicillin, glycopeptides, fusidic acid, macrolides (with some exceptions1), lincosamides, streptogramins, rifampicin, daptomycin and linezolid.
# Tbl2 Non-fermentative Gram-negative bacteria are also generally intrinsically resistant to benzylpenicillin, first and second generation cephalosporins, glycopeptides, fusidic acid, macrolides, lincosamides, streptogramins, rifampicin, daptomycin and linezolid
# Tbl3 Gram-negative bacteria other than Enterobacteriaceae and non-fermentative Gram-negative bacteria listed are also intrinsically resistant to glycopeptides, lincosamides, daptomycin and linezolid.
"ablist"
# last two columns created with:
# antibiotics %>%
# mutate(useful_gramnegative =
# if_else(
# atc_group1 %like% '(fusidic|glycopeptide|macrolide|lincosamide|daptomycin|linezolid)' |
# atc_group2 %like% '(fusidic|glycopeptide|macrolide|lincosamide|daptomycin|linezolid)' |
# official %like% '(fusidic|glycopeptide|macrolide|lincosamide|daptomycin|linezolid)',
# FALSE,
# NA
# ),
# useful_grampositive =
# if_else(
# atc_group1 %like% '(aztreonam|temocillin|polymyxin|colistin|nalidixic)' |
# atc_group2 %like% '(aztreonam|temocillin|polymyxin|colistin|nalidixic)' |
# official %like% '(aztreonam|temocillin|polymyxin|colistin|nalidixic)',
# FALSE,
# NA
# )
# )
"antibiotics"
#' Dataset with ~2500 microorganisms
#'
#' A dataset containing all microorganisms of MOLIS. MO codes of the UMCG can be looked up using \code{\link{bactlist.umcg}}.
#' @format A data.frame with 2507 observations and 10 variables:
#' @format A data.frame with 2507 observations and 12 variables:
#' \describe{
#' \item{\code{bactid}}{ID of microorganism}
#' \item{\code{bactsys}}{Bactsyscode of microorganism}
@ -56,12 +73,14 @@
#' \item{\code{species}}{Species name of microorganism, like \code{"coli"}}
#' \item{\code{subspecies}}{Subspecies name of bio-/serovar of microorganism, like \code{"EHEC"}}
#' \item{\code{fullname}}{Full name, like \code{"Echerichia coli (EHEC)"}}
#' \item{\code{type}}{Type of microorganism in Dutch, like \code{"Bacterie"} and \code{"Schimmel/gist"}}
#' \item{\code{gramstain}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
#' \item{\code{aerobic}}{Type aerobe/anaerobe of bacteria}
#' \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{aerobic}}{Logical whether bacteria is aerobic}
#' \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"}}
#' }
#' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
#' @seealso \code{\link{ablist}} \code{\link{bactlist.umcg}}
#' @seealso \code{\link{guess_bactid}} \code{\link{antibiotics}} \code{\link{bactlist.umcg}}
"bactlist"
#' Translation table for UMCG with ~1100 microorganisms
@ -90,7 +109,7 @@
#' \item{\code{sex}}{sex of the patient}
#' \item{\code{patient_id}}{ID of the patient, first 10 characters of an SHA hash containing irretrievable information}
#' \item{\code{bactid}}{ID of microorganism, see \code{\link{bactlist}}}
#' \item{\code{peni:mupi}}{38 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}), these column names occur in \code{\link{ablist}} and can be translated with \code{\link{abname}}}
#' \item{\code{peni:mupi}}{38 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}), these column names occur in \code{\link{antibiotics}} and can be translated with \code{\link{abname}}}
#' }
#' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
"septic_patients"
"septic_patients"

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@ -357,7 +357,7 @@ first_isolate <- function(tbl,
#' @export
#' @importFrom dplyr %>% mutate if_else
#' @return Character of length 1.
#' @seealso \code{\link{mo_property}} \code{\link{ablist}}
#' @seealso \code{\link{mo_property}} \code{\link{antibiotics}}
#' @examples
#' \donttest{
#' #' # set key antibiotics to a new variable
@ -403,7 +403,7 @@ key_antibiotics <- function(tbl,
}
}
# bactlist aan vastknopen
# join bactlist
tbl <- tbl %>% left_join_bactlist(col_bactcode)
tbl$key_ab <- NA_character_
@ -422,7 +422,7 @@ key_antibiotics <- function(tbl,
list_ab <- c(peni, amox, teic, vanc, clin, line, clar, trsu)
list_ab <- list_ab[list_ab %in% colnames(tbl)]
tbl <- tbl %>% mutate(key_ab =
if_else(gramstain %like% '^Positi[e]?ve',
if_else(gramstain %like% '^Positive ',
apply(X = tbl[, list_ab],
MARGIN = 1,
FUN = function(x) paste(x, collapse = "")),
@ -432,7 +432,7 @@ key_antibiotics <- function(tbl,
list_ab <- c(amox, amcl, pita, cfur, cfot, cfta, cftr, mero, cipr, trsu, gent)
list_ab <- list_ab[list_ab %in% colnames(tbl)]
tbl <- tbl %>% mutate(key_ab =
if_else(gramstain %like% '^Negati[e]?ve',
if_else(gramstain %like% '^Negative ',
apply(X = tbl[, list_ab],
MARGIN = 1,
FUN = function(x) paste(x, collapse = "")),
@ -502,3 +502,95 @@ key_antibiotics_equal <- function(x, y, points_threshold = 2, info = FALSE) {
}
result
}
#' Find bacteria ID based on genus/species
#'
#' Use this function to determine a valid ID based on a genus (and species). This input could be a full name (like \code{"Staphylococcus aureus"}), an abbreviated name (like \code{"S. aureus"}), or just a genus. You could also use a \code{\link{paste}} of a genus and species column to use the full name as input: \code{x = paste(df$genus, df$species)}, where \code{df} is your dataframe.
#' @param x character vector to determine \code{bactid}
#' @export
#' @importFrom dplyr %>% filter slice pull
#' @return Character (vector).
#' @seealso \code{\link{bactlist}} for the dataframe that is being used to determine ID's.
#' @examples
#' # These examples all return "STAAUR", the ID of S. aureus:
#' guess_bactid("stau")
#' guess_bactid("STAU")
#' guess_bactid("staaur")
#' guess_bactid("S. aureus")
#' guess_bactid("S aureus")
#' guess_bactid("Staphylococcus aureus")
#' guess_bactid("MRSA") # Methicillin-resistant S. aureus
#' guess_bactid("VISA") # Vancomycin Intermediate S. aureus
guess_bactid <- function(x) {
# remove dots and other non-text in case of "E. coli" except spaces
x <- gsub("[^a-zA-Z ]+", "", x)
x.bak <- x
# replace space by regex sign
x <- gsub(" ", ".*", x, fixed = TRUE)
# add start and stop
x_species <- paste(x, 'species')
x <- paste0('^', x, '$')
for (i in 1:length(x)) {
if (tolower(x[i]) == '^e.*coli$') {
# avoid detection of Entamoeba coli in case of Escherichia coli
x[i] <- 'Escherichia coli'
}
if (tolower(x[i]) == '^st.*au$'
| tolower(x[i]) == '^stau$'
| tolower(x[i]) == '^staaur$') {
# avoid detection of Staphylococcus auricularis in case of S. aureus
x[i] <- 'Staphylococcus aureus'
}
if (tolower(x[i]) == '^p.*aer$') {
# avoid detection of Pasteurella aerogenes in case of Pseudomonas aeruginosa
x[i] <- 'Pseudomonas aeruginosa'
}
# translate known trivial names to genus+species
if (toupper(x.bak[i]) == 'MRSA'
| toupper(x.bak[i]) == 'VISA'
| toupper(x.bak[i]) == 'VRSA') {
x[i] <- 'Staphylococcus aureus'
}
if (toupper(x.bak[i]) == 'MRSE') {
x[i] <- 'Staphylococcus epidermidis'
}
if (toupper(x.bak[i]) == 'VRE') {
x[i] <- 'Enterococcus'
}
# let's try the ID's first
found <- AMR::bactlist %>% filter(bactid == x.bak[i])
if (nrow(found) == 0) {
# now try exact match
found <- AMR::bactlist %>% filter(fullname == x[i])
}
if (nrow(found) == 0) {
# try any match
found <- AMR::bactlist %>% filter(fullname %like% x[i])
}
if (nrow(found) == 0) {
# try only genus, with 'species' attached
found <- AMR::bactlist %>% filter(fullname %like% x_species[i])
}
if (nrow(found) == 0) {
# try splitting of characters and then find ID
# like esco = E. coli, klpn = K. pneumoniae, stau = S. aureus
x_length <- nchar(x.bak[i])
x[i] <- paste0(x.bak[i] %>% substr(1, x_length / 2) %>% trimws(),
'.* ',
x.bak[i] %>% substr((x_length / 2) + 1, x_length) %>% trimws())
found <- AMR::bactlist %>% filter(fullname %like% paste0('^', x[i]))
}
if (nrow(found) != 0) {
x[i] <- found %>%
slice(1) %>%
pull(bactid)
} else {
x[i] <- ""
}
}
x
}

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@ -23,6 +23,7 @@ globalVariables(c('.',
'date_lab',
'days_diff',
'first_isolate_row_index',
'fullname',
'genus',
'gramstain',
'key_ab',

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@ -4,23 +4,28 @@
#' @rdname join
#' @name join
#' @aliases join inner_join
#' @param x existing table to join
#' @param x existing table to join, also supports character vectors
#' @param by a variable to join by - could be a column name of \code{x} with values that exist in \code{bactlist$bactid} (like \code{by = "bacteria_id"}), or another column in \code{\link{bactlist}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})
#' @param suffix if there are non-joined duplicate variables in \code{x} and \code{y}, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.
#' @param ... other parameters to pass on to \code{dplyr::\link[dplyr]{join}}.
#' @details As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
#' @details As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, characters vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
#' @export
#' @examples
#' left_join_bactlist("STAAUR")
#'
#' df <- data.frame(date = seq(from = as.Date("2018-01-01"),
#' to = as.Date("2018-01-07"),
#' by = 1),
#' bacteria_id = c("STAAUR", "STAAUR", "STAAUR", "STAAUR",
#' "ESCCOL", "ESCCOL", "ESCCOL"),
#' stringsAsFactors = FALSE)
#'
#' colnames(df)
#' df2 <- left_join_bactlist(df, "bacteria_id")
#' colnames(df2)
inner_join_bactlist <- function(x, by = 'bactid', ...) {
inner_join_bactlist <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
if (any(class(x) %in% c('character', 'factor'))) {
x <- data.frame(bactid = x, stringsAsFactors = FALSE)
}
# no name set to `by` parameter
if (is.null(names(by))) {
joinby <- colnames(AMR::bactlist)[1]
@ -37,7 +42,10 @@ inner_join_bactlist <- function(x, by = 'bactid', ...) {
#' @rdname join
#' @export
left_join_bactlist <- function(x, by = 'bactid', ...) {
left_join_bactlist <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
if (any(class(x) %in% c('character', 'factor'))) {
x <- data.frame(bactid = x, stringsAsFactors = FALSE)
}
# no name set to `by` parameter
if (is.null(names(by))) {
joinby <- colnames(AMR::bactlist)[1]
@ -54,7 +62,10 @@ left_join_bactlist <- function(x, by = 'bactid', ...) {
#' @rdname join
#' @export
right_join_bactlist <- function(x, by = 'bactid', ...) {
right_join_bactlist <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
if (any(class(x) %in% c('character', 'factor'))) {
x <- data.frame(bactid = x, stringsAsFactors = FALSE)
}
# no name set to `by` parameter
if (is.null(names(by))) {
joinby <- colnames(AMR::bactlist)[1]
@ -71,7 +82,10 @@ right_join_bactlist <- function(x, by = 'bactid', ...) {
#' @rdname join
#' @export
full_join_bactlist <- function(x, by = 'bactid', ...) {
full_join_bactlist <- function(x, by = 'bactid', suffix = c("2", ""), ...) {
if (any(class(x) %in% c('character', 'factor'))) {
x <- data.frame(bactid = x, stringsAsFactors = FALSE)
}
# no name set to `by` parameter
if (is.null(names(by))) {
joinby <- colnames(AMR::bactlist)[1]
@ -85,6 +99,9 @@ full_join_bactlist <- function(x, by = 'bactid', ...) {
#' @rdname join
#' @export
semi_join_bactlist <- function(x, by = 'bactid', ...) {
if (any(class(x) %in% c('character', 'factor'))) {
x <- data.frame(bactid = x, stringsAsFactors = FALSE)
}
# no name set to `by` parameter
if (is.null(names(by))) {
joinby <- colnames(AMR::bactlist)[1]
@ -98,6 +115,9 @@ semi_join_bactlist <- function(x, by = 'bactid', ...) {
#' @rdname join
#' @export
anti_join_bactlist <- function(x, by = 'bactid', ...) {
if (any(class(x) %in% c('character', 'factor'))) {
x <- data.frame(bactid = x, stringsAsFactors = FALSE)
}
# no name set to `by` parameter
if (is.null(names(by))) {
joinby <- colnames(AMR::bactlist)[1]

View File

@ -19,17 +19,20 @@
# No export, no Rd
"%like%" <- function(vector, pattern) {
# Source: https://github.com/Rdatatable/data.table/blob/master/R/like.R
# But made it case insensitive
if (is.factor(vector)) {
as.integer(vector) %in% grep(pattern, levels(vector))
as.integer(vector) %in% grep(pattern, levels(vector), ignore.case = TRUE)
} else {
grepl(pattern, vector)
grepl(pattern, vector, ignore.case = TRUE)
}
}
# No export, no Rd
percent <- function(x, round = 1, ...) {
base::paste0(base::round(x * 100, digits = round), "%")
}
# No export, no Rd
quasiquotate <- function(deparsed, parsed) {
# when text: remove first and last "
if (any(deparsed %like% '^".+"$' | deparsed %like% "^'.+'$")) {
@ -46,4 +49,4 @@ quasiquotate <- function(deparsed, parsed) {
} else {
parsed
}
}
}

View File

@ -28,7 +28,7 @@ This package is available on CRAN and also here on GitHub.
### From GitHub (latest development version)
[![Travis_Build](https://travis-ci.org/msberends/AMR.svg?branch=master)](https://travis-ci.org/msberends/AMR)
[![Since_Release](https://img.shields.io/github/commits-since/msberends/AMR/latest.svg?colorB=3679BC)](https://github.com/msberends/AMR/releases)
[![Since_Release](https://img.shields.io/github/commits-since/msberends/AMR/latest.svg?colorB=3679BC)](https://github.com/msberends/AMR/commits/master)
[![Last_Commit](https://img.shields.io/github/last-commit/msberends/AMR.svg?colorB=3679BC)](https://github.com/msberends/AMR/commits/master)
```r
@ -116,7 +116,14 @@ A plot of `rsi_data`:
plot(rsi_data)
```
![example](man/figures/rsi_example.png)
![example1](man/figures/rsi_example.png)
A plot of `mic_data` (defaults to bar plot):
```r
plot(mic_data)
```
![example2](man/figures/mic_example.png)
Other epidemiological functions:

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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{ablist}
\alias{ablist}
\title{Dataset with 420 antibiotics}
\format{A data.frame with 420 observations and 12 variables:
\describe{
\item{\code{atc}}{ATC code, like \code{J01CR02}}
\item{\code{molis}}{MOLIS code, like \code{amcl}}
\item{\code{umcg}}{UMCG code, like \code{AMCL}}
\item{\code{official}}{Official name by the WHO, like \code{"amoxicillin and enzyme inhibitor"}}
\item{\code{official_nl}}{Official name in the Netherlands, like \code{"Amoxicilline met enzymremmer"}}
\item{\code{trivial_nl}}{Trivial name in Dutch, like \code{"Amoxicilline/clavulaanzuur"}}
\item{\code{oral_ddd}}{Defined Daily Dose (DDD) according to the WHO, oral treatment}
\item{\code{oral_units}}{Units of \code{ddd_units}}
\item{\code{iv_ddd}}{Defined Daily Dose (DDD) according to the WHO, parenteral treatment}
\item{\code{iv_units}}{Units of \code{iv_ddd}}
\item{\code{atc_group1}}{ATC group in Dutch, like \code{"Macroliden, lincosamiden en streptograminen"}}
\item{\code{atc_group2}}{Subgroup of \code{atc_group1} in Dutch, like \code{"Macroliden"}}
}}
\source{
MOLIS (LIS of Certe) - \url{https://www.certe.nl} \cr \cr GLIMS (LIS of UMCG) - \url{https://www.umcg.nl} \cr \cr World Health Organization - \url{https://www.whocc.no/atc_ddd_index/}
}
\usage{
ablist
}
\description{
A dataset containing all antibiotics with a J0 code, with their DDD's.
}
\seealso{
\code{\link{bactlist}}
}
\keyword{datasets}

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@ -4,7 +4,7 @@
\alias{abname}
\title{Name of an antibiotic}
\source{
\code{\link{ablist}}
\code{\link{antibiotics}}
}
\usage{
abname(abcode, from = "umcg", to = "official", textbetween = " + ",
@ -13,14 +13,14 @@ abname(abcode, from = "umcg", to = "official", textbetween = " + ",
\arguments{
\item{abcode}{a code or name, like \code{"AMOX"}, \code{"AMCL"} or \code{"J01CA04"}}
\item{from, to}{type to transform from and to. See \code{\link{ablist}} for its column names.}
\item{from, to}{type to transform from and to. See \code{\link{antibiotics}} for its column names.}
\item{textbetween}{text to put between multiple returned texts}
\item{tolower}{return output as lower case with function \code{\link{tolower}}.}
}
\description{
Convert antibiotic codes (from a laboratory information system like MOLIS or GLIMS) to a (trivial) antibiotic name or ATC code, or vice versa. This uses the data from \code{\link{ablist}}.
Convert antibiotic codes (from a laboratory information system like MOLIS or GLIMS) to a (trivial) antibiotic name or ATC code, or vice versa. This uses the data from \code{\link{antibiotics}}.
}
\examples{
abname("AMCL")

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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{antibiotics}
\alias{antibiotics}
\title{Dataset with 420 antibiotics}
\format{A data.frame with 420 observations and 16 variables:
\describe{
\item{\code{atc}}{ATC code, like \code{J01CR02}}
\item{\code{molis}}{MOLIS code, like \code{amcl}}
\item{\code{umcg}}{UMCG code, like \code{AMCL}}
\item{\code{official}}{Official name by the WHO, like \code{"Amoxicillin and enzyme inhibitor"}}
\item{\code{official_nl}}{Official name in the Netherlands, like \code{"Amoxicilline met enzymremmer"}}
\item{\code{trivial_nl}}{Trivial name in Dutch, like \code{"Amoxicilline/clavulaanzuur"}}
\item{\code{oral_ddd}}{Defined Daily Dose (DDD), oral treatment}
\item{\code{oral_units}}{Units of \code{ddd_units}}
\item{\code{iv_ddd}}{Defined Daily Dose (DDD), parenteral treatment}
\item{\code{iv_units}}{Units of \code{iv_ddd}}
\item{\code{atc_group1}}{ATC group, like \code{"Macrolides, lincosamides and streptogramins"}}
\item{\code{atc_group2}}{Subgroup of \code{atc_group1}, like \code{"Macrolides"}}
\item{\code{atc_group1_nl}}{ATC group in Dutch, like \code{"Macroliden, lincosamiden en streptograminen"}}
\item{\code{atc_group2_nl}}{Subgroup of \code{atc_group1} in Dutch, like \code{"Macroliden"}}
\item{\code{useful_gramnegative}}{\code{FALSE} if not useful according to EUCAST, \code{NA} otherwise (see Source)}
\item{\code{useful_grampositive}}{\code{FALSE} if not useful according to EUCAST, \code{NA} otherwise (see Source)}
}}
\source{
- World Health Organization: \url{https://www.whocc.no/atc_ddd_index/} \cr - EUCAST - Expert rules intrinsic exceptional V3.1 \cr - MOLIS (LIS of Certe): \url{https://www.certe.nl} \cr - GLIMS (LIS of UMCG): \url{https://www.umcg.nl}
}
\usage{
antibiotics
}
\description{
A dataset containing all antibiotics with a J0 code, with their DDD's. Properties were downloaded from the WHO, see Source.
}
\seealso{
\code{\link{bactlist}}
}
\keyword{datasets}

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@ -4,7 +4,7 @@
\name{bactlist}
\alias{bactlist}
\title{Dataset with ~2500 microorganisms}
\format{A data.frame with 2507 observations and 10 variables:
\format{A data.frame with 2507 observations and 12 variables:
\describe{
\item{\code{bactid}}{ID of microorganism}
\item{\code{bactsys}}{Bactsyscode of microorganism}
@ -13,9 +13,11 @@
\item{\code{species}}{Species name of microorganism, like \code{"coli"}}
\item{\code{subspecies}}{Subspecies name of bio-/serovar of microorganism, like \code{"EHEC"}}
\item{\code{fullname}}{Full name, like \code{"Echerichia coli (EHEC)"}}
\item{\code{type}}{Type of microorganism in Dutch, like \code{"Bacterie"} and \code{"Schimmel/gist"}}
\item{\code{gramstain}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
\item{\code{aerobic}}{Type aerobe/anaerobe of bacteria}
\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{aerobic}}{Logical whether bacteria is aerobic}
\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"}}
}}
\source{
MOLIS (LIS of Certe) - \url{https://www.certe.nl}
@ -27,6 +29,6 @@ bactlist
A dataset containing all microorganisms of MOLIS. MO codes of the UMCG can be looked up using \code{\link{bactlist.umcg}}.
}
\seealso{
\code{\link{ablist}} \code{\link{bactlist.umcg}}
\code{\link{guess_bactid}} \code{\link{antibiotics}} \code{\link{bactlist.umcg}}
}
\keyword{datasets}

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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/first_isolates.R
\name{guess_bactid}
\alias{guess_bactid}
\title{Find bacteria ID based on genus/species}
\usage{
guess_bactid(x)
}
\arguments{
\item{x}{character vector to determine \code{bactid}}
}
\value{
Character (vector).
}
\description{
Use this function to determine a valid ID based on a genus (and species). This input could be a full name (like \code{"Staphylococcus aureus"}), an abbreviated name (like \code{"S. aureus"}), or just a genus. You could also use a \code{\link{paste}} of a genus and species column to use the full name as input: \code{x = paste(df$genus, df$species)}, where \code{df} is your dataframe.
}
\examples{
# These examples all return "STAAUR", the ID of S. aureus:
guess_bactid("stau")
guess_bactid("STAU")
guess_bactid("staaur")
guess_bactid("S. aureus")
guess_bactid("S aureus")
guess_bactid("Staphylococcus aureus")
guess_bactid("MRSA") # Methicillin-resistant S. aureus
guess_bactid("VISA") # Vancomycin Intermediate S. aureus
}
\seealso{
\code{\link{bactlist}} for the dataframe that is being used to determine ID's.
}

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@ -11,39 +11,42 @@
\alias{anti_join_bactlist}
\title{Join a table with \code{bactlist}}
\usage{
inner_join_bactlist(x, by = "bactid", ...)
inner_join_bactlist(x, by = "bactid", suffix = c("2", ""), ...)
left_join_bactlist(x, by = "bactid", ...)
left_join_bactlist(x, by = "bactid", suffix = c("2", ""), ...)
right_join_bactlist(x, by = "bactid", ...)
right_join_bactlist(x, by = "bactid", suffix = c("2", ""), ...)
full_join_bactlist(x, by = "bactid", ...)
full_join_bactlist(x, by = "bactid", suffix = c("2", ""), ...)
semi_join_bactlist(x, by = "bactid", ...)
anti_join_bactlist(x, by = "bactid", ...)
}
\arguments{
\item{x}{existing table to join}
\item{x}{existing table to join, also supports character vectors}
\item{by}{a variable to join by - could be a column name of \code{x} with values that exist in \code{bactlist$bactid} (like \code{by = "bacteria_id"}), or another column in \code{\link{bactlist}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})}
\item{suffix}{if there are non-joined duplicate variables in \code{x} and \code{y}, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.}
\item{...}{other parameters to pass on to \code{dplyr::\link[dplyr]{join}}.}
}
\description{
Join the list of microorganisms \code{\link{bactlist}} easily to an existing table.
}
\details{
As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, characters vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
}
\examples{
left_join_bactlist("STAAUR")
df <- data.frame(date = seq(from = as.Date("2018-01-01"),
to = as.Date("2018-01-07"),
by = 1),
bacteria_id = c("STAAUR", "STAAUR", "STAAUR", "STAAUR",
"ESCCOL", "ESCCOL", "ESCCOL"),
stringsAsFactors = FALSE)
colnames(df)
df2 <- left_join_bactlist(df, "bacteria_id")
colnames(df2)

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@ -33,5 +33,5 @@ tbl$keyab <- key_antibiotics(tbl)
}
}
\seealso{
\code{\link{mo_property}} \code{\link{ablist}}
\code{\link{mo_property}} \code{\link{antibiotics}}
}

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@ -15,7 +15,7 @@
\item{\code{sex}}{sex of the patient}
\item{\code{patient_id}}{ID of the patient, first 10 characters of an SHA hash containing irretrievable information}
\item{\code{bactid}}{ID of microorganism, see \code{\link{bactlist}}}
\item{\code{peni:mupi}}{38 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}), these column names occur in \code{\link{ablist}} and can be translated with \code{\link{abname}}}
\item{\code{peni:mupi}}{38 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}), these column names occur in \code{\link{antibiotics}} and can be translated with \code{\link{abname}}}
}}
\source{
MOLIS (LIS of Certe) - \url{https://www.certe.nl}