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big website update, licence txt update
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R/data.R
71
R/data.R
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# AUTHORS #
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# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
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# SOURCE #
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# https://gitlab.com/msberends/AMR #
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# #
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# LICENCE #
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# This package is free software; you can redistribute it and/or modify #
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# it under the terms of the GNU General Public License version 2.0, #
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# as published by the Free Software Foundation. #
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# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
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# #
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# This R package is distributed in the hope that it will be useful, #
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# but WITHOUT ANY WARRANTY; without even the implied warranty of #
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
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# GNU General Public License version 2.0 for more details. #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# #
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# This R package was created for academic research and was publicly #
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# released in the hope that it will be useful, but it comes WITHOUT #
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# ANY WARRANTY OR LIABILITY. #
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# Visit our website for more info: https://msberends.gitab.io/AMR. #
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# ==================================================================== #
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#' Data set with 423 antibiotics
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#' \item{\code{useful_grampositive}}{\code{FALSE} if not useful according to EUCAST, \code{NA} otherwise (see Source)}
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#' }
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#' @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}
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#' @inheritSection AMR Read more on our website!
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#' @seealso \code{\link{microorganisms}}
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# use this later to further fill AMR::antibiotics
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# drug <- "Ciprofloxacin"
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#' Data set with taxonomic data from ITIS
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#'
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#' A data set containing the complete microbial taxonomy of the kingdoms Bacteria, Fungi and Protozoa. MO codes can be looked up using \code{\link{as.mo}}.
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#' @inheritSection as.mo ITIS
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#' @inheritSection itis ITIS
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#' @format A \code{\link{data.frame}} with 18,833 observations and 15 variables:
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#' \describe{
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#' \item{\code{mo}}{ID of microorganism}
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#' \item{\code{ref}}{Author(s) and year of concerning publication as found in ITIS, see Source}
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#' }
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#' @source [3] Integrated Taxonomic Information System (ITIS) on-line database, \url{https://www.itis.gov}.
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#' @inheritSection AMR Read more on our website!
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#' @seealso \code{\link{as.mo}} \code{\link{mo_property}} \code{\link{microorganisms.umcg}}
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"microorganisms"
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#' \item{\code{ref}}{Author(s) and year of concerning publication as found in ITIS, see Source}
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#' }
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#' @source [3] Integrated Taxonomic Information System (ITIS) on-line database, \url{https://www.itis.gov}.
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#' @inheritSection AMR Read more on our website!
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#' @seealso \code{\link{as.mo}} \code{\link{mo_property}} \code{\link{microorganisms}}
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"microorganisms.old"
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#' \item{\code{umcg}}{Code of microorganism according to UMCG MMB}
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#' \item{\code{certe}}{Code of microorganism according to Certe MMB}
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#' }
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#' @inheritSection AMR Read more on our website!
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#' @seealso \code{\link{as.mo}} \code{\link{microorganisms.certe}} \code{\link{microorganisms}}
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"microorganisms.umcg"
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#' \item{\code{certe}}{Code of microorganism according to Certe MMB}
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#' \item{\code{mo}}{Code of microorganism in \code{\link{microorganisms}}}
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#' }
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#' @inheritSection AMR Read more on our website!
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#' @seealso \code{\link{as.mo}} \code{\link{microorganisms}}
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"microorganisms.certe"
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#' Data set with 2000 blood culture isolates of septic patients
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#'
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#' An anonymised data set containing 2,000 microbial blood culture isolates with their full antibiograms found in septic patients in 4 different hospitals in the Netherlands, between 2001 and 2017. It is true, genuine data. This \code{data.frame} can be used to practice AMR analysis. For examples, press F1.
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#' An anonymised data set containing 2,000 microbial blood culture isolates with their full antibiograms found in septic patients in 4 different hospitals in the Netherlands, between 2001 and 2017. It is true, genuine data. This \code{data.frame} can be used to practice AMR analysis. For examples, please read \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{the tutorial on our website}.
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#' @format A \code{\link{data.frame}} with 2,000 observations and 49 variables:
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#' \describe{
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#' \item{\code{date}}{date of receipt at the laboratory}
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#' \item{\code{mo}}{ID of microorganism created with \code{\link{as.mo}}, see also \code{\link{microorganisms}}}
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#' \item{\code{peni:rifa}}{40 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}); these column names occur in \code{\link{antibiotics}} data set and can be translated with \code{\link{abname}}}
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#' }
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#' @examples
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#' # ----------- #
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#' # PREPARATION #
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#' # ----------- #
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#'
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#' # Save this example data set to an object, so we can edit it:
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#' my_data <- septic_patients
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#'
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#' # load the dplyr package to make data science A LOT easier
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#' library(dplyr)
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#'
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#' # Add first isolates to our data set:
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#' my_data <- my_data %>%
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#' mutate(first_isolates = first_isolate(my_data, "date", "patient_id", "mo"))
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#'
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#' # -------- #
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#' # ANALYSIS #
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#' # -------- #
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#'
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#' # 1. Get the amoxicillin resistance percentages (p)
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#' # and numbers (n) of E. coli, divided by hospital:
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#'
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#' my_data %>%
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#' filter(mo == guess_mo("E. coli"),
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#' first_isolates == TRUE) %>%
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#' group_by(hospital_id) %>%
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#' summarise(n = n_rsi(amox),
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#' p = portion_IR(amox))
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#'
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#'
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#' # 2. Get the amoxicillin/clavulanic acid resistance
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#' # percentages of E. coli, trend over the years:
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#'
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#' my_data %>%
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#' filter(mo == guess_mo("E. coli"),
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#' first_isolates == TRUE) %>%
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#' group_by(year = format(date, "%Y")) %>%
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#' summarise(n = n_rsi(amcl),
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#' p = portion_IR(amcl, minimum = 20))
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#' @inheritSection AMR Read more on our website!
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"septic_patients"
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#' Supplementary Data
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#' These \code{\link{data.table}s} are transformed from the \code{\link{microorganisms}} and \code{\link{microorganisms}} data sets to improve speed of \code{\link{as.mo}}. They are meant for internal use only, and are only mentioned here for reference.
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#' @rdname supplementary_data
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#' @name supplementary_data
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#' @inheritSection AMR Read more on our website!
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# # Renew data:
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# microorganismsDT <- data.table::as.data.table(AMR::microorganisms)
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# # sort on (1) bacteria, (2) fungi, (3) protozoa and then human pathogenic prevalence and then TSN:
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