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new tibble export
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116
R/data.R
116
R/data.R
@ -27,7 +27,7 @@
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#'
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#' Two data sets containing all antibiotics/antimycotics and antivirals. Use [as.ab()] or one of the [`ab_*`][ab_property()] functions to retrieve values from the [antibiotics] data set. Three identifiers are included in this data set: an antibiotic ID (`ab`, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (`atc`) as defined by the WHO, and a Compound ID (`cid`) as found in PubChem. Other properties in this data set are derived from one or more of these codes. Note that some drugs have multiple ATC codes.
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#' @format
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#' ## For the [antibiotics] data set: a [data.frame] with `r nrow(antibiotics)` observations and `r ncol(antibiotics)` variables:
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#' ## For the [antibiotics] data set: a [tibble[tibble::tibble] with `r nrow(antibiotics)` observations and `r ncol(antibiotics)` variables:
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#' - `ab`\cr Antibiotic ID as used in this package (such as `AMC`), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
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#' - `cid`\cr Compound ID as found in PubChem
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#' - `name`\cr Official name as used by WHONET/EARS-Net or the WHO
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@ -43,7 +43,7 @@
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#' - `iv_units`\cr Units of `iv_ddd`
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#' - `loinc`\cr All LOINC codes (Logical Observation Identifiers Names and Codes) associated with the name of the antimicrobial agent. Use [ab_loinc()] to retrieve them quickly, see [ab_property()].
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#'
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#' ## For the [antivirals] data set: a [data.frame] with `r nrow(antivirals)` observations and `r ncol(antivirals)` variables:
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#' ## For the [antivirals] data set: a [tibble[tibble::tibble] with `r nrow(antivirals)` observations and `r ncol(antivirals)` variables:
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#' - `atc`\cr ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC
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#' - `cid`\cr Compound ID as found in PubChem
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#' - `name`\cr Official name as used by WHONET/EARS-Net or the WHO
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@ -58,24 +58,15 @@
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#' Synonyms (i.e. trade names) were derived from the Compound ID (`cid`) and consequently only available where a CID is available.
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#'
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#' ## Direct download
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#' These data sets are available as 'flat files' for use even without \R - you can find the files here:
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#'
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#' * <https://github.com/msberends/AMR/raw/main/data-raw/antibiotics.txt>
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#' * <https://github.com/msberends/AMR/raw/main/data-raw/antivirals.txt>
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#'
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#' Files in \R format (with preserved data structure) can be found here:
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#'
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#' * <https://github.com/msberends/AMR/raw/main/data/antibiotics.rda>
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#' * <https://github.com/msberends/AMR/raw/main/data/antivirals.rda>
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#' Like all data sets in this package, these data sets are publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
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#' @source World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): <https://www.whocc.no/atc_ddd_index/>
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#'
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#' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm>
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#' @inheritSection AMR Reference Data Publicly Available
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#' @inheritSection WHOCC WHOCC
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#' @seealso [microorganisms], [intrinsic_resistant]
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#' @examples
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#' head(antibiotics)
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#' head(antivirals)
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#' antibiotics
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#' antivirals
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"antibiotics"
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#' @rdname antibiotics
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@ -85,7 +76,7 @@
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#'
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#' A data set containing the full microbial taxonomy (**last updated: `r CATALOGUE_OF_LIFE$yearmonth_LPSN`**) of `r nr2char(length(unique(microorganisms$kingdom[!microorganisms$kingdom %like% "unknown"])))` kingdoms from the Catalogue of Life (CoL) and the List of Prokaryotic names with Standing in Nomenclature (LPSN). MO codes can be looked up using [as.mo()].
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#' @inheritSection catalogue_of_life Catalogue of Life
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#' @format A [data.frame] with `r format(nrow(microorganisms), big.mark = ",")` observations and `r ncol(microorganisms)` variables:
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#' @format A [tibble[tibble::tibble] with `r format(nrow(microorganisms), big.mark = ",")` observations and `r ncol(microorganisms)` variables:
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#' - `mo`\cr ID of microorganism as used by this package
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#' - `fullname`\cr Full name, like `"Escherichia coli"`
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#' - `kingdom`, `phylum`, `class`, `order`, `family`, `genus`, `species`, `subspecies`\cr Taxonomic rank of the microorganism
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@ -114,10 +105,7 @@
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#' - 6 families under the Enterobacterales order, according to Adeolu *et al.* (2016, PMID 27620848), that are not (yet) in the Catalogue of Life
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#'
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#' ## Direct download
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#' This data set is available as 'flat file' for use even without \R - you can find the file here: <https://github.com/msberends/AMR/raw/main/data-raw/microorganisms.txt>.
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#'
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#' The file in \R format (with preserved data structure) can be found here: <https://github.com/msberends/AMR/raw/main/data/microorganisms.rda>.
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#'
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#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
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#' @section About the Records from LPSN (see *Source*):
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#' The List of Prokaryotic names with Standing in Nomenclature (LPSN) provides comprehensive information on the nomenclature of prokaryotes. LPSN is a free to use service founded by Jean P. Euzeby in 1997 and later on maintained by Aidan C. Parte.
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#'
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@ -137,80 +125,80 @@
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#' `r SNOMED_VERSION$current_source` as currently implemented in this `AMR` package:
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#'
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#' * Retrieved from the `r SNOMED_VERSION$title`, OID `r SNOMED_VERSION$current_oid`, version `r SNOMED_VERSION$current_version`; url: <`r SNOMED_VERSION$url`>
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#' @inheritSection AMR Reference Data Publicly Available
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#' @seealso [as.mo()], [mo_property()], [microorganisms.codes], [intrinsic_resistant]
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#' @examples
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#' head(microorganisms)
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#' microorganisms
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"microorganisms"
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#' Data Set with Previously Accepted Taxonomic Names
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#'
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#' A data set containing old (previously valid or accepted) taxonomic names according to the Catalogue of Life. This data set is used internally by [as.mo()].
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#' @inheritSection catalogue_of_life Catalogue of Life
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#' @format A [data.frame] with `r format(nrow(microorganisms.old), big.mark = ",")` observations and `r ncol(microorganisms.old)` variables:
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#' @format A [tibble[tibble::tibble] with `r format(nrow(microorganisms.old), big.mark = ",")` observations and `r ncol(microorganisms.old)` variables:
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#' - `fullname`\cr Old full taxonomic name of the microorganism
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#' - `fullname_new`\cr New full taxonomic name of the microorganism
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#' - `ref`\cr Author(s) and year of concerning scientific publication
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#' - `prevalence`\cr Prevalence of the microorganism, see [as.mo()]
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#' @details
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#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
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#' @source Catalogue of Life: Annual Checklist (public online taxonomic database), <http://www.catalogueoflife.org> (check included annual version with [catalogue_of_life_version()]).
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#'
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#' Parte, A.C. (2018). LPSN - List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on. International Journal of Systematic and Evolutionary Microbiology, 68, 1825-1829; \doi{10.1099/ijsem.0.002786}
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#' @inheritSection AMR Reference Data Publicly Available
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#' @seealso [as.mo()] [mo_property()] [microorganisms]
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#' @examples
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#' head(microorganisms.old)
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#' microorganisms.old
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"microorganisms.old"
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#' Data Set with `r format(nrow(microorganisms.codes), big.mark = ",")` Common Microorganism Codes
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#'
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#' A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with [set_mo_source()]. They will all be searched when using [as.mo()] and consequently all the [`mo_*`][mo_property()] functions.
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#' @format A [data.frame] with `r format(nrow(microorganisms.codes), big.mark = ",")` observations and `r ncol(microorganisms.codes)` variables:
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#' @format A [tibble[tibble::tibble] with `r format(nrow(microorganisms.codes), big.mark = ",")` observations and `r ncol(microorganisms.codes)` variables:
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#' - `code`\cr Commonly used code of a microorganism
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#' - `mo`\cr ID of the microorganism in the [microorganisms] data set
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#' @inheritSection AMR Reference Data Publicly Available
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#' @details
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#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
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#' @inheritSection catalogue_of_life Catalogue of Life
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#' @seealso [as.mo()] [microorganisms]
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#' @examples
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#' head(microorganisms.codes)
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#' microorganisms.codes
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"microorganisms.codes"
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#' Data Set with `r format(nrow(example_isolates), big.mark = ",")` Example Isolates
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#'
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#' A data set containing `r format(nrow(example_isolates), big.mark = ",")` microbial isolates with their full antibiograms. The data set reflects reality and can be used to practice AMR data analysis. For examples, please read [the tutorial on our website](https://msberends.github.io/AMR/articles/AMR.html).
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#' @format A [data.frame] with `r format(nrow(example_isolates), big.mark = ",")` observations and `r ncol(example_isolates)` variables:
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#' - `date`\cr date of receipt at the laboratory
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#' - `hospital_id`\cr ID of the hospital, from A to D
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#' - `ward_icu`\cr [logical] to determine if ward is an intensive care unit
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#' - `ward_clinical`\cr [logical] to determine if ward is a regular clinical ward
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#' - `ward_outpatient`\cr [logical] to determine if ward is an outpatient clinic
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#' - `age`\cr age of the patient
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#' - `gender`\cr gender of the patient
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#' - `patient_id`\cr ID of the patient
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#' - `mo`\cr ID of microorganism created with [as.mo()], see also [microorganisms]
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#' - `PEN:RIF`\cr `r sum(vapply(FUN.VALUE = logical(1), example_isolates, is.rsi))` different antibiotics with class [`rsi`] (see [as.rsi()]); these column names occur in the [antibiotics] data set and can be translated with [ab_name()]
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#' @inheritSection AMR Reference Data Publicly Available
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#' A data set containing `r format(nrow(example_isolates), big.mark = ",")` microbial isolates with their full antibiograms. This data set contains randomised fictitious data, but reflects reality and can be used to practise AMR data analysis. For examples, please read [the tutorial on our website](https://msberends.github.io/AMR/articles/AMR.html).
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#' @format A [tibble[tibble::tibble] with `r format(nrow(example_isolates), big.mark = ",")` observations and `r ncol(example_isolates)` variables:
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#' - `date`\cr Date of receipt at the laboratory
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#' - `patient`\cr ID of the patient
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#' - `age`\cr Age of the patient
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#' - `gender`\cr Gender of the patient, either `r vector_or(example_isolates$gender)`
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#' - `ward`\cr Ward type where the patient was admitted, either `r vector_or(example_isolates$ward)`
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#' - `mo`\cr ID of microorganism created with [as.mo()], see also the [microorganisms] data set
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#' - `PEN:RIF`\cr `r sum(vapply(FUN.VALUE = logical(1), example_isolates, is.rsi))` different antibiotics with class [`rsi`] (see [as.rsi()]); these column names occur in the [antibiotics] data set and can be translated with [set_ab_names()] or [ab_name()]
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#' @details
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#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
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#' @examples
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#' head(example_isolates)
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#' example_isolates
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"example_isolates"
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#' Data Set with Unclean Data
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#'
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#' A data set containing `r format(nrow(example_isolates_unclean), big.mark = ",")` microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice.
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#' @format A [data.frame] with `r format(nrow(example_isolates_unclean), big.mark = ",")` observations and `r ncol(example_isolates_unclean)` variables:
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#' @format A [tibble[tibble::tibble] with `r format(nrow(example_isolates_unclean), big.mark = ",")` observations and `r ncol(example_isolates_unclean)` variables:
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#' - `patient_id`\cr ID of the patient
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#' - `date`\cr date of receipt at the laboratory
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#' - `hospital`\cr ID of the hospital, from A to C
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#' - `bacteria`\cr info about microorganism that can be transformed with [as.mo()], see also [microorganisms]
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#' - `AMX:GEN`\cr 4 different antibiotics that have to be transformed with [as.rsi()]
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#' @inheritSection AMR Reference Data Publicly Available
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#' @details
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#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
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#' @examples
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#' head(example_isolates_unclean)
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#' example_isolates_unclean
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"example_isolates_unclean"
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#' Data Set with `r format(nrow(WHONET), big.mark = ",")` Isolates - WHONET Example
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#'
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#' This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The antibiotic results are from our [example_isolates] data set. All patient names are created using online surname generators and are only in place for practice purposes.
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#' @format A [data.frame] with `r format(nrow(WHONET), big.mark = ",")` observations and `r ncol(WHONET)` variables:
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#' @format A [tibble[tibble::tibble] with `r format(nrow(WHONET), big.mark = ",")` observations and `r ncol(WHONET)` variables:
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#' - `Identification number`\cr ID of the sample
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#' - `Specimen number`\cr ID of the specimen
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#' - `Organism`\cr Name of the microorganism. Before analysis, you should transform this to a valid microbial class, using [as.mo()].
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@ -237,15 +225,16 @@
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#' - `Comment`\cr Other comments
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#' - `Date of data entry`\cr [Date] this data was entered in WHONET
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#' - `AMP_ND10:CIP_EE`\cr `r sum(vapply(FUN.VALUE = logical(1), WHONET, is.rsi))` different antibiotics. You can lookup the abbreviations in the [antibiotics] data set, or use e.g. [`ab_name("AMP")`][ab_name()] to get the official name immediately. Before analysis, you should transform this to a valid antibiotic class, using [as.rsi()].
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#' @inheritSection AMR Reference Data Publicly Available
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#' @details
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#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
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#' @examples
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#' head(WHONET)
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#' WHONET
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"WHONET"
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#' Data Set for R/SI Interpretation
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#'
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#' Data set containing reference data to interpret MIC and disk diffusion to R/SI values, according to international guidelines. Currently implemented guidelines are EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`). Use [as.rsi()] to transform MICs or disks measurements to R/SI values.
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#' @format A [data.frame] with `r format(nrow(rsi_translation), big.mark = ",")` observations and `r ncol(rsi_translation)` variables:
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#' @format A [tibble[tibble::tibble] with `r format(nrow(rsi_translation), big.mark = ",")` observations and `r ncol(rsi_translation)` variables:
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#' - `guideline`\cr Name of the guideline
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#' - `method`\cr Either `r vector_or(rsi_translation$method)`
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#' - `site`\cr Body site, e.g. "Oral" or "Respiratory"
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@ -258,31 +247,35 @@
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#' - `breakpoint_R`\cr Highest MIC value or lowest number of millimetres that leads to "R"
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#' - `uti`\cr A [logical] value (`TRUE`/`FALSE`) to indicate whether the rule applies to a urinary tract infection (UTI)
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#' @details
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#' The repository of this `AMR` package contains a file comprising this exact data set: <https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt>. This file **allows for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically and the `mo` and `ab` columns have been transformed to contain the full official names instead of codes.
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#' @inheritSection AMR Reference Data Publicly Available
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#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
|
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#'
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#' They **allow for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the MS Excel and PDF files distributed by EUCAST and CLSI.
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#' @seealso [intrinsic_resistant]
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#' @examples
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#' head(rsi_translation)
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#' rsi_translation
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"rsi_translation"
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#' Data Set with Bacterial Intrinsic Resistance
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#'
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#' Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations.
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#' @format A [data.frame] with `r format(nrow(intrinsic_resistant), big.mark = ",")` observations and `r ncol(intrinsic_resistant)` variables:
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||||
#' @format A [tibble[tibble::tibble] with `r format(nrow(intrinsic_resistant), big.mark = ",")` observations and `r ncol(intrinsic_resistant)` variables:
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#' - `mo`\cr Microorganism ID
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#' - `ab`\cr Antibiotic ID
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||||
#' @details The repository of this `AMR` package contains a file comprising this data set with full taxonomic and antibiotic names: <https://github.com/msberends/AMR/blob/main/data-raw/intrinsic_resistant.txt>. This file **allows for machine reading EUCAST guidelines about intrinsic resistance**, which is almost impossible with the Excel and PDF files distributed by EUCAST. The file is updated automatically.
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#'
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#' @details
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||||
#' This data set is based on `r format_eucast_version_nr(3.3)`.
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#' @inheritSection AMR Reference Data Publicly Available
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#'
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||||
#' ## Direct download
|
||||
#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
|
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#'
|
||||
#' They **allow for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the MS Excel and PDF files distributed by EUCAST and CLSI.
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#' @examples
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#' head(intrinsic_resistant)
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#' intrinsic_resistant
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"intrinsic_resistant"
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#' Data Set with Treatment Dosages as Defined by EUCAST
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||||
#'
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#' EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with [eucast_dosage()].
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||||
#' @format A [data.frame] with `r format(nrow(dosage), big.mark = ",")` observations and `r ncol(dosage)` variables:
|
||||
#' @format A [tibble[tibble::tibble] with `r format(nrow(dosage), big.mark = ",")` observations and `r ncol(dosage)` variables:
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||||
#' - `ab`\cr Antibiotic ID as used in this package (such as `AMC`), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
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||||
#' - `name`\cr Official name of the antimicrobial agent as used by WHONET/EARS-Net or the WHO
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||||
#' - `type`\cr Type of the dosage, either `r vector_or(dosage$type)`
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||||
@ -292,8 +285,11 @@
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#' - `notes`\cr Additional dosage notes
|
||||
#' - `original_txt`\cr Original text in the PDF file of EUCAST
|
||||
#' - `eucast_version`\cr Version number of the EUCAST Clinical Breakpoints guideline to which these dosages apply
|
||||
#' @details `r format_eucast_version_nr(11.0)` are based on the dosages in this data set.
|
||||
#' @inheritSection AMR Reference Data Publicly Available
|
||||
#' @details
|
||||
#' This data set is based on `r format_eucast_version_nr(11.0)`.
|
||||
#'
|
||||
#' ## Direct download
|
||||
#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
|
||||
#' @examples
|
||||
#' head(dosage)
|
||||
#' dosage
|
||||
"dosage"
|
||||
|
||||
Reference in New Issue
Block a user