mirror of https://github.com/msberends/AMR.git
add mo_pathogenicity
This commit is contained in:
parent
4801a6067e
commit
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@ -47,7 +47,7 @@ jobs:
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matrix:
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config:
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# Test all old versions of R >= 3.0, we support them all!
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# For these old versions, dependencies will not be installed and checked.
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# For these old versions, dependencies and vignettes will not be checked.
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# For recent R versions, see check-recent.yaml (r-lib and tidyverse support the latest 5 major R versions).
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- {os: ubuntu-22.04, r: '3.4', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
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- {os: ubuntu-22.04, r: '3.3', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
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@ -82,8 +82,8 @@ jobs:
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as.data.frame(utils::installed.packages())[, "Version", drop = FALSE]
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shell: Rscript {0}
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- name: Remove vignettes on R without knitr support
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if: matrix.config.r == '3.0' || matrix.config.r == '3.1' || matrix.config.r == '3.2' || matrix.config.r == '3.3'
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- name: Remove vignettes
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if: always() # matrix.config.r == '3.0' || matrix.config.r == '3.1' || matrix.config.r == '3.2' || matrix.config.r == '3.3'
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# writing to DESCRIPTION2 and then moving to DESCRIPTION is required for R <= 3.3 as writeLines() cannot overwrite
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run: |
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rm -rf vignettes
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@ -101,7 +101,7 @@ jobs:
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_R_CHECK_LENGTH_1_CONDITION_: verbose
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_R_CHECK_LENGTH_1_LOGIC2_: verbose
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# no check for old R versions - these packages require higher R versions
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_R_CHECK_RD_XREFS_: ${{ matrix.config.r != '3.0' && matrix.config.r != '3.1' && matrix.config.r != '3.2' && matrix.config.r != '3.3' && matrix.config.r != '3.4' }}
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_R_CHECK_RD_XREFS_: false
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_R_CHECK_FORCE_SUGGESTS_: false
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R_CHECK_CONSTANTS: 5
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R_JIT_STRATEGY: 3
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@ -99,6 +99,5 @@ jobs:
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- name: Show tinytest output
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if: always()
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run: |
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ls -lh
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find . -name 'tinytest.Rout*' -exec cat '{}' \; || true
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shell: bash
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@ -1,5 +1,5 @@
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Package: AMR
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Version: 1.8.2.9083
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Version: 1.8.2.9084
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Date: 2023-01-06
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Title: Antimicrobial Resistance Data Analysis
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Description: Functions to simplify and standardise antimicrobial resistance (AMR)
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@ -313,6 +313,7 @@ export(mo_lpsn)
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export(mo_matching_score)
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export(mo_name)
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export(mo_order)
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export(mo_pathogenicity)
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export(mo_phylum)
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export(mo_property)
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export(mo_rank)
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2
NEWS.md
2
NEWS.md
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@ -1,4 +1,4 @@
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# AMR 1.8.2.9083
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# AMR 1.8.2.9084
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*(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*
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@ -45,17 +45,19 @@
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#'
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#' Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions [mo_kingdom()] and [mo_domain()] return the exact same results.
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#'
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#' Determination of the Gram stain - [mo_gramstain()] - will be based on the taxonomic kingdom and phylum. Originally, Cavalier-Smith defined the so-called subkingdoms Negibacteria and Posibacteria (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318/)), and only considered these phyla as Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes. These phyla were renamed to Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota (2021, [PMID 34694987](https://pubmed.ncbi.nlm.nih.gov/34694987/)). Bacteria in these phyla are considered Gram-positive in this `AMR` package, except for members of the class Negativicutes (within phylum Bacillota) which are Gram-negative. All other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [mo_is_gram_negative()] and [mo_is_gram_positive()] always return `TRUE` or `FALSE` (or `NA` when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
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#' Determination of human pathogenicity ([mo_pathogenicity()]) is strongly based on Bartlett *et al.* (2022, \doi{10.1099/mic.0.001269}). This function returns a [factor] with the levels *Pathogenic*, *Potentially pathogenic*, *Non-pathogenic*, and *Unknown*.
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#'
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#' Determination of yeasts - [mo_is_yeast()] - will be based on the taxonomic kingdom and class. *Budding yeasts* are fungi of the phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes). *True yeasts* are aggregated into the underlying order Saccharomycetales. Thus, for all microorganisms that are member of the taxonomic class Saccharomycetes, the function will return `TRUE`. It returns `FALSE` otherwise (or `NA` when the input is `NA` or the MO code is `UNKNOWN`).
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#' Determination of the Gram stain ([mo_gramstain()]) will be based on the taxonomic kingdom and phylum. Originally, Cavalier-Smith defined the so-called subkingdoms Negibacteria and Posibacteria (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318/)), and only considered these phyla as Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes. These phyla were renamed to Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota (2021, [PMID 34694987](https://pubmed.ncbi.nlm.nih.gov/34694987/)). Bacteria in these phyla are considered Gram-positive in this `AMR` package, except for members of the class Negativicutes (within phylum Bacillota) which are Gram-negative. All other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [mo_is_gram_negative()] and [mo_is_gram_positive()] always return `TRUE` or `FALSE` (or `NA` when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
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#'
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#' Determination of intrinsic resistance - [mo_is_intrinsic_resistant()] - will be based on the [intrinsic_resistant] data set, which is based on `r format_eucast_version_nr(3.3)`. The [mo_is_intrinsic_resistant()] function can be vectorised over both argument `x` (input for microorganisms) and `ab` (input for antibiotics).
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#' Determination of yeasts ([mo_is_yeast()]) will be based on the taxonomic kingdom and class. *Budding yeasts* are fungi of the phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes). *True yeasts* are aggregated into the underlying order Saccharomycetales. Thus, for all microorganisms that are member of the taxonomic class Saccharomycetes, the function will return `TRUE`. It returns `FALSE` otherwise (or `NA` when the input is `NA` or the MO code is `UNKNOWN`).
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#'
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#' Determination of intrinsic resistance ([mo_is_intrinsic_resistant()]) will be based on the [intrinsic_resistant] data set, which is based on `r format_eucast_version_nr(3.3)`. The [mo_is_intrinsic_resistant()] function can be vectorised over both argument `x` (input for microorganisms) and `ab` (input for antibiotics).
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#'
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#' All output [will be translated][translate] where possible.
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#'
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#' The function [mo_url()] will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.
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#'
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#' SNOMED codes - [mo_snomed()] - are from the version of `r documentation_date(TAXONOMY_VERSION$SNOMED$accessed_date)`. See *Source* and the [microorganisms] data set for more info.
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#' SNOMED codes ([mo_snomed()]) are from the version of `r documentation_date(TAXONOMY_VERSION$SNOMED$accessed_date)`. See *Source* and the [microorganisms] data set for more info.
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#'
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#' Old taxonomic names (so-called 'synonyms') can be retrieved with [mo_synonyms()], the current taxonomic name can be retrieved with [mo_current()]. Both functions return full names.
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#' @inheritSection mo_matching_score Matching Score for Microorganisms
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@ -64,6 +66,7 @@
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#' @name mo_property
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#' @return
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#' - An [integer] in case of [mo_year()]
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#' - An [ordered factor][factor] in case of [mo_pathogenicity()]
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#' - A [list] in case of [mo_taxonomy()], [mo_synonyms()] and [mo_info()]
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#' - A named [character] in case of [mo_url()]
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#' - A [numeric] in case of [mo_snomed()]
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@ -73,6 +76,7 @@
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#' @inheritSection AMR Reference Data Publicly Available
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#' @examples
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#' # taxonomic tree -----------------------------------------------------------
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#'
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#' mo_kingdom("Klebsiella pneumoniae")
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#' mo_phylum("Klebsiella pneumoniae")
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#' mo_class("Klebsiella pneumoniae")
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@ -82,27 +86,37 @@
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#' mo_species("Klebsiella pneumoniae")
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#' mo_subspecies("Klebsiella pneumoniae")
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#'
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#' # colloquial properties ----------------------------------------------------
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#'
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#' # full names and short names -----------------------------------------------
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#'
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#' mo_name("Klebsiella pneumoniae")
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#' mo_fullname("Klebsiella pneumoniae")
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#' mo_shortname("Klebsiella pneumoniae")
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#'
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#'
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#' # other properties ---------------------------------------------------------
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#'
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#' mo_pathogenicity("Klebsiella pneumoniae")
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#' mo_gramstain("Klebsiella pneumoniae")
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#' mo_snomed("Klebsiella pneumoniae")
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#' mo_type("Klebsiella pneumoniae")
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#' mo_rank("Klebsiella pneumoniae")
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#' mo_url("Klebsiella pneumoniae")
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#' mo_synonyms("Klebsiella pneumoniae")
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#' mo_is_yeast(c("Candida", "Trichophyton", "Klebsiella"))
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#'
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#'
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#' # scientific reference -----------------------------------------------------
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#'
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#' mo_ref("Klebsiella pneumoniae")
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#' mo_authors("Klebsiella pneumoniae")
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#' mo_year("Klebsiella pneumoniae")
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#' mo_lpsn("Klebsiella pneumoniae")
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#' mo_gbif("Klebsiella pneumoniae")
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#' mo_synonyms("Klebsiella pneumoniae")
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#'
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#'
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#' # abbreviations known in the field -----------------------------------------
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#'
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#' mo_genus("MRSA")
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#' mo_species("MRSA")
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#' mo_shortname("VISA")
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@ -111,18 +125,24 @@
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#' mo_genus("EHEC")
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#' mo_species("EHEC")
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#'
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#'
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#' # known subspecies ---------------------------------------------------------
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#'
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#' mo_fullname("K. pneu rh")
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#' mo_shortname("K. pneu rh")
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#'
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#'
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#' \donttest{
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#' # Becker classification, see ?as.mo ----------------------------------------
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#'
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#' mo_fullname("Staph. epidermidis")
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#' mo_fullname("Staph. epidermidis", Becker = TRUE)
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#' mo_shortname("Staph. epidermidis")
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#' mo_shortname("Staph. epidermidis", Becker = TRUE)
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#'
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#'
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#' # Lancefield classification, see ?as.mo ------------------------------------
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#'
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#' mo_fullname("S. pyo")
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#' mo_fullname("S. pyo", Lancefield = TRUE)
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#' mo_shortname("S. pyo")
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@ -130,6 +150,7 @@
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#'
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#'
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#' # language support --------------------------------------------------------
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#'
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#' mo_gramstain("Klebsiella pneumoniae", language = "de") # German
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#' mo_gramstain("Klebsiella pneumoniae", language = "nl") # Dutch
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#' mo_gramstain("Klebsiella pneumoniae", language = "es") # Spanish
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@ -148,8 +169,6 @@
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#'
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#' # other --------------------------------------------------------------------
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#'
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#' mo_is_yeast(c("Candida", "Trichophyton", "Klebsiella"))
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#'
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#' # gram stains and intrinsic resistance can be used as a filter in dplyr verbs
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#' if (require("dplyr")) {
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#' example_isolates %>%
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@ -162,7 +181,6 @@
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#' count(mo_genus(), sort = TRUE)
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#' }
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#'
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#'
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#' # get a list with the complete taxonomy (from kingdom to subspecies)
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#' mo_taxonomy("Klebsiella pneumoniae")
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#'
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@ -386,6 +404,40 @@ mo_status <- function(x, language = get_AMR_locale(), keep_synonyms = getOption(
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translate_into_language(mo_validate(x = x, property = "status", language = language, keep_synonyms = keep_synonyms, ...), language = language, only_unknown = TRUE)
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}
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#' @rdname mo_property
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#' @export
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mo_pathogenicity <- function(x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ...) {
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if (missing(x)) {
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# this tries to find the data and an 'mo' column
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x <- find_mo_col(fn = "mo_pathogenicity")
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}
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meet_criteria(x, allow_NA = TRUE)
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language <- validate_language(language)
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meet_criteria(keep_synonyms, allow_class = "logical", has_length = 1)
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x.mo <- as.mo(x, language = language, keep_synonyms = keep_synonyms, ...)
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metadata <- get_mo_uncertainties()
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prev <- AMR_env$MO_lookup$prevalence[match(x.mo, AMR_env$MO_lookup$mo)]
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kngd <- AMR_env$MO_lookup$kingdom[match(x.mo, AMR_env$MO_lookup$mo)]
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rank <- AMR_env$MO_lookup$rank[match(x.mo, AMR_env$MO_lookup$mo)]
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out <- factor(ifelse(prev == 1 & kngd == "Bacteria" & rank != "genus",
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"Pathogenic",
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ifelse(prev < 2 & kngd == "Fungi",
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"Potentially pathogenic",
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ifelse(prev == 2 & kngd == "Bacteria",
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"Non-pathogenic",
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ifelse(kngd == "Bacteria",
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"Potentially pathogenic",
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"Unknown")))),
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levels = c("Pathogenic", "Potentially pathogenic", "Non-pathogenic", "Unknown"),
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ordered = TRUE)
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load_mo_uncertainties(metadata)
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out
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}
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#' @rdname mo_property
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#' @export
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mo_gramstain <- function(x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ...) {
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@ -102,6 +102,9 @@ expect_equal(names(mo_info("Escherichia coli")), c(
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))
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expect_inherits(mo_info(c("Escherichia coli", "Staphylococcus aureus")), "list")
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expect_equal(as.character(table(mo_pathogenicity(example_isolates$mo)))
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c("1561", "422", "1", "16"))
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expect_equal(mo_ref("Escherichia coli"), "Castellani et al., 1919")
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expect_equal(mo_authors("Escherichia coli"), "Castellani et al.")
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expect_equal(mo_year("Escherichia coli"), 1919)
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\alias{mo_domain}
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\alias{mo_type}
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\alias{mo_status}
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\alias{mo_pathogenicity}
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\alias{mo_gramstain}
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\alias{mo_is_gram_negative}
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\alias{mo_is_gram_positive}
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@ -133,6 +134,13 @@ mo_status(
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...
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)
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mo_pathogenicity(
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x,
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language = get_AMR_locale(),
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keep_synonyms = getOption("AMR_keep_synonyms", FALSE),
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...
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)
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mo_gramstain(
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x,
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language = get_AMR_locale(),
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@ -275,6 +283,7 @@ mo_property(
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\value{
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\itemize{
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\item An \link{integer} in case of \code{\link[=mo_year]{mo_year()}}
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\item An \link[=factor]{ordered factor} in case of \code{\link[=mo_pathogenicity]{mo_pathogenicity()}}
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\item A \link{list} in case of \code{\link[=mo_taxonomy]{mo_taxonomy()}}, \code{\link[=mo_synonyms]{mo_synonyms()}} and \code{\link[=mo_info]{mo_info()}}
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\item A named \link{character} in case of \code{\link[=mo_url]{mo_url()}}
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\item A \link{numeric} in case of \code{\link[=mo_snomed]{mo_snomed()}}
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@ -296,17 +305,19 @@ The short name - \code{\link[=mo_shortname]{mo_shortname()}} - almost always ret
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Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions \code{\link[=mo_kingdom]{mo_kingdom()}} and \code{\link[=mo_domain]{mo_domain()}} return the exact same results.
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Determination of the Gram stain - \code{\link[=mo_gramstain]{mo_gramstain()}} - will be based on the taxonomic kingdom and phylum. Originally, Cavalier-Smith defined the so-called subkingdoms Negibacteria and Posibacteria (2002, \href{https://pubmed.ncbi.nlm.nih.gov/11837318/}{PMID 11837318}), and only considered these phyla as Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes. These phyla were renamed to Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota (2021, \href{https://pubmed.ncbi.nlm.nih.gov/34694987/}{PMID 34694987}). Bacteria in these phyla are considered Gram-positive in this \code{AMR} package, except for members of the class Negativicutes (within phylum Bacillota) which are Gram-negative. All other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value \code{NA}. Functions \code{\link[=mo_is_gram_negative]{mo_is_gram_negative()}} and \code{\link[=mo_is_gram_positive]{mo_is_gram_positive()}} always return \code{TRUE} or \code{FALSE} (or \code{NA} when the input is \code{NA} or the MO code is \code{UNKNOWN}), thus always return \code{FALSE} for species outside the taxonomic kingdom of Bacteria.
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Determination of human pathogenicity (\code{\link[=mo_pathogenicity]{mo_pathogenicity()}}) is strongly based on Bartlett \emph{et al.} (2022, \doi{10.1099/mic.0.001269}). This function returns a \link{factor} with the levels \emph{Pathogenic}, \emph{Potentially pathogenic}, \emph{Non-pathogenic}, and \emph{Unknown}.
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Determination of yeasts - \code{\link[=mo_is_yeast]{mo_is_yeast()}} - will be based on the taxonomic kingdom and class. \emph{Budding yeasts} are fungi of the phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes). \emph{True yeasts} are aggregated into the underlying order Saccharomycetales. Thus, for all microorganisms that are member of the taxonomic class Saccharomycetes, the function will return \code{TRUE}. It returns \code{FALSE} otherwise (or \code{NA} when the input is \code{NA} or the MO code is \code{UNKNOWN}).
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Determination of the Gram stain (\code{\link[=mo_gramstain]{mo_gramstain()}}) will be based on the taxonomic kingdom and phylum. Originally, Cavalier-Smith defined the so-called subkingdoms Negibacteria and Posibacteria (2002, \href{https://pubmed.ncbi.nlm.nih.gov/11837318/}{PMID 11837318}), and only considered these phyla as Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes. These phyla were renamed to Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota (2021, \href{https://pubmed.ncbi.nlm.nih.gov/34694987/}{PMID 34694987}). Bacteria in these phyla are considered Gram-positive in this \code{AMR} package, except for members of the class Negativicutes (within phylum Bacillota) which are Gram-negative. All other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value \code{NA}. Functions \code{\link[=mo_is_gram_negative]{mo_is_gram_negative()}} and \code{\link[=mo_is_gram_positive]{mo_is_gram_positive()}} always return \code{TRUE} or \code{FALSE} (or \code{NA} when the input is \code{NA} or the MO code is \code{UNKNOWN}), thus always return \code{FALSE} for species outside the taxonomic kingdom of Bacteria.
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Determination of intrinsic resistance - \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} - will be based on the \link{intrinsic_resistant} data set, which is based on \href{https://www.eucast.org/expert_rules_and_expected_phenotypes/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021). The \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} function can be vectorised over both argument \code{x} (input for microorganisms) and \code{ab} (input for antibiotics).
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Determination of yeasts (\code{\link[=mo_is_yeast]{mo_is_yeast()}}) will be based on the taxonomic kingdom and class. \emph{Budding yeasts} are fungi of the phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes). \emph{True yeasts} are aggregated into the underlying order Saccharomycetales. Thus, for all microorganisms that are member of the taxonomic class Saccharomycetes, the function will return \code{TRUE}. It returns \code{FALSE} otherwise (or \code{NA} when the input is \code{NA} or the MO code is \code{UNKNOWN}).
|
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|
||||
Determination of intrinsic resistance (\code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}}) will be based on the \link{intrinsic_resistant} data set, which is based on \href{https://www.eucast.org/expert_rules_and_expected_phenotypes/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021). The \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} function can be vectorised over both argument \code{x} (input for microorganisms) and \code{ab} (input for antibiotics).
|
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|
||||
All output \link[=translate]{will be translated} where possible.
|
||||
|
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The function \code{\link[=mo_url]{mo_url()}} will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.
|
||||
|
||||
SNOMED codes - \code{\link[=mo_snomed]{mo_snomed()}} - are from the version of 1 July, 2021. See \emph{Source} and the \link{microorganisms} data set for more info.
|
||||
SNOMED codes (\code{\link[=mo_snomed]{mo_snomed()}}) are from the version of 1 July, 2021. See \emph{Source} and the \link{microorganisms} data set for more info.
|
||||
|
||||
Old taxonomic names (so-called 'synonyms') can be retrieved with \code{\link[=mo_synonyms]{mo_synonyms()}}, the current taxonomic name can be retrieved with \code{\link[=mo_current]{mo_current()}}. Both functions return full names.
|
||||
}
|
||||
|
|
@ -369,6 +380,7 @@ All data sets in this \code{AMR} package (about microorganisms, antibiotics, R/S
|
|||
|
||||
\examples{
|
||||
# taxonomic tree -----------------------------------------------------------
|
||||
|
||||
mo_kingdom("Klebsiella pneumoniae")
|
||||
mo_phylum("Klebsiella pneumoniae")
|
||||
mo_class("Klebsiella pneumoniae")
|
||||
|
|
@ -378,27 +390,37 @@ mo_genus("Klebsiella pneumoniae")
|
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mo_species("Klebsiella pneumoniae")
|
||||
mo_subspecies("Klebsiella pneumoniae")
|
||||
|
||||
# colloquial properties ----------------------------------------------------
|
||||
|
||||
# full names and short names -----------------------------------------------
|
||||
|
||||
mo_name("Klebsiella pneumoniae")
|
||||
mo_fullname("Klebsiella pneumoniae")
|
||||
mo_shortname("Klebsiella pneumoniae")
|
||||
|
||||
|
||||
# other properties ---------------------------------------------------------
|
||||
|
||||
mo_pathogenicity("Klebsiella pneumoniae")
|
||||
mo_gramstain("Klebsiella pneumoniae")
|
||||
mo_snomed("Klebsiella pneumoniae")
|
||||
mo_type("Klebsiella pneumoniae")
|
||||
mo_rank("Klebsiella pneumoniae")
|
||||
mo_url("Klebsiella pneumoniae")
|
||||
mo_synonyms("Klebsiella pneumoniae")
|
||||
mo_is_yeast(c("Candida", "Trichophyton", "Klebsiella"))
|
||||
|
||||
|
||||
# scientific reference -----------------------------------------------------
|
||||
|
||||
mo_ref("Klebsiella pneumoniae")
|
||||
mo_authors("Klebsiella pneumoniae")
|
||||
mo_year("Klebsiella pneumoniae")
|
||||
mo_lpsn("Klebsiella pneumoniae")
|
||||
mo_gbif("Klebsiella pneumoniae")
|
||||
mo_synonyms("Klebsiella pneumoniae")
|
||||
|
||||
|
||||
# abbreviations known in the field -----------------------------------------
|
||||
|
||||
mo_genus("MRSA")
|
||||
mo_species("MRSA")
|
||||
mo_shortname("VISA")
|
||||
|
|
@ -407,18 +429,24 @@ mo_gramstain("VISA")
|
|||
mo_genus("EHEC")
|
||||
mo_species("EHEC")
|
||||
|
||||
|
||||
# known subspecies ---------------------------------------------------------
|
||||
|
||||
mo_fullname("K. pneu rh")
|
||||
mo_shortname("K. pneu rh")
|
||||
|
||||
|
||||
\donttest{
|
||||
# Becker classification, see ?as.mo ----------------------------------------
|
||||
|
||||
mo_fullname("Staph. epidermidis")
|
||||
mo_fullname("Staph. epidermidis", Becker = TRUE)
|
||||
mo_shortname("Staph. epidermidis")
|
||||
mo_shortname("Staph. epidermidis", Becker = TRUE)
|
||||
|
||||
|
||||
# Lancefield classification, see ?as.mo ------------------------------------
|
||||
|
||||
mo_fullname("S. pyo")
|
||||
mo_fullname("S. pyo", Lancefield = TRUE)
|
||||
mo_shortname("S. pyo")
|
||||
|
|
@ -426,6 +454,7 @@ mo_shortname("S. pyo", Lancefield = TRUE)
|
|||
|
||||
|
||||
# language support --------------------------------------------------------
|
||||
|
||||
mo_gramstain("Klebsiella pneumoniae", language = "de") # German
|
||||
mo_gramstain("Klebsiella pneumoniae", language = "nl") # Dutch
|
||||
mo_gramstain("Klebsiella pneumoniae", language = "es") # Spanish
|
||||
|
|
@ -444,8 +473,6 @@ mo_fullname("S. pyogenes", Lancefield = TRUE, language = "uk")
|
|||
|
||||
# other --------------------------------------------------------------------
|
||||
|
||||
mo_is_yeast(c("Candida", "Trichophyton", "Klebsiella"))
|
||||
|
||||
# gram stains and intrinsic resistance can be used as a filter in dplyr verbs
|
||||
if (require("dplyr")) {
|
||||
example_isolates \%>\%
|
||||
|
|
@ -458,7 +485,6 @@ if (require("dplyr")) {
|
|||
count(mo_genus(), sort = TRUE)
|
||||
}
|
||||
|
||||
|
||||
# get a list with the complete taxonomy (from kingdom to subspecies)
|
||||
mo_taxonomy("Klebsiella pneumoniae")
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue