mirror of https://github.com/msberends/AMR.git
209 lines
13 KiB
R
209 lines
13 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/mo.R
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\name{as.mo}
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\alias{as.mo}
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\alias{mo}
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\alias{is.mo}
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\alias{mo_failures}
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\alias{mo_uncertainties}
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\alias{mo_renamed}
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\title{Transform to microorganism ID}
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\usage{
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as.mo(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain = TRUE,
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reference_df = get_mo_source())
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is.mo(x)
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mo_failures()
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mo_uncertainties()
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mo_renamed()
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}
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\arguments{
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\item{x}{a character vector or a \code{data.frame} with one or two columns}
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\item{Becker}{a logical to indicate whether \emph{Staphylococci} should be categorised into Coagulase Negative \emph{Staphylococci} ("CoNS") and Coagulase Positive \emph{Staphylococci} ("CoPS") instead of their own species, according to Karsten Becker \emph{et al.} [1].
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This excludes \emph{Staphylococcus aureus} at default, use \code{Becker = "all"} to also categorise \emph{S. aureus} as "CoPS".}
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\item{Lancefield}{a logical to indicate whether beta-haemolytic \emph{Streptococci} should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield [2]. These \emph{Streptococci} will be categorised in their first group, e.g. \emph{Streptococcus dysgalactiae} will be group C, although officially it was also categorised into groups G and L.
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This excludes \emph{Enterococci} at default (who are in group D), use \code{Lancefield = "all"} to also categorise all \emph{Enterococci} as group D.}
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\item{allow_uncertain}{a logical to indicate whether the input should be checked for less possible results, see Details}
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\item{reference_df}{a \code{data.frame} to use for extra reference when translating \code{x} to a valid \code{mo}. See \code{\link{set_mo_source}} and \code{\link{get_mo_source}} to automate the usage of your own codes (e.g. used in your analysis or organisation).}
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}
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\value{
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Character (vector) with class \code{"mo"}. Unknown values will return \code{NA}.
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}
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\description{
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Use this function to determine a valid microorganism ID (\code{mo}). Determination is done using Artificial Intelligence (AI) and the complete taxonomic kingdoms \emph{Bacteria}, \emph{Fungi} and \emph{Protozoa} (see Source), so the input can be almost anything: a full name (like \code{"Staphylococcus aureus"}), an abbreviated name (like \code{"S. aureus"}), an abbreviation known in the field (like \code{"MRSA"}), or just a genus. You could also \code{\link{select}} a genus and species column, zie Examples.
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}
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\details{
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A microbial ID from this package (class: \code{mo}) typically looks like these examples:\cr
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\preformatted{
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Code Full name
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--------------- --------------------------------------
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B_KLBSL Klebsiella
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B_KLBSL_PNE Klebsiella pneumoniae
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B_KLBSL_PNE_RHI Klebsiella pneumoniae rhinoscleromatis
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| | | |
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| | | |
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| | | ----> subspecies, a 3-4 letter acronym
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| | ----> species, a 3-4 letter acronym
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| ----> genus, a 5-7 letter acronym, mostly without vowels
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----> taxonomic kingdom: A (Archaea), B (Bacteria), C (Chromista),
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F (Fungi), P (Protozoa) or V (Viruses)
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}
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Use the \code{\link{mo_property}} functions to get properties based on the returned code, see Examples.
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This function uses Artificial Intelligence (AI) to help getting fast and logical results. It tries to find matches in this order:
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\itemize{
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\item{Taxonomic kingdom: it first searches in Bacteria, then Fungi, then Protozoa}
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\item{Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones (see section \emph{Microbial prevalence of pathogens in humans})}
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\item{Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations}
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\item{Breakdown of input values: from here it starts to breakdown input values to find possible matches}
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}
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A couple of effects because of these rules:
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\itemize{
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\item{\code{"E. coli"} will return the ID of \emph{Escherichia coli} and not \emph{Entamoeba coli}, although the latter would alphabetically come first}
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\item{\code{"H. influenzae"} will return the ID of \emph{Haemophilus influenzae} and not \emph{Haematobacter influenzae} for the same reason}
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\item{Something like \code{"p aer"} will return the ID of \emph{Pseudomonas aeruginosa} and not \emph{Pasteurella aerogenes}}
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\item{Something like \code{"stau"} or \code{"S aur"} will return the ID of \emph{Staphylococcus aureus} and not \emph{Staphylococcus auricularis}}
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}
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This means that looking up human pathogenic microorganisms takes less time than looking up human \strong{non}-pathogenic microorganisms.
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\strong{UNCERTAIN RESULTS} \cr
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When using \code{allow_uncertain = TRUE} (which is the default setting), it will use additional rules if all previous AI rules failed to get valid results. These are:
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\itemize{
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\item{It tries to look for previously accepted (but now invalid) taxonomic names}
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\item{It strips off values between brackets and the brackets itself, and re-evaluates the input with all previous rules}
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\item{It strips off words from the end one by one and re-evaluates the input with all previous rules}
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\item{It strips off words from the start one by one and re-evaluates the input with all previous rules}
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\item{It tries to look for some manual changes which are not yet published to the Catalogue of Life (like \emph{Propionibacterium} not yet being \emph{Cutibacterium})}
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}
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Examples:
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\itemize{
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\item{\code{"Streptococcus group B (known as S. agalactiae)"}. The text between brackets will be removed and a warning will be thrown that the result \emph{Streptococcus group B} (\code{B_STRPT_GRB}) needs review.}
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\item{\code{"S. aureus - please mind: MRSA"}. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result \emph{Staphylococcus aureus} (\code{B_STPHY_AUR}) needs review.}
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\item{\code{"Fluoroquinolone-resistant Neisseria gonorrhoeae"}. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result \emph{Neisseria gonorrhoeae} (\code{B_NESSR_GON}) needs review.}
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}
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Use \code{mo_failures()} to get a vector with all values that could not be coerced to a valid value.
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Use \code{mo_uncertainties()} to get a vector with all values that were coerced to a valid value, but with uncertainty.
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Use \code{mo_renamed()} to get a vector with all values that could be coerced based on an old, previously accepted taxonomic name.
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}
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\section{Microbial prevalence of pathogens in humans}{
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The artificial intelligence takes into account microbial prevalence of pathogens in humans. It uses three groups and every (sub)species is in the group it matches first. These groups are:
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\itemize{
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\item{1 (most prevalent): class is Gammaproteobacteria \strong{or} genus is one of: \emph{Enterococcus}, \emph{Staphylococcus}, \emph{Streptococcus}.}
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\item{2: phylum is one of: Proteobacteria, Firmicutes, Actinobacteria, Sarcomastigophora \strong{or} genus is one of: \emph{Aspergillus}, \emph{Bacteroides}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Chryseobacterium}, \emph{Cryptococcus}, \emph{Elisabethkingia}, \emph{Flavobacterium}, \emph{Fusobacterium}, \emph{Giardia}, \emph{Leptotrichia}, \emph{Mycoplasma}, \emph{Prevotella}, \emph{Rhodotorula}, \emph{Treponema}, \emph{Trichophyton}, \emph{Ureaplasma}.}
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\item{3 (least prevalent): all others.}
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}
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Group 1 contains all common Gram negatives, like all Enterobacteriaceae and e.g. \emph{Pseudomonas} and \emph{Legionella}.
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Group 2 probably contains all microbial pathogens ever found in humans.
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}
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\section{Source}{
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[1] Becker K \emph{et al.} \strong{Coagulase-Negative Staphylococci}. 2014. Clin Microbiol Rev. 27(4): 870–926. \url{https://dx.doi.org/10.1128/CMR.00109-13}
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[2] Lancefield RC \strong{A serological differentiation of human and other groups of hemolytic streptococci}. 1933. J Exp Med. 57(4): 571–95. \url{https://dx.doi.org/10.1084/jem.57.4.571}
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[3] Catalogue of Life: Annual Checklist (public online database), \url{www.catalogueoflife.org}.
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}
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\section{Catalogue of Life}{
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\if{html}{\figure{logo_col.png}{options: height=60px style=margin-bottom:5px} \cr}
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This package contains the complete taxonomic tree of almost all microorganisms from the authoritative and comprehensive Catalogue of Life (\url{http://www.catalogueoflife.org}). This data is updated annually - check the included version with \code{\link{catalogue_of_life_version}}.
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Included are:
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\itemize{
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\item{All ~55,000 (sub)species from the kingdoms of Archaea, Bacteria, Protozoa and Viruses}
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\item{All ~3,500 (sub)species from these orders of the kingdom of Fungi: Eurotiales, Onygenales, Pneumocystales, Saccharomycetales, Schizosaccharomycetales and Tremellales. The kingdom of Fungi is a very large taxon with almost 300,000 different (sub)species, of which most are not microbial (but rather macroscopic, like mushrooms). Because of this, not all fungi fit the scope of this package and including everything would tremendously slow down our algorithms too. By only including the aforementioned taxonomic orders, the most relevant fungi are covered (like all species of \emph{Aspergillus}, \emph{Candida}, \emph{Cryptococcus}, \emph{Histplasma}, \emph{Pneumocystis}, \emph{Saccharomyces} and \emph{Trichophyton}).}
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\item{All ~15,000 previously accepted names of included (sub)species that have been taxonomically renamed}
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\item{The complete taxonomic tree of all included (sub)species: from kingdom to subspecies}
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\item{The responsible author(s) and year of scientific publication}
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}
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The Catalogue of Life (\url{http://www.catalogueoflife.org}) is the most comprehensive and authoritative global index of species currently available. It holds essential information on the names, relationships and distributions of over 1.6 million species. The Catalogue of Life is used to support the major biodiversity and conservation information services such as the Global Biodiversity Information Facility (GBIF), Encyclopedia of Life (EoL) and the International Union for Conservation of Nature Red List. It is recognised by the Convention on Biological Diversity as a significant component of the Global Taxonomy Initiative and a contribution to Target 1 of the Global Strategy for Plant Conservation.
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The syntax used to transform the original data to a cleansed R format, can be found here: \url{https://gitlab.com/msberends/AMR/blob/master/reproduction_of_microorganisms.R}.
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}
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\section{Read more on our website!}{
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On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
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}
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\examples{
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# These examples all return "B_STPHY_AUR", the ID of S. aureus:
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as.mo("stau")
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as.mo("STAU")
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as.mo("staaur")
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as.mo("S. aureus")
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as.mo("S aureus")
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as.mo("Staphylococcus aureus")
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as.mo("Staphylococcus aureus (MRSA)")
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as.mo("MRSA") # Methicillin Resistant S. aureus
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as.mo("VISA") # Vancomycin Intermediate S. aureus
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as.mo("VRSA") # Vancomycin Resistant S. aureus
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as.mo("Streptococcus group A")
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as.mo("GAS") # Group A Streptococci
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as.mo("GBS") # Group B Streptococci
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as.mo("S. epidermidis") # will remain species: B_STPHY_EPI
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as.mo("S. epidermidis", Becker = TRUE) # will not remain species: B_STPHY_CNS
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as.mo("S. pyogenes") # will remain species: B_STRPT_PYO
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as.mo("S. pyogenes", Lancefield = TRUE) # will not remain species: B_STRPT_GRA
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# Use mo_* functions to get a specific property based on `mo`
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Ecoli <- as.mo("E. coli") # returns `B_ESCHR_COL`
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mo_genus(Ecoli) # returns "Escherichia"
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mo_gramstain(Ecoli) # returns "Gram negative"
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# but it uses as.mo internally too, so you could also just use:
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mo_genus("E. coli") # returns "Escherichia"
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\dontrun{
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df$mo <- as.mo(df$microorganism_name)
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# the select function of tidyverse is also supported:
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library(dplyr)
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df$mo <- df \%>\%
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select(microorganism_name) \%>\%
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as.mo()
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# and can even contain 2 columns, which is convenient for genus/species combinations:
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df$mo <- df \%>\%
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select(genus, species) \%>\%
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as.mo()
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# although this works easier and does the same:
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df <- df \%>\%
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mutate(mo = as.mo(paste(genus, species)))
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}
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}
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\seealso{
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\code{\link{microorganisms}} for the \code{data.frame} that is being used to determine ID's. \cr
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The \code{\link{mo_property}} functions (like \code{\link{mo_genus}}, \code{\link{mo_gramstain}}) to get properties based on the returned code.
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}
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\keyword{Becker}
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\keyword{Lancefield}
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\keyword{becker}
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\keyword{guess}
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\keyword{lancefield}
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\keyword{mo}
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