% Generated by roxygen2: do not edit by hand % Please edit documentation in R/mo_property.R \name{mo_property} \alias{mo_property} \alias{mo_name} \alias{mo_fullname} \alias{mo_shortname} \alias{mo_subspecies} \alias{mo_species} \alias{mo_genus} \alias{mo_family} \alias{mo_order} \alias{mo_class} \alias{mo_phylum} \alias{mo_kingdom} \alias{mo_domain} \alias{mo_type} \alias{mo_status} \alias{mo_gramstain} \alias{mo_is_gram_negative} \alias{mo_is_gram_positive} \alias{mo_is_yeast} \alias{mo_is_intrinsic_resistant} \alias{mo_snomed} \alias{mo_ref} \alias{mo_authors} \alias{mo_year} \alias{mo_lpsn} \alias{mo_gbif} \alias{mo_rank} \alias{mo_taxonomy} \alias{mo_synonyms} \alias{mo_current} \alias{mo_info} \alias{mo_url} \title{Get Properties of a Microorganism} \usage{ mo_name( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_fullname( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_shortname( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_subspecies( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_species( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_genus( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_family( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_order( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_class( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_phylum( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_kingdom( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_domain( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_type( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_status( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_gramstain( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_is_gram_negative( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_is_gram_positive( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_is_yeast( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_is_intrinsic_resistant( x, ab, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_snomed( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_ref( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_authors( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_year( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_lpsn( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_gbif( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_rank( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_taxonomy( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_synonyms( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_current(x, language = get_AMR_locale(), ...) mo_info( x, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_url( x, open = FALSE, language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) mo_property( x, property = "fullname", language = get_AMR_locale(), keep_synonyms = getOption("AMR_keep_synonyms", FALSE), ... ) } \arguments{ \item{x}{any \link{character} (vector) that can be coerced to a valid microorganism code with \code{\link[=as.mo]{as.mo()}}. Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, see \emph{Examples}.} \item{language}{language to translate text like "no growth", which defaults to the system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}})} \item{keep_synonyms}{a \link{logical} to indicate if old, previously valid taxonomic names must be preserved and not be corrected to currently accepted names. The default is \code{FALSE}, which will return a note if old taxonomic names were processed. The default can be set with \code{options(AMR_keep_synonyms = TRUE)} or \code{options(AMR_keep_synonyms = FALSE)}.} \item{...}{other arguments passed on to \code{\link[=as.mo]{as.mo()}}, such as 'minimum_matching_score', 'ignore_pattern', and 'remove_from_input'} \item{ab}{any (vector of) text that can be coerced to a valid antibiotic drug code with \code{\link[=as.ab]{as.ab()}}} \item{open}{browse the URL using \code{\link[utils:browseURL]{browseURL()}}} \item{property}{one of the column names of the \link{microorganisms} data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence" or "snomed", or must be \code{"shortname"}} } \value{ \itemize{ \item An \link{integer} in case of \code{\link[=mo_year]{mo_year()}} \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()}} \item A named \link{character} in case of \code{\link[=mo_url]{mo_url()}} \item A \link{numeric} in case of \code{\link[=mo_snomed]{mo_snomed()}} \item A \link{character} in all other cases } } \description{ Use these functions to return a specific property of a microorganism based on the latest accepted taxonomy. All input values will be evaluated internally with \code{\link[=as.mo]{as.mo()}}, which makes it possible to use microbial abbreviations, codes and names as input. See \emph{Examples}. } \details{ All functions will, at default, keep old taxonomic properties. Please refer to this example, knowing that \emph{Escherichia blattae} was renamed to \emph{Shimwellia blattae} in 2010: \itemize{ \item \code{mo_name("Escherichia blattae")} will return \code{"Shimwellia blattae"} (with a note about the renaming) \item \code{mo_ref("Escherichia blattae", keep_synonyms = TRUE)} will return \code{"Burgess et al., 1973"} (without a note) \item \code{mo_ref("Shimwellia blattae", keep_synonyms = FALSE)} will return \code{"Priest et al., 2010"} (without a note) } The short name - \code{\link[=mo_shortname]{mo_shortname()}} - almost always returns the first character of the genus and the full species, like \code{"E. coli"}. Exceptions are abbreviations of staphylococci (such as \emph{"CoNS"}, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as \emph{"GBS"}, Group B Streptococci). Please bear in mind that e.g. \emph{E. coli} could mean \emph{Escherichia coli} (kingdom of Bacteria) as well as \emph{Entamoeba coli} (kingdom of Protozoa). Returning to the full name will be done using \code{\link[=as.mo]{as.mo()}} internally, giving priority to bacteria and human pathogens, i.e. \code{"E. coli"} will be considered \emph{Escherichia coli}. In other words, \code{mo_fullname(mo_shortname("Entamoeba coli"))} returns \code{"Escherichia coli"}. 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. 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. 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}). 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). All output \link[=translate]{will be translated} where possible. 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. 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. } \section{Matching Score for Microorganisms}{ With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as: \ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{\ifelse{html}{\figure{mo_matching_score.png}{options: width="300" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}} where: \itemize{ \item \ifelse{html}{\out{x is the user input;}}{\eqn{x} is the user input;} \item \ifelse{html}{\out{n is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);} \item \ifelse{html}{\out{ln is the length of n;}}{l_n is the length of \eqn{n};} \item \ifelse{html}{\out{lev is the Levenshtein distance function (counting any insertion as 1, and any deletion or substitution as 2) that is needed to change x into n;}}{lev is the Levenshtein distance function (counting any insertion as 1, and any deletion or substitution as 2) that is needed to change \eqn{x} into \eqn{n};} \item \ifelse{html}{\out{pn is the human pathogenic prevalence group of n, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;} \item \ifelse{html}{\out{kn is the taxonomic kingdom of n, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.} } The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence: \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acanthamoeba}, \emph{Acholeplasma}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Aedes}, \emph{Alistipes}, \emph{Alloprevotella}, \emph{Alternaria}, \emph{Amoeba}, \emph{Anaerosalibacter}, \emph{Ancylostoma}, \emph{Angiostrongylus}, \emph{Anisakis}, \emph{Anopheles}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Bergeyella}, \emph{Blastocystis}, \emph{Blastomyces}, \emph{Borrelia}, \emph{Brachyspira}, \emph{Branhamella}, \emph{Butyricimonas}, \emph{Candida}, \emph{Capillaria}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Cetobacterium}, \emph{Chaetomium}, \emph{Chlamydia}, \emph{Chlamydophila}, \emph{Chryseobacterium}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Contracaecum}, \emph{Cordylobia}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Deinococcus}, \emph{Demodex}, \emph{Dermatobia}, \emph{Dientamoeba}, \emph{Diphyllobothrium}, \emph{Dirofilaria}, \emph{Dysgonomonas}, \emph{Echinostoma}, \emph{Elizabethkingia}, \emph{Empedobacter}, \emph{Entamoeba}, \emph{Enterobius}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Fasciola}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Giardia}, \emph{Haloarcula}, \emph{Halobacterium}, \emph{Halococcus}, \emph{Hendersonula}, \emph{Heterophyes}, \emph{Histomonas}, \emph{Histoplasma}, \emph{Hymenolepis}, \emph{Hypomyces}, \emph{Hysterothylacium}, \emph{Leishmania}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Lucilia}, \emph{Lumbricus}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Metagonimus}, \emph{Meyerozyma}, \emph{Microsporidium}, \emph{Microsporum}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Myroides}, \emph{Necator}, \emph{Nectria}, \emph{Ochroconis}, \emph{Odoribacter}, \emph{Oesophagostomum}, \emph{Oidiodendron}, \emph{Opisthorchis}, \emph{Ornithobacterium}, \emph{Parabacteroides}, \emph{Pediculus}, \emph{Pedobacter}, \emph{Phlebotomus}, \emph{Phocaeicola}, \emph{Phocanema}, \emph{Phoma}, \emph{Pichia}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Pneumocystis}, \emph{Porphyromonas}, \emph{Prevotella}, \emph{Pseudallescheria}, \emph{Pseudoterranova}, \emph{Pulex}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Riemerella}, \emph{Saccharomyces}, \emph{Sarcoptes}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium}, \emph{Sphingobacterium}, \emph{Spirometra}, \emph{Spiroplasma}, \emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Streptobacillus}, \emph{Strongyloides}, \emph{Syngamus}, \emph{Taenia}, \emph{Tannerella}, \emph{Tenacibaculum}, \emph{Terrimonas}, \emph{Toxocara}, \emph{Treponema}, \emph{Trichinella}, \emph{Trichobilharzia}, \emph{Trichoderma}, \emph{Trichomonas}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Trichostrongylus}, \emph{Trichuris}, \emph{Tritirachium}, \emph{Trombicula}, \emph{Trypanosoma}, \emph{Tunga}, \emph{Ureaplasma}, \emph{Victivallis}, \emph{Wautersiella}, \emph{Weeksella} or \emph{Wuchereria}. \strong{Group 3} consists of all other microorganisms. All characters in \eqn{x} and \eqn{n} are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses. All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.688}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.079}, a less prevalent microorganism in humans), although the latter would alphabetically come first. } \section{Source}{ \enumerate{ \item Berends MS \emph{et al.} (2022). \strong{AMR: An R Package for Working with Antimicrobial Resistance Data}. \emph{Journal of Statistical Software}, 104(3), 1-31; \doi{10.18637/jss.v104.i03} \item Becker K \emph{et al.} (2014). \strong{Coagulase-Negative Staphylococci.} \emph{Clin Microbiol Rev.} 27(4): 870-926; \doi{10.1128/CMR.00109-13} \item Becker K \emph{et al.} (2019). \strong{Implications of identifying the recently defined members of the \emph{S. aureus} complex, \emph{S. argenteus} and \emph{S. schweitzeri}: A position paper of members of the ESCMID Study Group for staphylococci and Staphylococcal Diseases (ESGS).} \emph{Clin Microbiol Infect}; \doi{10.1016/j.cmi.2019.02.028} \item Becker K \emph{et al.} (2020). \strong{Emergence of coagulase-negative staphylococci} \emph{Expert Rev Anti Infect Ther.} 18(4):349-366; \doi{10.1080/14787210.2020.1730813} \item Lancefield RC (1933). \strong{A serological differentiation of human and other groups of hemolytic streptococci}. \emph{J Exp Med.} 57(4): 571-95; \doi{10.1084/jem.57.4.571} \item Berends MS \emph{et al.} (2022). \strong{Trends in Occurrence and Phenotypic Resistance of Coagulase-Negative Staphylococci (CoNS) Found in Human Blood in the Northern Netherlands between 2013 and 2019} \emph{Microorganisms} 10(9), 1801; \doi{10.3390/microorganisms10091801} \item Parte, AC \emph{et al.} (2020). \strong{List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ.} International Journal of Systematic and Evolutionary Microbiology, 70, 5607-5612; \doi{10.1099/ijsem.0.004332}. Accessed from \url{https://lpsn.dsmz.de} on 12 September, 2022. \item GBIF Secretariat (November 26, 2021). GBIF Backbone Taxonomy. Checklist dataset \doi{10.15468/39omei}. Accessed from \url{https://www.gbif.org} on 12 September, 2022. \item Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS). US Edition of SNOMED CT from 1 September 2020. Value Set Name 'Microoganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: \url{https://phinvads.cdc.gov} } } \section{Reference Data Publicly Available}{ All data sets in this \code{AMR} package (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit \href{https://msberends.github.io/AMR/articles/datasets.html}{our website for the download links}. The actual files are of course available on \href{https://github.com/msberends/AMR/tree/main/data-raw}{our GitHub repository}. } \examples{ # taxonomic tree ----------------------------------------------------------- mo_kingdom("Klebsiella pneumoniae") mo_phylum("Klebsiella pneumoniae") mo_class("Klebsiella pneumoniae") mo_order("Klebsiella pneumoniae") mo_family("Klebsiella pneumoniae") mo_genus("Klebsiella pneumoniae") mo_species("Klebsiella pneumoniae") mo_subspecies("Klebsiella pneumoniae") # colloquial properties ---------------------------------------------------- mo_name("Klebsiella pneumoniae") mo_fullname("Klebsiella pneumoniae") mo_shortname("Klebsiella pneumoniae") # other properties --------------------------------------------------------- mo_gramstain("Klebsiella pneumoniae") mo_snomed("Klebsiella pneumoniae") mo_type("Klebsiella pneumoniae") mo_rank("Klebsiella pneumoniae") mo_url("Klebsiella pneumoniae") mo_synonyms("Klebsiella pneumoniae") # scientific reference ----------------------------------------------------- mo_ref("Klebsiella pneumoniae") mo_authors("Klebsiella pneumoniae") mo_year("Klebsiella pneumoniae") mo_lpsn("Klebsiella pneumoniae") mo_gbif("Klebsiella pneumoniae") # abbreviations known in the field ----------------------------------------- mo_genus("MRSA") mo_species("MRSA") mo_shortname("VISA") 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") 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 mo_gramstain("Klebsiella pneumoniae", language = "el") # Greek mo_gramstain("Klebsiella pneumoniae", language = "uk") # Ukrainian # mo_type is equal to mo_kingdom, but mo_kingdom will remain official mo_kingdom("Klebsiella pneumoniae") mo_type("Klebsiella pneumoniae") mo_kingdom("Klebsiella pneumoniae", language = "zh") # Chinese, no effect mo_type("Klebsiella pneumoniae", language = "zh") # Chinese, translated mo_fullname("S. pyogenes", Lancefield = TRUE, language = "de") 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 \%>\% filter(mo_is_gram_positive()) \%>\% count(mo_genus(), sort = TRUE) } if (require("dplyr")) { example_isolates \%>\% filter(mo_is_intrinsic_resistant(ab = "vanco")) \%>\% count(mo_genus(), sort = TRUE) } # get a list with the complete taxonomy (from kingdom to subspecies) mo_taxonomy("Klebsiella pneumoniae") # get a list with the taxonomy, the authors, Gram-stain, # SNOMED codes, and URL to the online database mo_info("Klebsiella pneumoniae") } } \seealso{ Data set \link{microorganisms} }