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473 lines
23 KiB
R
473 lines
23 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/mo_property.R
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\name{mo_property}
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\alias{mo_property}
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\alias{mo_name}
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\alias{mo_fullname}
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\alias{mo_shortname}
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\alias{mo_subspecies}
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\alias{mo_species}
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\alias{mo_genus}
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\alias{mo_family}
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\alias{mo_order}
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\alias{mo_class}
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\alias{mo_phylum}
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\alias{mo_kingdom}
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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_gramstain}
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\alias{mo_is_gram_negative}
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\alias{mo_is_gram_positive}
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\alias{mo_is_yeast}
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\alias{mo_is_intrinsic_resistant}
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\alias{mo_snomed}
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\alias{mo_ref}
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\alias{mo_authors}
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\alias{mo_year}
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\alias{mo_lpsn}
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\alias{mo_gbif}
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\alias{mo_rank}
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\alias{mo_taxonomy}
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\alias{mo_synonyms}
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\alias{mo_current}
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\alias{mo_info}
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\alias{mo_url}
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\title{Get Properties of a Microorganism}
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\usage{
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mo_name(
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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_fullname(
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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_shortname(
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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_subspecies(
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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_species(
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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_genus(
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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_family(
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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_order(
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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_class(
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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_phylum(
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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_kingdom(
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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_domain(
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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_type(
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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_status(
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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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keep_synonyms = getOption("AMR_keep_synonyms", FALSE),
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...
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)
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mo_is_gram_negative(
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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_is_gram_positive(
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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_is_yeast(
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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_is_intrinsic_resistant(
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x,
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ab,
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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_snomed(
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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_ref(
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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_authors(
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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_year(
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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_lpsn(
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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_gbif(
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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_rank(
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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_taxonomy(
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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_synonyms(
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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_current(x, language = get_AMR_locale(), ...)
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mo_info(
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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_url(
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x,
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open = FALSE,
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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_property(
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x,
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property = "fullname",
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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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}
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\arguments{
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\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}.}
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\item{language}{language to translate text like "no growth", which defaults to the system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}})}
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\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)}.}
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\item{...}{other arguments passed on to \code{\link[=as.mo]{as.mo()}}, such as 'minimum_matching_score', 'ignore_pattern', and 'remove_from_input'}
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\item{ab}{any (vector of) text that can be coerced to a valid antibiotic drug code with \code{\link[=as.ab]{as.ab()}}}
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\item{open}{browse the URL using \code{\link[utils:browseURL]{browseURL()}}}
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\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"}}
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}
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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 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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\item A \link{character} in all other cases
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}
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}
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\description{
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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}.
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}
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\details{
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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:
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\itemize{
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\item \code{mo_name("Escherichia blattae")} will return \code{"Shimwellia blattae"} (with a note about the renaming)
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\item \code{mo_ref("Escherichia blattae", keep_synonyms = TRUE)} will return \code{"Burgess et al., 1973"} (without a note)
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\item \code{mo_ref("Shimwellia blattae", keep_synonyms = FALSE)} will return \code{"Priest et al., 2010"} (without a note)
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}
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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"}.
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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 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.
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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.
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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.
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}
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\section{Matching Score for Microorganisms}{
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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:
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\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 )}}
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where:
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\itemize{
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\item \ifelse{html}{\out{<i>x</i> is the user input;}}{\eqn{x} is the user input;}
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\item \ifelse{html}{\out{<i>n</i> is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
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\item \ifelse{html}{\out{<i>l<sub>n</sub></i> is the length of <i>n</i>;}}{l_n is the length of \eqn{n};}
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\item \ifelse{html}{\out{<i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a> (counting any insertion as 1, and any deletion or substitution as 2) that is needed to change <i>x</i> into <i>n</i>;}}{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};}
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\item \ifelse{html}{\out{<i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
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\item \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, 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.}
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}
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The grouping into human pathogenic prevalence (\eqn{p}) is based on recent work from Bartlett \emph{et al.} (2022, \doi{10.1099/mic.0.001269}) who extensively studied medical-scientific literature to categorise all bacterial species into these groups:
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\itemize{
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\item \strong{Established}, if a taxonomic species has infected at least three persons in three or more references. These records have \code{prevalence = 1.0} in the \link{microorganisms} data set;
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\item \strong{Putative}, if a taxonomic species has fewer than three known cases. These records have \code{prevalence = 1.25} in the \link{microorganisms} data set.
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}
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Furthermore,
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\itemize{
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\item Any genus present in the \strong{established} list also has \code{prevalence = 1.0} in the \link{microorganisms} data set;
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\item Any other genus present in the \strong{putative} list has \code{prevalence = 1.25} in the \link{microorganisms} data set;
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\item Any other species or subspecies of which the genus is present in the two aforementioned groups, has \code{prevalence = 1.5} in the \link{microorganisms} data set;
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\item Any \emph{non-bacterial} genus, species or subspecies of which the genus is present in the following list, has \code{prevalence = 1.5} in the \link{microorganisms} data set: \emph{Absidia}, \emph{Acanthamoeba}, \emph{Acremonium}, \emph{Aedes}, \emph{Alternaria}, \emph{Amoeba}, \emph{Ancylostoma}, \emph{Angiostrongylus}, \emph{Anisakis}, \emph{Anopheles}, \emph{Apophysomyces}, \emph{Aspergillus}, \emph{Aureobasidium}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Blastomyces}, \emph{Candida}, \emph{Capillaria}, \emph{Chaetomium}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Contracaecum}, \emph{Cordylobia}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Demodex}, \emph{Dermatobia}, \emph{Dientamoeba}, \emph{Diphyllobothrium}, \emph{Dirofilaria}, \emph{Echinostoma}, \emph{Entamoeba}, \emph{Enterobius}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Fasciola}, \emph{Fonsecaea}, \emph{Fusarium}, \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{Malassezia}, \emph{Malbranchea}, \emph{Metagonimus}, \emph{Meyerozyma}, \emph{Microsporidium}, \emph{Microsporum}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Necator}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oesophagostomum}, \emph{Oidiodendron}, \emph{Opisthorchis}, \emph{Pediculus}, \emph{Phlebotomus}, \emph{Phoma}, \emph{Pichia}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Pneumocystis}, \emph{Pseudallescheria}, \emph{Pseudoterranova}, \emph{Pulex}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Saccharomyces}, \emph{Sarcoptes}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium}, \emph{Spirometra}, \emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Strongyloides}, \emph{Syngamus}, \emph{Taenia}, \emph{Toxocara}, \emph{Trichinella}, \emph{Trichobilharzia}, \emph{Trichoderma}, \emph{Trichomonas}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Trichostrongylus}, \emph{Trichuris}, \emph{Tritirachium}, \emph{Trombicula}, \emph{Trypanosoma}, \emph{Tunga} or \emph{Wuchereria};
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\item All other records have \code{prevalence = 2.0} in the \link{microorganisms} data set.
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}
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When calculating the matching score, all characters in \eqn{x} and \eqn{n} are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.
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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 = 0.159}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
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}
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\section{Source}{
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\enumerate{
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\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}
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\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}
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\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}
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\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}
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\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}
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\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}
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\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 11 December, 2022.
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\item GBIF Secretariat (2022). GBIF Backbone Taxonomy. Checklist dataset \doi{10.15468/39omei}. Accessed from \url{https://www.gbif.org} on 11 December, 2022.
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\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}
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\item Bartlett A \emph{et al.} (2022). \strong{A comprehensive list of bacterial pathogens infecting humans} \emph{Microbiology} 168:001269; \doi{10.1099/mic.0.001269}
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}
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}
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\section{Reference Data Publicly Available}{
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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}.
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}
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\examples{
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# taxonomic tree -----------------------------------------------------------
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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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mo_order("Klebsiella pneumoniae")
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mo_family("Klebsiella pneumoniae")
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mo_genus("Klebsiella pneumoniae")
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mo_species("Klebsiella pneumoniae")
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mo_subspecies("Klebsiella pneumoniae")
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# colloquial properties ----------------------------------------------------
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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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# other properties ---------------------------------------------------------
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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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# scientific reference -----------------------------------------------------
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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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# abbreviations known in the field -----------------------------------------
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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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mo_gramstain("VISA")
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mo_genus("EHEC")
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mo_species("EHEC")
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# known subspecies ---------------------------------------------------------
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mo_fullname("K. pneu rh")
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mo_shortname("K. pneu rh")
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\donttest{
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# Becker classification, see ?as.mo ----------------------------------------
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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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# Lancefield classification, see ?as.mo ------------------------------------
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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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mo_shortname("S. pyo", Lancefield = TRUE)
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# language support --------------------------------------------------------
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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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mo_gramstain("Klebsiella pneumoniae", language = "el") # Greek
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mo_gramstain("Klebsiella pneumoniae", language = "uk") # Ukrainian
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# mo_type is equal to mo_kingdom, but mo_kingdom will remain official
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mo_kingdom("Klebsiella pneumoniae")
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mo_type("Klebsiella pneumoniae")
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mo_kingdom("Klebsiella pneumoniae", language = "zh") # Chinese, no effect
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mo_type("Klebsiella pneumoniae", language = "zh") # Chinese, translated
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mo_fullname("S. pyogenes", Lancefield = TRUE, language = "de")
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mo_fullname("S. pyogenes", Lancefield = TRUE, language = "uk")
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# other --------------------------------------------------------------------
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mo_is_yeast(c("Candida", "Trichophyton", "Klebsiella"))
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# 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)
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|
}
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|
# get a list with the complete taxonomy (from kingdom to subspecies)
|
|
mo_taxonomy("Klebsiella pneumoniae")
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|
|
|
# get a list with the taxonomy, the authors, Gram-stain,
|
|
# SNOMED codes, and URL to the online database
|
|
mo_info("Klebsiella pneumoniae")
|
|
}
|
|
}
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|
\seealso{
|
|
Data set \link{microorganisms}
|
|
}
|