AMR/man/microorganisms.old.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{microorganisms.old}
\alias{microorganisms.old}
\title{Data set with previously accepted taxonomic names}
\format{A \code{\link{data.frame}} with 2,383 observations and 4 variables:
\describe{
  \item{\code{tsn}}{Old Taxonomic Serial Number (TSN), as defined by ITIS}
  \item{\code{name}}{Old taxonomic name of the microorganism as found in ITIS, see Source}
  \item{\code{tsn_new}}{New Taxonomic Serial Number (TSN), as defined by ITIS}
  \item{\code{ref}}{Author(s) and year of concerning publication as found in ITIS, see Source}
}}
\source{
[3] Integrated Taxonomic Information System (ITIS) on-line database, \url{https://www.itis.gov}.
}
\usage{
microorganisms.old
}
\description{
A data set containing old (previously valid or accepted) taxonomic names according to ITIS. This data set is used internally by \code{\link{as.mo}}.
}
\section{ITIS}{

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This package contains the \strong{complete microbial taxonomic data} (with all nine taxonomic ranks - from kingdom to subspecies) from the publicly available Integrated Taxonomic Information System (ITIS, \url{https://www.itis.gov}).

All ~20,000 (sub)species from \strong{the taxonomic kingdoms Bacteria, Fungi and Protozoa are included in this package}, as well as all their ~2,500 previously accepted names known to ITIS. Furthermore, the responsible authors and year of publication are available. This allows users to use authoritative taxonomic information for their data analysis on any microorganism, not only human pathogens. It also helps to quickly determine the Gram stain of bacteria, since ITIS honours the taxonomic branching order of bacterial phyla according to Cavalier-Smith (2002), which defines that all bacteria are classified into either subkingdom Negibacteria or subkingdom Posibacteria.

ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic specialists [3].
}

\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 omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R.
}

\seealso{
\code{\link{as.mo}} \code{\link{mo_property}} \code{\link{microorganisms}}
}
\keyword{datasets}