AMR/man/mo_source.Rd

63 lines
3.2 KiB
R

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mo_source.R
\name{mo_source}
\alias{mo_source}
\alias{set_mo_source}
\alias{get_mo_source}
\title{Use predefined reference data set}
\usage{
set_mo_source(path)
get_mo_source()
}
\arguments{
\item{path}{location of your reference file, see Details}
}
\description{
These functions can be used to predefine your own reference to be used in \code{\link{as.mo}} and consequently all \code{mo_*} functions like \code{\link{mo_genus}} and \code{\link{mo_gramstain}}.
}
\details{
The reference file can be a text file seperated with commas (CSV) or pipes, an Excel file (old 'xls' format or new 'xlsx' format) or an R object file (extension '.rds'). To use an Excel file, you need to have the \code{readxl} package installed.
\code{set_mo_source} will check the file for validity: it must be a \code{data.frame}, must have a column named \code{"mo"} which contains values from \code{microorganisms$mo} and must have a reference column with your own defined values. If all tests pass, \code{set_mo_source} will read the file into R and export it to \code{"~/.mo_source.rds"}. This compressed data file will then be used at default for MO determination (function \code{\link{as.mo}} and consequently all \code{mo_*} functions like \code{\link{mo_genus}} and \code{\link{mo_gramstain}}). The location of the original file will be saved as option with \code{\link{options}(mo_source = path)}. Its timestamp will be saved with \code{\link{options}(mo_source_datetime = ...)}.
\code{get_mo_source} will return the data set by reading \code{"~/.mo_source.rds"} with \code{\link{readRDS}}. If the original file has changed (the file defined with \code{path}), it will call \code{set_mo_source} to update the data file automatically.
Reading an Excel file (\code{.xlsx}) with only one row has a size of 8-9 kB. The compressed file will have a size of 0.1 kB and can be read by \code{get_mo_source} in only a couple of microseconds (a millionth of a second).
}
\section{Read more on our website!}{
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}.
}
\examples{
\dontrun{
# imagine this Excel file (mo codes looked up in `microorganisms` data set):
# A B
# 1 our code mo
# 2 lab_mo_ecoli B_ESCHR_COL
# 3 lab_mo_kpneumoniae B_KLBSL_PNE
# 1. We save it as 'home/me/ourcodes.xlsx'
# 2. We use it for input:
set_mo_source("C:\\path\\ourcodes.xlsx")
#> Created mo_source file '~/.mo_source.rds' from 'home/me/ourcodes.xlsx'.
# 3. And use it in our functions:
as.mo("lab_mo_ecoli")
#> B_ESCHR_COL
mo_genus("lab_mo_kpneumoniae")
#> "Klebsiella"
# 4. It will look for changes itself:
# (add new row to the Excel file and save it)
mo_genus("lab_mo_kpneumoniae")
#> Updated mo_source file '~/.mo_source.rds' from 'home/me/ourcodes.xlsx'.
#> "Klebsiella"
}
}