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97 lines
4.4 KiB
R
97 lines
4.4 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/mo_source.R
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\name{mo_source}
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\alias{mo_source}
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\alias{set_mo_source}
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\alias{get_mo_source}
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\title{Use predefined reference data set}
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\usage{
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set_mo_source(path)
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get_mo_source()
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}
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\arguments{
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\item{path}{location of your reference file, see Details}
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}
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\description{
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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}}.
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This is \strong{the fastest way} to have your organisation (or analysis) specific codes picked up and translated by this package.
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}
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\details{
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The reference file can be a text file seperated with commas (CSV) or tabs or pipes, an Excel file (either 'xls' or 'xlsx' format) or an R object file (extension '.rds'). To use an Excel file, you need to have the \code{readxl} package installed.
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\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 = ...)}.
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\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.
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Reading an Excel file (\code{.xlsx}) with only one row has a size of 8-9 kB. The compressed file used by this package 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).
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}
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\section{How it works}{
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Imagine this data on a sheet of an Excel file (mo codes were looked up in the `microorganisms` data set). The first column contains the organisation specific codes, the second column contains an MO code from this package:
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\preformatted{
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| A | B |
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--|--------------------|-------------|
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1 | Organisation XYZ | mo |
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2 | lab_mo_ecoli | B_ESCHR_COL |
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3 | lab_mo_kpneumoniae | B_KLBSL_PNE |
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4 | | |
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}
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We save it as \code{'home/me/ourcodes.xlsx'}. Now we have to set it as a source:
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\preformatted{
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set_mo_source("home/me/ourcodes.xlsx")
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# Created mo_source file '~/.mo_source.rds' from 'home/me/ourcodes.xlsx'.
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}
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It has now created a file "~/.mo_source.rds" with the contents of our Excel file, but only the first column with foreign values and the 'mo' column will be kept.
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And now we can use it in our functions:
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\preformatted{
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as.mo("lab_mo_ecoli")
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[1] B_ESCHR_COL
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mo_genus("lab_mo_kpneumoniae")
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[1] "Klebsiella"
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# other input values still work too
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as.mo(c("Escherichia coli", "E. coli", "lab_mo_ecoli"))
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[1] B_ESCHR_COL B_ESCHR_COL B_ESCHR_COL
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}
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If we edit the Excel file to, let's say, this:
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\preformatted{
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| A | B |
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--|--------------------|-------------|
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1 | Organisation XYZ | mo |
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2 | lab_mo_ecoli | B_ESCHR_COL |
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3 | lab_mo_kpneumoniae | B_KLBSL_PNE |
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4 | lab_Staph_aureus | B_STPHY_AUR |
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5 | | |
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}
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...any new usage of an MO function in this package will update your data:
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\preformatted{
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as.mo("lab_mo_ecoli")
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# Updated mo_source file '~/.mo_source.rds' from 'home/me/ourcodes.xlsx'.
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[1] B_ESCHR_COL
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mo_genus("lab_Staph_aureus")
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[1] "Staphylococcus"
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}
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To remove the reference completely, just use any of these:
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\preformatted{
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set_mo_source("")
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set_mo_source(NULL)
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# Removed mo_source file '~/.mo_source.rds'.
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}
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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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