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This is the fastest way to have your organisation (or analysis) specific codes picked up and translated by this package." />
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< h1 > Use predefined reference data set< / h1 >
< div class = "hidden name" > < code > mo_source.Rd< / code > < / div >
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< p > These functions can be used to predefine your own reference to be used in < code > < a href = 'as.mo.html' > as.mo()< / a > < / code > and consequently all < code > mo_*< / code > functions like < code > < a href = 'mo_property.html' > mo_genus()< / a > < / code > and < code > < a href = 'mo_property.html' > mo_gramstain()< / a > < / code > .< / p >
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< p > This is < strong > the fastest way< / strong > to have your organisation (or analysis) specific codes picked up and translated by this package.< / p >
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< / div >
< pre class = "usage" > < span class = 'fu' > set_mo_source< / span > (< span class = 'no' > path< / span > )
< span class = 'fu' > get_mo_source< / span > ()< / pre >
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< h2 class = "hasAnchor" id = "arguments" > < a class = "anchor" href = "#arguments" > < / a > Arguments< / h2 >
< table class = "ref-arguments" >
< colgroup > < col class = "name" / > < col class = "desc" / > < / colgroup >
< tr >
< th > path< / th >
< td > < p > location of your reference file, see Details< / p > < / td >
< / tr >
< / table >
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< h2 class = "hasAnchor" id = "details" > < a class = "anchor" href = "#details" > < / a > Details< / h2 >
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< p > 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< / code > package installed.< / p >
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< p > < code > set_mo_source()< / code > will check the file for validity: it must be a < code > < a href = 'https://rdrr.io/r/base/data.frame.html' > data.frame< / a > < / code > , must have a column named < code > "mo"< / code > which contains values from < code > < a href = 'microorganisms.html' > microorganisms$mo< / a > < / code > and must have a reference column with your own defined values. If all tests pass, < code > set_mo_source()< / code > will read the file into R and export it to < code > "~/.mo_source.rds"< / code > . This compressed data file will then be used at default for MO determination (function < code > < a href = 'as.mo.html' > as.mo()< / a > < / code > and consequently all < code > mo_*< / code > functions like < code > < a href = 'mo_property.html' > mo_genus()< / a > < / code > and < code > < a href = 'mo_property.html' > mo_gramstain()< / a > < / code > ). The location of the original file will be saved as option with < code > < a href = 'https://rdrr.io/r/base/options.html' > options(mo_source = path)< / a > < / code > . Its timestamp will be saved with < code > < a href = 'https://rdrr.io/r/base/options.html' > options(mo_source_datetime = ...)< / a > < / code > .< / p >
< p > < code > get_mo_source()< / code > will return the data set by reading < code > "~/.mo_source.rds"< / code > with < code > < a href = 'https://rdrr.io/r/base/readRDS.html' > readRDS()< / a > < / code > . If the original file has changed (the file defined with < code > path< / code > ), it will call < code > set_mo_source()< / code > to update the data file automatically.< / p >
< p > Reading an Excel file (< code > .xlsx< / code > ) 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()< / code > in only a couple of microseconds (a millionth of a second).< / p > < h3 > How it works< / h3 >
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< p > Imagine this data on a sheet of an Excel file (mo codes were looked up in the < code > microorganisms< / code > data set). The first column contains the organisation specific codes, the second column contains an MO code from this package:< / p > < pre > | A | B |
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--|--------------------|-------------|
1 | Organisation XYZ | mo |
2 | lab_mo_ecoli | B_ESCHR_COL |
3 | lab_mo_kpneumoniae | B_KLBSL_PNE |
4 | | |
< / pre >
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< p > We save it as < code > "home/me/ourcodes.xlsx"< / code > . Now we have to set it as a source:< / p > < pre > set_mo_source("home/me/ourcodes.xlsx")
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# Created mo_source file '~/.mo_source.rds' from 'home/me/ourcodes.xlsx'.
< / pre >
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< p > It has now created a file < code > "~/.mo_source.rds"< / code > with the contents of our Excel file, but only the first column with foreign values and the 'mo' column will be kept.< / p >
< p > And now we can use it in our functions:< / p > < pre > as.mo("lab_mo_ecoli")
\[1\] B_ESCHR_COLI
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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_COLI B_ESCHR_COLI B_ESCHR_COLI
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< / pre >
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< p > If we edit the Excel file to, let's say, this:< / p > < pre > | A | B |
--|--------------------|--------------|
1 | Organisation XYZ | mo |
2 | lab_mo_ecoli | B_ESCHR_COLI |
3 | lab_mo_kpneumoniae | B_KLBSL_PNMN |
4 | lab_Staph_aureus | B_STPHY_AURS |
5 | | |
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< / pre >
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< p > ...any new usage of an MO function in this package will update your data:< / p > < pre > 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_COLI
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mo_genus("lab_Staph_aureus")
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[1] "Staphylococcus"
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< / pre >
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< p > To remove the reference completely, just use any of these:< / p > < pre > set_mo_source("")
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set_mo_source(NULL)
# Removed mo_source file '~/.mo_source.rds'.
< / pre >
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< p > On our website < a href = 'https://msberends.gitlab.io/AMR' > https://msberends.gitlab.io/AMR< / a > you can find < a href = 'https://msberends.gitlab.io/AMR/articles/AMR.html' > a tutorial< / a > about how to conduct AMR analysis, the < a href = 'https://msberends.gitlab.io/AMR/reference' > complete documentation of all functions< / a > (which reads a lot easier than here in R) and < a href = 'https://msberends.gitlab.io/AMR/articles/WHONET.html' > an example analysis using WHONET data< / a > .< / p >
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