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225 lines
8.5 KiB
R
225 lines
8.5 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# SOURCE #
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# https://gitlab.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2018-2020 Berends MS, Luz CF et al. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
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#' Use predefined reference data set
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#'
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#' @description These functions can be used to predefine your own reference to be used in [as.mo()] and consequently all `mo_*` functions like [mo_genus()] and [mo_gramstain()].
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#'
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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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#' @inheritSection lifecycle Stable lifecycle
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#' @param path location of your reference file, see Details
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#' @rdname mo_source
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#' @name mo_source
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#' @aliases set_mo_source get_mo_source
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#' @details 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 `readxl` package installed.
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#'
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#' [set_mo_source()] will check the file for validity: it must be a [`data.frame`], must have a column named `"mo"` which contains values from [`microorganisms$mo`][microorganisms] and must have a reference column with your own defined values. If all tests pass, [set_mo_source()] will read the file into R and export it to `"~/.mo_source.rds"`. This compressed data file will then be used at default for MO determination (function [as.mo()] and consequently all `mo_*` functions like [mo_genus()] and [mo_gramstain()]). The location of the original file will be saved as option with `options(mo_source = path)`. Its timestamp will be saved with `options(mo_source_datetime = ...)`.
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#'
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#' [get_mo_source()] will return the data set by reading `"~/.mo_source.rds"` with [readRDS()]. If the original file has changed (the file defined with `path`), it will call [set_mo_source()] to update the data file automatically.
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#'
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#' Reading an Excel file (`.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 [get_mo_source()] in only a couple of microseconds (a millionth of a second).
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#'
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#' ## How it works
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#'
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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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#' ```
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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_COLI |
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#' 3 | lab_mo_kpneumoniae | B_KLBSL_PNMN |
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#' 4 | | |
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#' ```
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#'
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#' We save it as `"home/me/ourcodes.xlsx"`. Now we have to set it as a source:
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#' ```
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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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#'
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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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#'
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#' And now we can use it in our functions:
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#' ```
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#' as.mo("lab_mo_ecoli")
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#' [1] B_ESCHR_COLI
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#'
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#' mo_genus("lab_mo_kpneumoniae")
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#' [1] "Klebsiella"
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#'
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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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#' ```
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#'
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#' If we edit the Excel file to, let's say, by adding row 4 like this:
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#' ```
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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_COLI |
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#' 3 | lab_mo_kpneumoniae | B_KLBSL_PNMN |
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#' 4 | lab_Staph_aureus | B_STPHY_AURS |
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#' 5 | | |
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#' ```
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#'
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#' ...any new usage of an MO function in this package will update your data file:
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#' ```
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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_COLI
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#'
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#' mo_genus("lab_Staph_aureus")
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#' [1] "Staphylococcus"
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#' ```
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#'
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#' To remove the reference data file completely, just use `""` or `NULL` as input for `[set_mo_source()]`:
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#' ```
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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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#' @importFrom dplyr select everything
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#' @export
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#' @inheritSection AMR Read more on our website!
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set_mo_source <- function(path) {
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file_location <- path.expand("~/mo_source.rds")
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if (!is.character(path) | length(path) > 1) {
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stop("`path` must be a character of length 1.")
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}
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if (path %in% c(NULL, "")) {
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options(mo_source = NULL)
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options(mo_source_timestamp = NULL)
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if (file.exists(file_location)) {
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unlink(file_location)
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message("Removed mo_source file '", file_location, "'.")
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}
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return(invisible())
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}
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if (!file.exists(path)) {
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stop("File not found: ", path)
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}
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if (path %like% "[.]rds$") {
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df <- readRDS(path)
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} else if (path %like% "[.]xlsx?$") {
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# is Excel file (old or new)
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stopifnot_installed_package("readxl")
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df <- readxl::read_excel(path)
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} else if (path %like% "[.]tsv$") {
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df <- utils::read.table(header = TRUE, sep = "\t", stringsAsFactors = FALSE)
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} else {
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# try comma first
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try(
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df <- utils::read.table(header = TRUE, sep = ",", stringsAsFactors = FALSE),
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silent = TRUE)
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if (!mo_source_isvalid(df)) {
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# try tab
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try(
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df <- utils::read.table(header = TRUE, sep = "\t", stringsAsFactors = FALSE),
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silent = TRUE)
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}
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if (!mo_source_isvalid(df)) {
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# try pipe
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try(
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df <- utils::read.table(header = TRUE, sep = "|", stringsAsFactors = FALSE),
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silent = TRUE)
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}
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}
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if (!mo_source_isvalid(df)) {
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stop("File must contain a column with self-defined values and a reference column `mo` with valid values from the `microorganisms` data set.")
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}
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df <- df %>% filter(!is.na(mo))
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# keep only first two columns, second must be mo
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if (colnames(df)[1] == "mo") {
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df <- df[, c(2, 1)]
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} else {
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df <- df[, c(1, 2)]
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}
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df <- as.data.frame(df, stringAsFactors = FALSE)
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# success
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if (file.exists(file_location)) {
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action <- "Updated"
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} else {
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action <- "Created"
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}
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saveRDS(df, file_location)
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options(mo_source = path)
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options(mo_source_timestamp = as.character(file.info(path)$mtime))
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message(action, " mo_source file '", file_location, "' from '", path, "'.")
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}
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#' @rdname mo_source
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#' @export
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get_mo_source <- function() {
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if (is.null(getOption("mo_source", NULL))) {
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NULL
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} else {
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old_time <- as.POSIXct(getOption("mo_source_timestamp"))
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new_time <- as.POSIXct(as.character(file.info(getOption("mo_source", ""))$mtime))
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if (is.na(new_time)) {
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# source file was deleted, remove reference too
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set_mo_source("")
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return(NULL)
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}
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if (new_time != old_time) {
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# set updated source
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set_mo_source(getOption("mo_source"))
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}
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file_location <- path.expand("~/mo_source.rds")
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readRDS(file_location)
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}
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}
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mo_source_isvalid <- function(x) {
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check_dataset_integrity()
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if (deparse(substitute(x)) == "get_mo_source()") {
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return(TRUE)
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}
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if (identical(x, get_mo_source())) {
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return(TRUE)
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}
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if (is.null(x)) {
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return(TRUE)
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}
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if (!is.data.frame(x)) {
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return(FALSE)
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}
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if (!"mo" %in% colnames(x)) {
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return(FALSE)
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}
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all(x$mo %in% c("", microorganisms$mo, microorganisms.translation$mo_old), na.rm = TRUE)
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}
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