mirror of
https://github.com/johrpan/geposan.git
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88 lines
2.3 KiB
R
88 lines
2.3 KiB
R
#' Analyze genes based on position data.
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#'
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#' @param preset The preset to use which should be created using [preset()].
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#' @param progress A function to be called for progress information. The
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#' function should accept a number between 0.0 and 1.0 for the current
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#' progress. If no function is provided, a simple text progress bar will be
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#' shown.
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#'
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#' @returns An object containing the results of the analysis with the following
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#' items:
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#' \describe{
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#' \item{`preset`}{The preset that was used.}
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#' \item{`scores`}{Table containing all scores for each gene.}
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#' \item{`results`}{Results from the different methods including details.}
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#' }
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#'
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#' @export
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analyze <- function(preset, progress = NULL) {
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if (!inherits(preset, "geposan_preset")) {
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stop("Preset is invalid. Use geposan::preset() to create one.")
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}
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if (is.null(progress)) {
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progress_bar <- progress::progress_bar$new()
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progress_bar$update(0.0)
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progress <- function(progress_value) {
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if (!progress_bar$finished) {
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progress_bar$update(progress_value)
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if (progress_value >= 1.0) {
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progress_bar$terminate()
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}
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}
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}
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}
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progress_buffer <- 0.0
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method_count <- length(preset$methods)
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method_progress <- function(progress_value) {
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progress(progress_buffer + progress_value / method_count)
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}
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scores <- data.table(gene = preset$gene_id)
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results <- list()
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for (method in preset$methods) {
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method_results <- method$func(preset, method_progress)
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scores <- merge(scores, method_results$scores)
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setnames(scores, "score", method$id)
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results <- c(results, list(method_results))
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progress_buffer <- progress_buffer + 1 / method_count
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progress(progress_buffer)
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}
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structure(
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list(
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preset = preset,
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scores = scores,
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results = results
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),
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class = "geposan_analysis"
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)
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}
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#' Print an analysis object.
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#'
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#' @param x The analysis to print.
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#' @param ... Other parameters.
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#'
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#' @seealso [analyze()]
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#'
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#' @export
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print.geposan_analysis <- function(x, ...) {
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cat("geposan analysis:\n\n")
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print(x$preset)
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cat("\n")
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for (result in x$results) {
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print(result)
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cat("\n")
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}
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invisible(x)
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}
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