106 lines
3.0 KiB
Plaintext
106 lines
3.0 KiB
Plaintext
nextflow.enable.dsl=2
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process CORTO {
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container "${params.container}"
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containerOptions "${params.containerOptions}"
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publishDir "${params.outdir}/${params.project_name}", mode: 'copy'
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debug true
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// maxForks 1
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stageInMode 'copy'
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input:
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path gene_expression_matrix
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path centroid_list
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path cnv_data // This could be optional
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// Define output channels
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output:
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path "regulon.rda", emit: regulon
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path "*.csv", emit: csv_regulon
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path "*.log", optional: true, emit: logs // if you have log files
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script:
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"""
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#!/bin/bash
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# Create an R script
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cat <<EOF > corto_analysis.R
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# Print the R version
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print(R.version.string)
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# Load the corto library
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library(corto)
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# Function to load data
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loadData <- function(file_name, expected_var) {
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load(file_name)
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if (exists(expected_var)) {
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data <- get(expected_var)
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} else {
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stop(paste("Object", expected_var, "not found in", file_name))
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}
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return(data)
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}
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# Load the input matrix
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inmat <- loadData("${gene_expression_matrix}", "inmat")
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print("Dimensions of inmat before any operation:")
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print(dim(inmat))
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# Load the centroids
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centroids <- loadData("${centroid_list}", "centroids")
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print("Length of centroids:")
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print(length(centroids))
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# Run corto with specified parameters
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regulon <- corto(inmat, centroids=centroids, nbootstraps=10, p=1e-30, nthreads=2)
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# Save the regulon object for later use
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save(regulon, file="regulon.rda")
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# Transform regulon into a data frame
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regulon_to_df <- function(regulon) {
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result_df <- data.frame(TF = character(),
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Target = character(),
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TFMode = numeric(),
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Likelihood = numeric(),
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stringsAsFactors = FALSE)
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for (tf in names(regulon)) {
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tf_data <- regulon[[tf]]
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if (is.null(tf_data\$tfmode) || is.null(tf_data\$likelihood)) next
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for (i in seq_along(tf_data\$tfmode)) {
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tf_mode <- tf_data\$tfmode[[i]]
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likelihood <- tf_data\$likelihood[[i]]
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target_name <- names(tf_data\$tfmode)[i]
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tf_df <- data.frame(TF = tf,
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Target = target_name,
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TFMode = tf_mode,
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Likelihood = likelihood,
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stringsAsFactors = FALSE)
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result_df <- rbind(result_df, tf_df)
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}
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}
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return(result_df)
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}
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# Check if regulon is a list and transform it
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if (is.list(regulon)) {
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regulon_df <- regulon_to_df(regulon)
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write.csv(regulon_df, file="regulon.csv", row.names=FALSE)
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} else {
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warning("Regulon object is not a list. Custom transformation needed.")
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}
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EOF
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# Execute the R script
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Rscript corto_analysis.R
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"""
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}
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