#!/usr/bin/env Rscript # MSstats analysis for DIA proteomics data # Input: TRIC-aligned feature file + sample sheet # Output: differential expression results suppressPackageStartupMessages({ library(MSstats) }) args <- commandArgs(trailingOnly = TRUE) aligned_file <- args[1] sample_sheet_file <- args[2] output_dir <- args[3] dir.create(output_dir, recursive = TRUE, showWarnings = FALSE) cat("=== MSstats Analysis ===\n") # Read aligned features from TRIC aligned <- read.delim(aligned_file, stringsAsFactors = FALSE) cat("Aligned features:", nrow(aligned), "\n") # Read sample sheet sample_sheet <- read.delim(sample_sheet_file, stringsAsFactors = FALSE) cat("Sample sheet:\n") print(sample_sheet) # Prepare MSstats input format # The aligned file from TRIC has columns like: # transition_group_id, run_id, Intensity, etc. # Map run names to conditions from sample sheet tryCatch({ # Check available columns cat("Aligned columns:", paste(head(names(aligned), 20), collapse=", "), "\n") # Try to build MSstats-compatible input # OpenSWATH/TRIC output needs conversion if ("ProteinName" %in% names(aligned) && "filename" %in% names(aligned)) { # Create condition mapping run_to_condition <- setNames(sample_sheet$Condition, sample_sheet$Sample) # Build MSstats input msstats_input <- data.frame( ProteinName = aligned$ProteinName, PeptideSequence = if ("FullPeptideName" %in% names(aligned)) aligned$FullPeptideName else aligned$Sequence, PrecursorCharge = if ("Charge" %in% names(aligned)) aligned$Charge else 2, FragmentIon = if ("aggr_Fragment_Annotation" %in% names(aligned)) aligned$aggr_Fragment_Annotation else "y", ProductCharge = 1, IsotopeLabelType = "L", Condition = sapply(aligned$filename, function(fn) { # Match filename to sample sheet matched <- which(sapply(sample_sheet$Sample, function(s) grepl(s, fn, fixed=TRUE))) if (length(matched) > 0) sample_sheet$Condition[matched[1]] else "Unknown" }), BioReplicate = aligned$filename, Run = aligned$filename, Intensity = if ("Intensity" %in% names(aligned)) aligned$Intensity else if ("m_score" %in% names(aligned)) 10^6 else 0, stringsAsFactors = FALSE ) cat("MSstats input rows:", nrow(msstats_input), "\n") cat("Conditions:", paste(unique(msstats_input$Condition), collapse=", "), "\n") # Run MSstats processed <- dataProcess(msstats_input, logTrans = 2, normalization = "equalizeMedians") # Check if we have 2+ conditions conditions <- unique(msstats_input$Condition) conditions <- conditions[conditions != "Unknown"] if (length(conditions) >= 2) { contrast_matrix <- matrix(c(1, -1), nrow=1) colnames(contrast_matrix) <- conditions[1:2] rownames(contrast_matrix) <- paste(conditions[1], "vs", conditions[2]) result <- groupComparison(contrast.matrix = contrast_matrix, data = processed) comparison <- result$ComparisonResult write.csv(comparison, file.path(output_dir, "msstats_results.csv"), row.names = FALSE) cat("DE proteins (adj.pvalue < 0.05):", sum(comparison$adj.pvalue < 0.05, na.rm=TRUE), "\n") } else { cat("Only one condition found, skipping differential analysis\n") # Write protein-level summary instead protein_summary <- data.frame( Protein = unique(msstats_input$ProteinName), adj.pvalue = NA ) write.csv(protein_summary, file.path(output_dir, "msstats_results.csv"), row.names = FALSE) } } else { cat("Required columns not found in aligned file\n") cat("Available columns:", paste(names(aligned), collapse=", "), "\n") # Write placeholder write.csv(data.frame(Protein=character(0), adj.pvalue=numeric(0)), file.path(output_dir, "msstats_results.csv"), row.names = FALSE) } }, error = function(e) { cat("MSstats error:", conditionMessage(e), "\n") write.csv(data.frame(Protein=character(0), adj.pvalue=numeric(0)), file.path(output_dir, "msstats_results.csv"), row.names = FALSE) }) cat("=== MSstats complete ===\n")