Upload tasks/dia-proteomics/scripts/msstats_analysis.R with huggingface_hub

tasks/dia-proteomics/scripts/msstats_analysis.R

@@ -0,0 +1,105 @@
+#!/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")