MaxQuant + Perseus — Proteomics Analysis Pipeline

Overview

MaxQuant is the community-standard software for label-free quantification (LFQ) and SILAC proteomics. It performs database search, protein grouping, and intensity-based quantification from raw LC-MS/MS files, producing proteinGroups.txt as the primary output. Downstream statistical analysis — filtering, normalization, imputation, differential abundance testing, and visualization — is performed in Python using pandas, scipy, and matplotlib/seaborn, mirroring the Perseus workflow in a reproducible scripting environment.

When to Use

• Performing label-free quantification (LFQ) of proteins across multiple biological conditions — MaxQuant's MaxLFQ algorithm is the community benchmark
• Running SILAC (stable isotope labeling) experiments with light/heavy or triple-label designs
• Processing iTRAQ or TMT isobaric labeling experiments via MaxQuant's reporter ion quantification
• Identifying and quantifying proteins when you need the widely-cited MaxQuant output format (proteinGroups.txt) for comparison with published datasets
• Performing statistical differential abundance analysis on MaxQuant outputs without installing Perseus (GUI-only, Windows)
• Generating publication-quality volcano plots and GO enrichment from proteomics data in a reproducible Python workflow
• Use Proteome Discoverer instead when working with Thermo raw files requiring instrument-native processing or Sequest HT
• Use FragPipe/MSFragger instead for GPU-accelerated database search (3–10× faster) or when processing DIA (data-independent acquisition) data

Prerequisites