maxquant-proteomics
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
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