msmu 0.2.3

BERTIS LC-MS/MS analysis library through MuData

msmu

Python toolkit for LC-MS/MS Proteomics analysis based on MuData

Overview

msmu is a Python package for scalable, modular, and reproducible LC-MS/MS bottom-up proteomics data analysis.
It supports PSM (precursor), peptide, and protein-level processing, integrates MuData (AnnData) structure, and enables stepwise normalization, batch correction, and statistical testing for biomarker discovery and systems biology.

More Information about msmu can be found in the Documentation.

Key Features

• Flexible data ingestion from DIA-NN, Sage and other popular DB search tools
• MuData/AnnData-compatible object structure for multi-level omics
• Built-in QC: precursor purity, peptide length, charge, missed cleavage
• Protein inference: infer protein with parsimony rule
• Normalization options: log2 transformation, median, quantile, GIS/IRS
• Batch correction: GIS/IRS, median centering
• Statistical analysis: permutation-based DE test and FDR
• PTM support and stoichiometry adjustment with global dataset
• Visualization: PCA, UMAP, volcano plots, heatmaps, QC metrics

Supporting DB Search Tools

• Sage: https://sage-docs.vercel.app
• DIA-NN: https://github.com/vdemichev/DIA-NN
• MaxQuant: https://www.maxquant.org/
• FragPipe: https://fragpipe.nesvilab.org/

License

BSD 3-Clause License. See LICENSE for details.