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All Projects → Nesvilab → philosopher

Nesvilab / philosopher

Licence: GPL-3.0 license
A complete toolkit for shotgun proteomics data analysis

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bioinformaticsdata-analysisproteomicsmass-spectrometryms-data

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Release Golang Go Report Card GitHub GitHub Workflow Status

Philosopher is a fast, easy-to-use, scalable, and versatile data analysis software for mass spectrometry-based proteomics. Philosopher is dependency-free and can analyze both traditional database searches and open searches for post-translational modification (PTM) discovery.

  • Database downloading and formatting.

  • Peptide-spectrum matching with MSFragger and Comet.

  • Peptide assignment validation with PeptideProphet.

  • Multi-level integrative analysis with iProphet.

  • PTM site localization with PTMProphet.

  • Protein inference with ProteinProphet.

  • FDR filtering with custom algorithms.

    • Two-dimensional filtering for simultaneous control of PSM and Protein FDR levels.
    • Sequential FDR estimation for large data sets using filtered PSM and proteins lists.

  • Label-free quantification via spectral counting and MS1 intensities.

  • Label-based quantification using TMT and iTRAQ.

  • Quantification based on functional protein groups.

  • Multi-level detailed reports for peptides, ions, and proteins.

  • Support for REPRINT and MSstats.

Download

Download the latest version here.

How to Use

Documentation

See the documentation for more details about the available commands.

Questions, requests and bug reports

If you have any questions or remarks please use the Discussion board. If you want to report a bug, please use the Issue tracker.

How to cite

da Veiga Leprevost F, Haynes SE, Avtonomov DM, Chang HY, Shanmugam AK, Mellacheruvu D, Kong AT, Nesvizhskii AI. Philosopher: a versatile toolkit for shotgun proteomics data analysis. Nat Methods. 2020 Sep;17(9):869-870. doi: 10.1038/s41592-020-0912-y. PMID: 32669682; PMCID: PMC7509848.

About the authors, and contributors

Felipe da Veiga Leprevost (main author)

Sarah Haynes

Guo Ci Teo

Alexey Nesvizhskii's research group

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