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 the latest version here.
How to Use
- Philosopher basics - general usage information
- Preparing protein databases - download and format sequences
- Simple data analysis - basic step-by-step tutorial
- Using pipeline for TMT analysis - pipeline analysis of a large data set
- Step-by-step TMT analysis - step-by-step tutorial for isobaric quantification of a small data set
- Open search analysis - step-by-step tutorial for open searches
- Step-by-step analysis with Comet - step-by-step tutorial with Comet search
- Protein-protein interaction analysis - analyze AP-MS data for downstream use with REPRINT
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)
Guo Ci Teo
Alexey Nesvizhskii’s research group