The Perseus software platform supports biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication.

• Hands-on tutorials and theoretical lectures are available on the MaxQuant youtube channel.
• Participate in our annual MaxQuant summer school to gain even deeper insights into MaxQuant and Perseus.
• Read the protocol-style book chapter on Perseus.
• Join the discussion around Perseus and data analysis on the Perseus mailing list – a great place to ask any question and get answers from the community.

Perseus is freely available to commercial and academic users, just follow the download and installation guide.

If you use Perseus in your project, please cite:
The Perseus computational platform for comprehensive analysis of (prote)omics data Nat. Methods 2016.

Network analysis, co-expression and PluginInterop:
A network module for the Perseus software for computational proteomics facilitates proteome interaction graph analysis BioRxiv 2018.

Find a predictive protein signature using SVMs:
Proteomic maps of breast cancer subtypes Nat. Comm. 2016.

Perform 1D or 2D annotation enrichment:
1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data BMC Bioinformatics 2012.

See our 'Report a bug' page.