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Julian Uszkoreit, Alexandra Maerkens, Yasset Perez-Riverol, Helmut E Meyer, Katrin Marcus, Christian Stephan, Oliver Kohlbacher, and Martin Eisenacher (2015)

PIA - An intuitive protein inference engine with a web-based user interface

J. Proteome Res., 14(7):2988-97.

Protein inference connects the peptide-spectrum matches (PSMs) obtained from database search engines back to proteins, which are typically at the heart of most proteomics studies. Different search engines yield different PSMs and thus different protein lists. Analysis of results from one or multiple search engines is often hampered by different data exchange formats and lack of convenient and intuitive user interfaces. We present PIA, a flexible software suite for combining PSMs from different search engine runs and turning these into consistent results. PIA can be integrated into proteomics data analysis workflows in several ways. A user-friendly graphical user interface can either be run locally or (e.g., for larger core facilities) from a central server. For automated data processing, stand-alone tools are available. PIA implements several established protein inference algorithms and can combine results from different search engines seamlessly. On several benchmark datasets we can show that PIA can identify a larger number of proteins at the same protein FDR when compared to inference based on a single search engine. PIA supports the majority of established search engines and data in the mzIdentML standard format. It is implemented in Java and freely available from https://github.com/mpc-bioinformatics/pia.
25938255
10.1021/acs.jproteome.5b00121