Joint Protein Inference Analysis with PyProteinInference Elucidates Biological Understanding of Tandem Mass Spectrometry Data

Abstract

Selection and application of protein inference algorithms can have a significant impact on the data output from tandem mass spectrometry (MS/MS) experiments, yet its use is often an afterthought in proteomics research due to the inability to apply different inference algorithms in existing analysis systems today. PyProteinInference provides a comprehensive suite of tools to guide researchers through the application of multiple inference algorithms and computation of protein-level, set-based false discovery rates (FDR) from tandem mass spectrometry (MS/MS) data using a unified interface. Here, we describe the software and its application to a K562 whole-cell lysate as well as in a CRAF affinity-purification mass spectrometry experiment to demonstrate its utility in facilitating conclusions about underlying biological mechanisms in proteomic data.