PhosphoExplorer: Software for annotating and analyzing phosphoproteomics data

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Abstract Phosphoproteomics (PP) data derived from mass spectrometry experiments has a unique ability to interrogate cellular signaling pathways and networks in a comprehensive manner. Such information on a global scale will provide unique insights into cellular signaling in development and differentiation, which will considerably advance our understanding of biology. Although technologies for collecting PP data using mass spectrometry are advancing rapidly, computational tools for analyzing the PP data are not keeping pace. The management and annotation of information on thousands of phosphosites is ineffective if conducted manually and must be automated and visually presented to the user. In addition, although many effective tools exist for pathway and network analysis of gene and protein expression data, the tools for PP are relatively underdeveloped. This proposal, submitted under PA-14-155, intends to advance the field of PP by developing, testing, and disseminating software for phosphoprotein and phosphosite identification, localization, annotation, pathway and network analysis. The outcome of this research will be more rapid and effective translation of PP data into useful knowledge for advancing biological science and drug development. The research will comprise 3 Aims: Aim 1: Development and testing of PhosMS-GF+ and PhosphoExplorer, a tool for phosphosite identification and annotation from mass spectrometry data. This aim will provide a tool that can unify mass spectrometry data with multiple phosphosite databases and extend the number of PP identifications improving analyses. Aim 2: Development and testing of a phosphoprotein set enrichment analysis tool kit and phosphoprotein interaction and network analysis tool kit as expansions of PhosphoExplorer. This aim will provide an unique toolkit for systems level analysis of PP data. Aim 3: Develop, test, calibrate, and release software tools for systems-level annotation and analysis of phosphoproteomics data. This aim will deliver robust open-source software to the user community. As prototype versions of PhosphoExplorer currently exist and are in use in-house at Case Western Reserve University, we have no doubt that over a three-year period we can complete the above improvements and put the tools in the hands of a national cohort of users that are actively collecting and analyzing PP datasets.