ProBAMsuite, a bioinformatics framework for genome-based representation and analysis of proteomics data

Xiaojing Wang, Robbert J.C. Slebos, Matthew C. Chambers, David L. Tabb, Daniel C. Liebler, Bing Zhang

Research output: Contribution to journalArticlepeer-review

24 Scopus citations


To facilitate genome-based representation and analysis of proteomics data, we developed a new bioinformatics framework, proBAMsuite, in which a central component is the protein BAM (proBAM) file format for organizing peptide spectrum matches (PSMs)1 within the context of the genome. proBAMsuite also includes two R packages, pro-BAMr and proBAMtools, for generating and analyzing pro-BAM files, respectively. Applying proBAMsuite to three recently published proteomics datasets, we demonstrated its utility in facilitating efficient genome-based sharing, interpretation, and integration of proteomics data. First, the interpretation of proteomics data is significantly enhanced with the rich genomic annotation information. Second, PSMs can be easily reannotated using user-specified gene annotation schemes and assembled into both protein and gene identifications. Third, using the genome as a common reference, proBAMsuite facilitates seamless proteomics and proteogenomics data integration. Finally, proBAM files can be readily visualized in genome browsers and thus bring proteomics data analysis to a general audience beyond the proteomics community. Results from this study establish proBAMsuite as a useful bioinformatics framework for proteomics and proteogenomics research.

Original languageEnglish (US)
Pages (from-to)1164-1175
Number of pages12
JournalMolecular and Cellular Proteomics
Issue number3
StatePublished - Mar 2016
Externally publishedYes

ASJC Scopus subject areas

  • Analytical Chemistry
  • Molecular Biology
  • Biochemistry


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