proBAMsuite, a Bioinformatics Framework for Genome-Based Representation and Analysis of Proteomics Data.

Mol Cell Proteomics

From the ‡Department of Biomedical Informatics, ‖Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN 37232;

Published: March 2016

AI Article Synopsis

  • A new bioinformatics framework called proBAMsuite was developed to improve the organization and analysis of proteomics data using a unique protein BAM (proBAM) file format linked to the genome.
  • The suite includes two R packages, proBAMr and proBAMtools, that assist in creating and analyzing proBAM files, highlighting its effectiveness through three published proteomics datasets.
  • proBAMsuite enhances data interpretation with genomic annotations, allows customization of PSM reannotation, and facilitates integration of proteomics with genomic data, making it accessible for a wider audience beyond just proteomics researchers.

Article Abstract

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, proBAMr and proBAMtools, for generating and analyzing proBAM 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4813696PMC
http://dx.doi.org/10.1074/mcp.M115.052860DOI Listing

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