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

Area of Science:

• Bioinformatics
• Proteomics
• Genomics

Background:

• Proteomics data analysis traditionally lacks direct genomic context.
• Integrating proteomics with genomic information is crucial for comprehensive biological insights.

Purpose of the Study:

• To introduce proBAMsuite, a novel bioinformatics framework for genome-based proteomics data management.
• To enhance the interpretation, sharing, and integration of proteomics data using genomic annotations.

Main Methods:

• Development of the protein BAM (proBAM) file format for organizing peptide spectrum matches (PSMs) with genomic context.
• Creation of R packages (proBAMr and proBAMtools) for proBAM file generation and analysis.
• Application of proBAMsuite to existing proteomics datasets.

Main Results:

• proBAMsuite significantly enhances proteomics data interpretation through rich genomic annotation.
• Facilitates reannotation of PSMs and assembly into protein and gene identifications.
• Enables seamless integration of proteomics and proteogenomics data using the genome as a reference.
• Allows visualization of proteomics data in genome browsers, broadening accessibility.

Conclusions:

• proBAMsuite provides a robust framework for genome-based proteomics and proteogenomics research.
• Improves data sharing, interpretation, and integration by linking proteomics to genomic data.
• Increases the accessibility of proteomics data analysis to a wider scientific audience.