Overview

• Researchers from UCLA and the University of Toronto developed moPepGen, a graph-based computational tool for comprehensive protein variant analysis.
• moPepGen’s graph model systematically captures alternative splicing, gene fusions, circular RNAs and RNA editing to reveal non-canonical peptides.
• The tool detected four times more unique protein variants than prior methods across proteogenomic data from prostate and kidney tumors and 376 cancer cell lines.
• moPepGen identifies tumor-specific variant peptides that serve as neoantigens, supporting the design of personalized cancer vaccines and adoptive cell therapies.
• Available freely on GitHub and compatible with existing proteomics workflows, moPepGen also holds promise for neurodegenerative and other protein-driven disease research.