MutCombinator

MutCombinator identifies mutated peptides from tandem mass spectra by searching combinatorial point mutations on a nucleotide-based variant graph to support proteogenomic analyses.


Key Features:

  • Combinatorial Mutation Search: Considers combinations of point mutations during database searches of tandem mass spectra to detect a broader spectrum of peptide variants.
  • Variant Graph Utilization: Employs a nucleotide-based variant graph that maintains reading-frame information and is indexed by nine nucleotides for rapid access.
  • Integration with Mutation Databases: Uses large mutation databases such as COSMIC to generate candidate variant peptides for searching.
  • In-Frame and Three-Frame Search: Supports in-frame searches for coding regions and three-frame searches for non-coding regions.
  • Genomics–Proteomics Integration: Leverages next-generation sequencing (NGS) and proteomic data to infer protein expression and detect mutation-derived peptide variants.

Scientific Applications:

  • Proteogenomic peptide discovery: Identifies novel peptides that arise from genetic mutations for proteogenomic studies.
  • Detection of combinatorial variant peptides: Detects peptide variants resulting from multiple concurrent point mutations that conventional searches may miss.
  • Cancer proteomics: Supports analysis of protein variations linked to somatic mutations cataloged in COSMIC and other cancer-related mutation datasets.

Methodology:

Performs a nucleotide-based graph search using a variant graph indexed by nine nucleotides that preserves frame information; considers combinatorial point mutations during database searches of tandem mass spectra; supports in-frame and three-frame searches and incorporates mutation databases such as COSMIC to generate candidate peptides.

Topics

Details

Tool Type:
desktop application
Programming Languages:
Java
Added:
1/18/2021
Last Updated:
3/2/2021

Operations

Publications

Choi S, Paek E. MutCombinator: identification of mutated peptides allowing combinatorial mutations using nucleotide-based graph search. Bioinformatics. 2020;36(Supplement_1):i203-i209. doi:10.1093/bioinformatics/btaa504. PMID:32657416. PMCID:PMC7355298.

PMID: 32657416
PMCID: PMC7355298
Funding: - National Research Foundation of Korea: NRF-2017M3C9A5031597, NRF-2017R1E1A1A01077412, NRF-2019M3E5D3073568