MutCombinator: identification of mutated peptides allowing combinatorial mutations using nucleotide-based graph search

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초록

Motivation: Proteogenomics has proven its utility by integrating genomics and proteomics. Typical approaches use data from next-generation sequencing to infer proteins expressed. A sample-specific protein sequence database is often adopted to identify novel peptides from matched mass spectrometry-based proteomics; nevertheless, there is no software that can practically identify all possible forms of mutated peptides suggested by various genomic information sources.Results: We propose MutCombinator, which enables us to practically identify mutated peptides from tandem mass spectra allowing combinatorial mutations during the database search. It uses an upgraded version of a variant graph, keeping track of frame information. The variant graph is indexed by nine nucleotides for fast access. Using MutCombinator, we could identify more mutated peptides than previous methods, because combinations of point mutations are considered and also because it can be practically applied together with a large mutation database such as COSMIC. Furthermore, MutCombinator supports in-frame search for coding regions and three-frame search for non-coding regions.

키워드

PROTEOGENOMIC CHARACTERIZATIONDATABASE
제목
MutCombinator: identification of mutated peptides allowing combinatorial mutations using nucleotide-based graph search
저자
Choi, SeunghyukPaek, Eunok
DOI
10.1093/bioinformatics/btaa504
발행일
2020-07
유형
Article; Proceedings Paper
저널명
Bioinformatics
36
supp.1
페이지
203 ~ 209

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