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

Author:

Choi Seunghyuk1,Paek Eunok1

Affiliation:

1. Department of Computer Science, Hanyang University, Seongdong-gu, Seoul 04763, Republic of Korea

Abstract

Abstract 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. Availability and implementation https://prix.hanyang.ac.kr/download/mutcombinator.jsp. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Research Foundation of Korea

National Research Foundation

Ministry of Education of Korea

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference24 articles.

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