MaxQuant Module for the Identification of Genomic Variants Propagated into Peptides

Pavel Sinitcyn; Maximilian Gerwien; Jürgen Cox

doi:10.1007/978-1-0716-2124-0_23

MaxQuant Module for the Identification of Genomic Variants Propagated into Peptides

Methods Mol Biol. 2022:2456:339-347. doi: 10.1007/978-1-0716-2124-0_23.

Authors

Pavel Sinitcyn¹, Maximilian Gerwien¹, Jürgen Cox²

Affiliations

¹ Computational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.
² Computational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany. cox@biochem.mpg.de.

PMID: 35612753
DOI: 10.1007/978-1-0716-2124-0_23

Abstract

Standard shotgun proteomics data analysis pipelines usually only identify peptides that are encoded in the reference genome. In many situations, it is desirable to identify peptides resulting from non-synonymous variations as well. Here, we present a new module in the MaxQuant software that takes both DNA and RNA based next-generation sequencing (NGS) data as well as raw proteomics data as input. This allows for the identification of variant peptides that are otherwise missed.

Keywords: Immunopeptidomics; MaxQuant; NGS; Proteogenomics; Proteomics; Sequence variations.

MeSH terms

Genomics*
High-Throughput Nucleotide Sequencing
Peptides / genetics
Proteomics* / methods
Software

Substances

Peptides