Efficient indexing of peptides for database search using Tide

• Published in: bioRxiv
• Main Authors: Adoquaye Acquaye, Frank Lawrence Nii, Kertesz-Farkas, Attila, Noble, William Stafford
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 01.10.2022; Cold Spring Harbor Laboratory
• Edition: 1.1
• Subjects: Bioinformatics; Digestion; Mass spectroscopy; Peptides; Post-translation; Search engines; Statistics
• ISSN: 2692-8205; 2692-8205
• DOI: 10.1101/2022.09.30.510396

The first step in the analysis of protein tandem mass spectrometry data typically involves searching the observed spectra against a protein database. During database search, the search engine must digest the proteins in the database into peptides, subject to digestion rules that are under user control. The choice of these digestion parameters, as well as selection of post-translational modifications (PTMs), can dramatically affect the size of the search space and hence the statistical power of the search. The Tide search engine separates the creation of the peptide index from the database search step, thereby saving time by allowing a peptide index to be reused in multiple searches. Here we describe an improved implementation of the indexing component of Tide that consumes around four times less resources (CPU and RAM) than the previous version and can generate arbitrarily large peptide databases, limited by only the amount of available disk space. We use this improved implementation to explore the relationship between database size and the parameters controlling digestion and PTMs, as well as database size and statistical power. Our results can help guide practitioners in proper selection of these important parameters. Competing Interest Statement The authors have declared no competing interest. Footnotes * http://crux.ms