Mokapot: Fast and Flexible Semisupervised Learning for Peptide Detection.

ABSTRACT: Proteomics studies rely on the accurate assignment of peptides to the acquired tandem mass spectra-a task where machine learning algorithms have proven invaluable. We describe mokapot, which provides a flexible semisupervised learning algorithm that allows for highly customized analyses. We demonstrate some of the unique features of mokapot by improving the detection of RNA-cross-linked peptides from an analysis of RNA-binding proteins and increasing the consistency of peptide detection in a single-cell proteomics study.

SUBMITTER: Fondrie WE 

PROVIDER: S-EPMC8022319 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature