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bioRxiv · 10.1101/2020.12.01.407270

mokapot: Fast and flexible semi-supervised learning for peptide detection

Fondrie, W. E.·Noble, W. S.
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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 semi-supervised 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.

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Fondrie, W. E., Noble, W. S.. 2020-12-02. mokapot: Fast and flexible semi-supervised learning for peptide detection. https://doi.org/10.1101/2020.12.01.407270

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