MSFragger: ultrafast and comprehensive peptide identification in shotgun proteomics

There is a need to better understand and handle the “dark matter” of proteomics – the vast diversity of post-translational and chemical modifications that are unaccounted in a typical analysis and thus remain unidentified. We present a novel fragment-ion indexing method, and its implementation in pe...

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Veröffentlicht in:Nature methods 2017-04, Vol.14 (5), p.513-520
Hauptverfasser: Kong, Andy T., Leprevost, Felipe V., Avtonomov, Dmitry M., Mellacheruvu, Dattatreya, Nesvizhskii, Alexey I.
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container_end_page 520
container_issue 5
container_start_page 513
container_title Nature methods
container_volume 14
creator Kong, Andy T.
Leprevost, Felipe V.
Avtonomov, Dmitry M.
Mellacheruvu, Dattatreya
Nesvizhskii, Alexey I.
description There is a need to better understand and handle the “dark matter” of proteomics – the vast diversity of post-translational and chemical modifications that are unaccounted in a typical analysis and thus remain unidentified. We present a novel fragment-ion indexing method, and its implementation in peptide identification tool MSFragger, that enables an over 100-fold improvement in speed over most existing tools. Using some of the largest proteomic datasets to date, we demonstrate how MSFragger empowers the open database search concept for comprehensive identification of peptides and all their modified forms, uncovering dramatic differences in the modification rates across experimental samples and conditions. We further illustrate its utility using protein-RNA crosslinked peptide data, and using affinity purification experiments where we observe on average a 300% increase in the number of identified spectra for enriched proteins. We also discuss the benefits of open searching for improved false discovery rate estimation in proteomics.
doi_str_mv 10.1038/nmeth.4256
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