NPS: scoring and evaluating the statistical significance of peptidic natural product-spectrum matches.
Journal
Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944
Informations de publication
Date de publication:
15 07 2019
15 07 2019
Historique:
entrez:
13
9
2019
pubmed:
13
9
2019
medline:
13
6
2020
Statut:
ppublish
Résumé
Peptidic natural products (PNPs) are considered a promising compound class that has many applications in medicine. Recently developed mass spectrometry-based pipelines are transforming PNP discovery into a high-throughput technology. However, the current computational methods for PNP identification via database search of mass spectra are still in their infancy and could be substantially improved. Here we present NPS, a statistical learning-based approach for scoring PNP-spectrum matches. We incorporated NPS into two leading PNP discovery tools and benchmarked them on millions of natural product mass spectra. The results demonstrate more than 45% increase in the number of identified spectra and 20% more found PNPs at a false discovery rate of 1%. NPS is available as a command line tool and as a web application at http://cab.spbu.ru/software/NPS. Supplementary data are available at Bioinformatics online.
Identifiants
pubmed: 31510666
pii: 5529154
doi: 10.1093/bioinformatics/btz374
pmc: PMC6612854
doi:
Substances chimiques
Biological Products
0
Peptides
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
i315-i323Informations de copyright
© The Author(s) 2019. Published by Oxford University Press.
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