Avant-garde: an automated data-driven DIA data curation tool.
Journal
Nature methods
ISSN: 1548-7105
Titre abrégé: Nat Methods
Pays: United States
ID NLM: 101215604
Informations de publication
Date de publication:
12 2020
12 2020
Historique:
received:
18
02
2019
accepted:
25
09
2020
pubmed:
18
11
2020
medline:
9
2
2021
entrez:
17
11
2020
Statut:
ppublish
Résumé
Several challenges remain in data-independent acquisition (DIA) data analysis, such as to confidently identify peptides, define integration boundaries, remove interferences, and control false discovery rates. In practice, a visual inspection of the signals is still required, which is impractical with large datasets. We present Avant-garde as a tool to refine DIA (and parallel reaction monitoring) data. Avant-garde uses a novel data-driven scoring strategy: signals are refined by learning from the dataset itself, using all measurements in all samples to achieve the best optimization. We evaluate the performance of Avant-garde using benchmark DIA datasets and show that it can determine the quantitative suitability of a peptide peak, and reach the same levels of selectivity, accuracy, and reproducibility as manual validation. Avant-garde is complementary to existing DIA analysis engines and aims to establish a strong foundation for subsequent analysis of quantitative mass spectrometry data.
Identifiants
pubmed: 33199889
doi: 10.1038/s41592-020-00986-4
pii: 10.1038/s41592-020-00986-4
pmc: PMC7723322
mid: NIHMS1632766
doi:
Substances chimiques
Peptides
0
Proteome
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
1237-1244Subventions
Organisme : NCI NIH HHS
ID : U24 CA210986
Pays : United States
Organisme : NHGRI NIH HHS
ID : U54 HG008097
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA210979
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA214125
Pays : United States
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