NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses.
Journal
Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011
Informations de publication
Date de publication:
20 08 2020
20 08 2020
Historique:
accepted:
08
06
2020
revised:
20
04
2020
received:
18
02
2020
pubmed:
12
6
2020
medline:
29
9
2020
entrez:
12
6
2020
Statut:
ppublish
Résumé
Mass spectrometry (MS)-based quantitative proteomics experiments frequently generate data with missing values, which may profoundly affect downstream analyses. A wide variety of imputation methods have been established to deal with the missing-value issue. To date, however, there is a scarcity of efficient, systematic, and easy-to-handle tools that are tailored for proteomics community. Herein, we developed a user-friendly and powerful stand-alone software, NAguideR, to enable implementation and evaluation of different missing value methods offered by 23 widely used missing-value imputation algorithms. NAguideR further evaluates data imputation results through classic computational criteria and, unprecedentedly, proteomic empirical criteria, such as quantitative consistency between different charge-states of the same peptide, different peptides belonging to the same proteins, and individual proteins participating protein complexes and functional interactions. We applied NAguideR into three label-free proteomic datasets featuring peptide-level, protein-level, and phosphoproteomic variables respectively, all generated by data independent acquisition mass spectrometry (DIA-MS) with substantial biological replicates. The results indicate that NAguideR is able to discriminate the optimal imputation methods that are facilitating DIA-MS experiments over those sub-optimal and low-performance algorithms. NAguideR further provides downloadable tables and figures supporting flexible data analysis and interpretation. NAguideR is freely available at http://www.omicsolution.org/wukong/NAguideR/ and the source code: https://github.com/wangshisheng/NAguideR/.
Identifiants
pubmed: 32526036
pii: 5856122
doi: 10.1093/nar/gkaa498
pmc: PMC7641313
doi:
Substances chimiques
Protein Precursors
0
Formaldehyde
1HG84L3525
Nocodazole
SH1WY3R615
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e83Informations de copyright
© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.
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