Update on the moFF Algorithm for Label-Free Quantitative Proteomics.
MS1-peptide intensity
bioinformatics tool
label-free quantification
singleton peptides
Journal
Journal of proteome research
ISSN: 1535-3907
Titre abrégé: J Proteome Res
Pays: United States
ID NLM: 101128775
Informations de publication
Date de publication:
01 02 2019
01 02 2019
Historique:
pubmed:
5
12
2018
medline:
20
2
2020
entrez:
5
12
2018
Statut:
ppublish
Résumé
moFF is a modular and operating-system-independent tool for quantitative analysis of label-free mass-spectrometry-based proteomics data. The moFF workflow, comprising matching-between-runs and apex quantification, can be applied to any upstream search engine's output, along with the corresponding Thermo or mzML raw file. We here present moFF 2.0, with improvements in speed through multithreading, the use of a new raw file access library, and a novel filtering approach in the matching-between-runs module. This filter allows moFF to correctly identify features that are present in one run but not in another, as demonstrated using spiked-in iRT peptides. Moreover, moFF 2.0 also provides a new peptide summary export that can be used in downstream statistical analysis. moFF is open source and freely available and can be downloaded from https://github.com/compomics/moFF.
Identifiants
pubmed: 30511867
doi: 10.1021/acs.jproteome.8b00708
doi:
Substances chimiques
Peptides
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
728-731Subventions
Organisme : NCI NIH HHS
ID : U24 CA199347
Pays : United States