期刊
BIOINFORMATICS
卷 36, 期 10, 页码 3148-3155出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btaa118
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资金
- French National Agency for Research (ANR) [ANR-10-INBS-08]
- ProFI project, 'Infrastructures Nationales en Biologie et Sante'
- 'Investissements d'Avenir'call
Motivation: The proteomics field requires the production and publication of reliable mass spectrometry-based identification and quantification results. Although many tools or algorithms exist, very few consider the importance of combining, in a unique software environment, efficient processing algorithms and a data management system to process and curate hundreds of datasets associated with a single proteomics study. Results: Here, we present Proline, a robust software suite for analysis of MS-based proteomics data, which collects, processes and allows visualization and publication of proteomics datasets. We illustrate its ease of use for various steps in the validation and quantification workflow, its data curation capabilities and its computational efficiency. The DDA label-free quantification workflow efficiency was assessed by comparing results obtained with Proline to those obtained with a widely used software using a spiked-in sample. This assessment demonstrated Proline's ability to provide high quantification accuracy in a user-friendly interface for datasets of any size.
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