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Wieczorek S, Combes F, Lazar C, Giai Gianetto Q, Gatto L, Dorffer A, Hesse AM, Couté Y, Ferro M, Bruley C, Burger T. DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics. Bioinformatics 2016; 33:135-136. [PMID: 27605098 PMCID: PMC5408771 DOI: 10.1093/bioinformatics/btw580] [Citation(s) in RCA: 177] [Impact Index Per Article: 22.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Revised: 07/05/2016] [Accepted: 09/02/2016] [Indexed: 11/30/2022] Open
Abstract
Summary DAPAR and ProStaR are software tools to perform the statistical analysis of label-free XIC-based quantitative discovery proteomics experiments. DAPAR contains procedures to filter, normalize, impute missing value, aggregate peptide intensities, perform null hypothesis significance tests and select the most likely differentially abundant proteins with a corresponding false discovery rate. ProStaR is a graphical user interface that allows friendly access to the DAPAR functionalities through a web browser. Availability and implementation DAPAR and ProStaR are implemented in the R language and are available on the website of the Bioconductor project (http://www.bioconductor.org/). A complete tutorial and a toy dataset are accompanying the packages.
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Affiliation(s)
- Samuel Wieczorek
- Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.,CEA, BIG-BGE, Grenoble, 38000, France.,INSERM, BGE, Grenoble, 38000, France
| | - Florence Combes
- Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.,CEA, BIG-BGE, Grenoble, 38000, France.,INSERM, BGE, Grenoble, 38000, France
| | - Cosmin Lazar
- Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.,CEA, BIG-BGE, Grenoble, 38000, France.,INSERM, BGE, Grenoble, 38000, France
| | - Quentin Giai Gianetto
- Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.,CEA, BIG-BGE, Grenoble, 38000, France.,INSERM, BGE, Grenoble, 38000, France
| | - Laurent Gatto
- Computational Proteomics Unit, Cambridge, CB2 1GA, UK.,Cambridge Center for Proteomics, Cambridge, CB2 1GA, UK
| | - Alexia Dorffer
- Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.,CEA, BIG-BGE, Grenoble, 38000, France.,INSERM, BGE, Grenoble, 38000, France
| | - Anne-Marie Hesse
- Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.,CEA, BIG-BGE, Grenoble, 38000, France.,INSERM, BGE, Grenoble, 38000, France
| | - Yohann Couté
- Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.,CEA, BIG-BGE, Grenoble, 38000, France.,INSERM, BGE, Grenoble, 38000, France
| | - Myriam Ferro
- Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.,CEA, BIG-BGE, Grenoble, 38000, France.,INSERM, BGE, Grenoble, 38000, France
| | - Christophe Bruley
- Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.,CEA, BIG-BGE, Grenoble, 38000, France.,INSERM, BGE, Grenoble, 38000, France
| | - Thomas Burger
- Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.,CEA, BIG-BGE, Grenoble, 38000, France.,INSERM, BGE, Grenoble, 38000, France.,CNRS, BIG-BGE, Grenoble, 38000, France
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