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Bioinformatics. 2017 Jan 1;33(1):135-136. doi: 10.1093/bioinformatics/btw580. Epub 2016 Sep 6.

DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics.

Wieczorek S1,2,3, Combes F1,2,3, Lazar C1,2,3, Giai Gianetto Q1,2,3, Gatto L4,5, Dorffer A1,2,3, Hesse AM1,2,3, Couté Y1,2,3, Ferro M1,2,3, Bruley C1,2,3, Burger T1,2,3,6.

Author information

1
Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.
2
CEA, BIG-BGE, Grenoble, 38000, France.
3
INSERM, BGE, Grenoble, 38000, France.
4
Computational Proteomics Unit, Cambridge, CB2 1GA, UK.
5
Cambridge Center for Proteomics, Cambridge, CB2 1GA, UK.
6
CNRS, BIG-BGE, Grenoble, 38000, France.

Abstract

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.

CONTACT:

samuel.wieczorek@cea.fr, florence.combes@cea.fr, thomas.burger@cea.fr.

PMID:
27605098
PMCID:
PMC5408771
DOI:
10.1093/bioinformatics/btw580
[Indexed for MEDLINE]
Free PMC Article

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