alexa Large Scale Statistical Analysis of GEO Datasets
ISSN: 2329-6682

Gene Technology
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Research Article

Large Scale Statistical Analysis of GEO Datasets

Bernard Ycart1,2,3,*, Konstantina Charmpi1,2,3, Sophie Rousseaux1,4 and Jean-Jacques Fournié3,5,6,7
1Université Grenoble Alpes, France
2Laboratoire Jean Kuntzmann, CNRS UMR5224, Grenoble, France
3Laboratoire d’Excellence TOUCAN, France
4INSERM, UMR823, Institut Albert Bonniot, Grenoble, France
5INSERM UMR1037-Cancer Research Center of Toulouse, Toulouse, France
6Université Toulouse III Paul-Sabatier, Toulouse, France
7ERL 5294 CNRS, Toulouse, France
Corresponding Author : Bernard Ycart
Laboratoire Jean Kuntzmann
Université Grenoble Alpes
CNRS UMR5224, France
Tel: +33 4 76 51 49 95
E-mail: [email protected]
Received May 20, 2014; Accepted June 22, 2014; Published July 30, 2014
Citation: Ycart B, Charmpi K, Rousseaux S, Fournié JJ (2015) Large Scale Statistical Analysis of GEO Datasets. Gene Technology 4:113. doi:10.4172/2329-6682.1000113
Copyright: © 2015 Ycart B et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
 
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Abstract

The problem addressed here is that of simultaneous treatment of several gene expression datasets, possibly collected under different experimental conditions and/or platforms. Using robust statistics, a large scale statistical analysis has been conducted over 20 datasets downloaded from the Gene Expression Omnibus repository. The differences between datasets are compared to the variability inside a given dataset. Evidence that meaningful biological information can be extracted by merging different sources is provided.

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