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Journal Articles Briefings in Bioinformatics Year : 2012

A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis

Andrea Rau
Julie Aubert
Céline Keime
Jordi Estellé
Bernd Jagla
  • Function : Author
  • PersonId : 1073181
  • IdHAL : bernd-jagla
Denis Laloë
Caroline Le Gall
  • Function : Author
Brigitte Schaeffer
  • Function : Author
Stéphane Le Crom
Mickaël Guedj
  • Function : Author

Abstract

During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data.

Dates and versions

hal-00782486 , version 1 (29-01-2013)

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Cite

Marie-Agnès Dillies, Andrea Rau, Julie Aubert, Christelle Hennequet-Antier, Marine Jeanmougin, et al.. A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis. Briefings in Bioinformatics, 2012, 14 (6), pp.671-683. ⟨10.1093/bib/bbs046⟩. ⟨hal-00782486⟩
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