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

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.
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Briefings in Bioinformatics, Oxford University Press (OUP), 2012, 14 (6), 〈10.1093/bib/bbs046〉
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https://hal.inria.fr/hal-00782486
Contributeur : Guillemette Marot <>
Soumis le : mardi 29 janvier 2013 - 18:18:42
Dernière modification le : vendredi 16 novembre 2018 - 02:11:20

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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, Oxford University Press (OUP), 2012, 14 (6), 〈10.1093/bib/bbs046〉. 〈hal-00782486〉

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