Journal
BRIEFINGS IN BIOINFORMATICS
Volume 14, Issue 6, Pages 671-683Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bib/bbs046
Keywords
high-throughput sequencing; RNA-seq; normalization; differential analysis
Funding
- Groupe de Rercherche Bioinformatique Moleculaire (GdR BiM)
- DIM STEM-Pole fellowship
- Association Francaise contre les Myopathies
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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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