In papyro comparison of TMM (edgeR), RLE (DESeq2), and MRN normalization methods for a simple two-conditions-without-replicates RNA-Seq experimental design

Elie Maza (1)

1 GBF - Génomique et Biotechnologie des Fruits

In the past 5 years, RNA-Seq has become a powerful tool in transcriptome analysis even though computational methods dedicated to the analysis of high-throughput sequencing data are yet to be standardized. It is, however, now commonly accepted that the choice of a normalization procedure is an important step in such a process, for example in differential gene expression analysis. The present article highlights the similarities between three normalization methods: TMM from edgeR R package, RLE from DESeq2 R package, and MRN. Both TMM and DESeq2 are widely used for differential gene expression analysis. This paper introduces properties that show when these three methods will give exactly the same results. These properties are proven mathematically and illustrated by performing in silico calculations on a given RNA-Seq data set.

Mots clés: RNA-seq data; Normalization; Comparison of methods; DESeq2; edgeR

Domaines: Biochimie, Biologie Moléculaire; Génomique, Transcriptomique et Protéomique [q-bio.GN]

Elie Maza. In papyro comparison of TMM (edgeR), RLE (DESeq2), and MRN normalization methods for a simple two-conditions-without-replicates RNA-Seq experimental design. Frontiers in Genetics, 2016, vol. 7 (n° 164), pp.0. ⟨10.3389/fgene.2016.00164⟩. ⟨hal-01494988⟩