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.