文章详情：Maza E (2016)
In Papyro Comparison of TMM (edgeR), RLE (DESeq2), and MRN Normalization Methods for a Simple Two-Conditions-Without-Replicates RNA-Seq Experimental Design.
Front Genet
7:164. [article]
一图概况如下：
文章提到了以下3个算法，做了一下测试数据的比较：
The first method is the “Trimmed Mean of
M
-values” normalization (TMM) described in and implemented in the edgeR package.
The second method is the “Relative Log Expression” normalization (RLE) implemented in the DESeq2 package.
The third method is the “Median Ratio Normalization” (MRN).
作者的测试数据是：a matrix of counts: 34675 rows (genes) and 9 columns (samples from 3 stages and 3 biological replicates per stage). 一个
in silico
calculations carried out on a given real data set from the tomato fruit set.
作者的结论很有意思：
For a very simple experimental design, i.e., about two conditions and no replicates, users can use any of the three studied normalization methods with no impact on results.
But, for a more complex experimental design, the MRN method could be adopted.
