Dear Community,

I am new to do differential gene expression analysis uisng DESeq2. I have a set of 380 genes sequenced and i ran DESeq2 to find genes significantly expressed. However i read that DESeq2 is more suitable for whole genome expression analysis.

Is it OK to use DESeq2 for targeted gene expression analysis like i did only with around 380 genes.

Small number of genes is affecting in anyway the procedure of diffrential expression analysis method??

Kindly write down your experiences and share your ideas.

Thank you so much,

Suranandbabu,

MPZ, Heidelberg.

Germany.

There are two primary concerns when analyzing a smaller number of genes. The first question is whether you have enough genes to estimate a robust dispersion trend. I think 380 genes should suffice for this. The second question is whether your targeted set of genes satisfies the criteria for the normalization method you are using. Typically, normalization methods for RNA-seq assume that a majority of genes are not differentially expressed, and/or that differential expression is approximately equally split between positive and negative changes. A whole transcriptome analysis usually satisfies these criteria, but a targeted analysis frequently fails these criteria by design, since it would make little sense to target a majority of genes for which you expect no differential expression. If the changes are balanced, you may still be able to use the standard normalization methods. Otherwise, you may need to select a set of control genes a priori and use these to normalize the entire data set.

Dear Ryan C Thompson,

Thank you so much. It is really helpful.

Dear Ryan C Thompson,

Thank you so much. It is really helpful.