This is a test version of Biostars. For the public version, visit https://www.biostars.org.
DESeq2 Normalization of time course

Hi,

I am new to DESeq2 analysis. I have RNASeq raw count data from three different time points namely 0h, 5h, 1d. Every time point has triplicates for Control samples, Treatment-A, Treatment-B, Treatment-C. All I want to find is the differential expressed genes between Treated against Control samples(Treatment-A vs Control; Treatment-B vs Control; Treatment-C vs Control) within every time point. Now I would like to know whether , I should load raw counts of all the samples from all time points together into DESeq2 pipeline and compute diff. expression analysis OR load only the raw counts of particular time point(i.e. Control_0h, Treatment-A_0h, Treatment-B_0h and Treatment-C_0h) separately and perform differential gene expression analysis. Kindly guide me

deseq2 rna-seq normalization
• 2,807 views • link
updated by bioinfo17 • bioinfo17 • written by EVR EVR

2 answers

In my opinion, it is best to load all the data because the estimation of the dispersion and of the variance-mean dependance will be more robust.

There is also this related post.

• 0 views • link
written by Carlo Yague Carlo Yague

hi EVR, I am after a similar analysis, would be great if you could share the deseq2 R script - thanks

• 0 views • link
written by bioinfo17 • bioinfo17

Log in to answer this question.

More posts like this