[BioC] How to use DESeq to normalize and estimate variance in a RNAseq timecourse analysis

Marie Sémon marie.semon at ens-lyon.fr
Wed May 9 22:03:55 CEST 2012

Dear all,

We are using DESeq to analyse differential expression in a RNAseq 
timecourse analysis (5 time points after treatment + control).
The dataset contains 3 replicates for the control, and single measures 
for each time point. For each timepoint, we aim to extract differentially
expressed genes relative to control.

We are wondering what is the best procedure to prepare this dataset for 
this analysis (steps of normalization + variance estimation):
1) is it better to start with normalizing + estimating dispersion on the 
whole dataset (5 points + 3 controls), and then to test for differential 
expression in
the two by two comparisons just mentionned
2) or is it better to normalize + estimate dispersion on restricted 
datasets composed of 1 time-point + 3 controls, and then test for 
differential expression between this time point and the controls.

It seems to us that the first procedure is better, because it may be 
less sensitive to outliers. But we would be grateful to have your 
enlightened input.

Thank you very much in advance,



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