[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,
Cheers,
Marie
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