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Old 07-17-2015, 11:46 AM   #3
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Location: UK

Join Date: Jan 2015
Posts: 9

Thanks, Michael.

So it is clear to me now that the dispersion values are now per-gene, so gene-est-only no longer applies.

Quoting from the paper:

Many methods for differential expression analysis of RNA-seq data perform such information sharing across genes for variance (or, equivalently, dispersion) estimation. edgeR[2],[3] moderates the dispersion estimate for each gene toward a common estimate across all genes, or toward a local estimate from genes with similar expression strength, using a weighted conditional likelihood. Our DESeq method [4] detects and corrects dispersion estimates that are too low through modeling of the dependence of the dispersion on the average expression strength over all samples.

What about estimating the dispersions within each condition instead of across all samples? (per-condition)?

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