Hi Michael,

On Jun 10, 2013 8:15 PM, "Michael Muratet" <mmuratet@hudsonalpha.org> wrote:
>
> Greetings
>
> I am working on analyzing the data from an experiment with multiple
technical replicates but no biological replicates. FWIW, it's the same data
set I have posted about in recent weeks. I think the experiment would
benefit greatly from some biological replicates. The question I have is
this: given that the dispersion estimator algorithm is able to 'share' data
among samples, does anyone know of any experiments or simulations to
establish guidelines for a minimum or recommended number of biological
replicates smaller than all N samples?

The power, or ability to detect true differential expression for a gene, is
dependent on the sample size, but all also on the true log fold change. You
could try using the makeExampleDESeqDataSet() function to simulate some
data, which has a number of tunable parameters, in order to simulate
different effect sizes and test power.

>The DESeq2 manual says that it employs Cox-Reid for estimating
dispersions, is it same implementation as described in McCarthy et al.,
2012, or are there some new twists?

The Cox Reid term is the same, but the method of information sharing across
the gene estimates is different. This is described in the man page for
estimateDispersions().

Mike

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