Hi All,

In DESeq, if one data set has both technical and biological replicates, i am
curious how technical and biological replicates are distinguished in that
package. for instance, say, each biological replicate has two technical
replicates. T_b_1_t_1(cancer biological replicate 1, technical replicate1)
T_b_1_t_2,  T_b_2_t_1,  T_b_2_t_2  VS similarly Normal samples.

So. the main null hypothesis is no difference between tumor vs normal
group.(4 samples vs 4)

For such a case, when analyzing 8 samples together with the above
hypothesis,

Q1. for "conds" variable indicating the labels of samples mentioned in DESeq
manual, how do i have to define to distinguish tech vs biological
replicates?(edgeR can not do for such a data, i know that it is able to
treat only data with technical replicates rather than biological individuals
instead, yet, it seems DESeq is able to handle data set with biological
replicates without any additional variable of biological individual factor
as like GLM. In the paper, one of published data sets for such kind of type
data which has both tech and bio replicates was also analyzed: RNA-Seq of
yeast as real data application using DESeq)

Q2. If question one is doable in DESeq, it is also able to take experimental
effects(nuisance factors) such as library/flow cell/time point(if it is a
time series data set) as well as main hypothesis into account in DESeq?

Q3. when estimating size factors, Sj, it is using geometric mean
pseudo-reference as like quantile adjusted way in 2008 Robinson paper. so.
here i was wondering why it is taken by especially geometric mean rather
than just simple arithmetic mean(or median) or trimmed mean(or median). is
there any specific reason to take geometric mean in the estimation of size
factors here?


Thank you all in advance. S-

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