Originally posted by a_mt
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From the DESeq paper:
"However, it has been noted [1,8] that the assumption of Poisson distribution is too restrictive: it predicts smaller variations than what is seen in the data. Therefore, the resulting statistical test does not control type-I error (the probability of false discoveries) as advertised."
In other words, the Poisson distribution leads to false positives and is not suitable. That is why DESeq is based on a Negative Binomial, not a Poisson distribution:
"To address this so-called overdispersion problem, it has been proposed to model count data with negative binomial (NB) distributions [9], and this approach is used in the edgeR package for analysis of SAGE and RNA-Seq [8,10]."
The DESeq vignette provides protocols for analyzing data without technical replicates.
Go here: http://bioconductor.org/packages/rel.../doc/DESeq.pdf
and read section 3.3 titled "Working without any replicates." That will tell you how to do this in DESeq. The purpose of the VSD normalized data is to put everything on the same scale for clustering and other sorts of analysis, not for differential expression.
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