When calculating the dispersion DESeq2 will only give one dispersion value for each gene, as can also be seen in the dispersion plot. I don't have much knowledge about statistics, but as far as I know we basically want to compare a distribution from condition 1 vs condition 2 and see whether there is a significant difference, as depicted here (Imgur link). So I would expect that there would be two dispersion calculation one for each condition (in a two condition experiment). I could imagine that one would say that this could be generalized over the conditions but why would this be the case? Let's say the expression of gene X is low in condition 1 then it could have high variablity, whereas gene X may be highly expressed in condition 2 and having low variability. Then combining these into one dispersion esitimate would probably underestimate the dispersion for condition 1 and overestimate if for condition2. Note again I have little knowledge about statistics, thus what am I missing here?
(Although a similar question was asked on biostars: Question: DESeq2: Is dispersion estimation gene-wise or gene- and condition-wise? I still cannot understand it)