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DESeq2 task, on the other hand, is a Partek Flow native implementation of DESeq2 differential expression detection algorithm, it is much faster than DESeq2(R). Like GSA and ANOVA, before you run this task, we recommend that you first remove (filter out) features expressed at a low level and then perform normalization using Median ratio (DESeq2 only). 

Note: DESeq2 differential analysis can only be performed on the following normalization output data node, those methods can produce library sizes:

TMM, CPM, Upper Quartile, Median ratio, Postcounts

Installation of R is not required to run DESeq2 task.

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