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The DESeq2(R) task can be invoked from data nodes generated by quantification tasks that contains raw read count values for each feature in each sample (Gene counts, Transcript counts, microRNA counts, etc.). DESeq2(R) cannot be run on a normalized counts data node because DESeq2 DESeq(2) internally corrects for library size and implements a low expression filter.

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In DESeq2 advanced options configure dialog, there is reference selection option:

A reference level should be is specified for each categorical factor in the model , and the result will be different when choose different reference levels.may be dependent on the choice. In R, the reference level is typically chosen by default whenever a categorical factor is present in the model. This Flow option was created to allow the user to specify exactly the same reference level as in her R script, if need be.

DESeq2/DESeq2(R) report

The report produced by DESeq2 is similar to the ANOVA report; each row is a feature and columns include p-value, FDR p-value, and fold change in linear scale for each contrast. However DESeq2(R) report doesn't have LSMeans information on the compared groups.

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