Partek^® Flow^® provides  offers the DESeq2 method for differential expression detection, the . The implementation details of this algorithm for DESeq2 can be found at : http://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#the-deseq2-modelthe external DESeq2 documentation page, which includes changes made by the algorithm authors since the publication of the original manuscript (Love, Huber, and Anders 2014).  

The DESeq2 task can be invoked from the data node nodes generated from quantification task, it by quantification tasks that contains raw read count values of for each feature in each sample . Normalized counts is not appropriate to perform DESeq2 since DESeq2 model (Gene counts, Transcript counts, microRNA counts, etc.). DESeq2 cannot be run on a normalized counts data node because DESeq2 internally corrects for library size.

 If the value of the raw count has includes a decimal pointfraction, the value will be rounded to an integer be fore before DESeq2 is performed.

Configuring DESeq2

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Categorical and numeric attributes, as well as interaction terms can be added to the DESeq2 model. The DESeq2 configuration dialog for adding attributes and interactions to the model is very similar to the ANOVA configuration dialog, both categorical and numeric attributes can be added into the model. Interaction terms can also be added to the model, however, in order to perform contrast of the interaction term. However, DESeq2 has two important limitations not shared by GSA or ANOVA.

First, interaction terms cannot be added to contrasts in DESeq2. In order to perform contrasts of an interaction term in DESeq2, a new attribute that combines the factors of interest should must be added , and the contrast can be performed on the new combined attribute ( http://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#interactions).Another difference in configuration from ANOVA dialog is that, in the Define comparisons page, DESeq2 only allow to select one subgroup name to move it to the right panel while ANOVA allow you to pool multiple subgroups to perform the comparison.. This limitation of DESeq2 is detailed in the official DESeq2 documentation page. To perform contrasts of interaction terms without creating new combined attributes, please use either the GSA or ANOVA method.

Second, DESeq2 only allows two subgroups to be compared in each contrast. To analyze multiple subgroups, please use either the GSA or ANOVA method. 

DESeq2 report

The report of DESeq produced by DESeq2 is similar to the ANOVA report, each ; each row is a feature , each contrast reports and columns include p-value, FDR p-value and fold change in linear scale for each contrast.

References

Love MI, Huber W, and Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 2014l 15(12): 550.