I am using deseq2 to find differential significant taxa (count data). The data is longitudinal and three groups of mice and I am using sth like

`diagdds = phyloseq_to_deseq2(physeq.fecal, ~ condition + week_experiment +`

team + condition:week_experiment)

since I have three groups, I wonder how DEseq2 is calculating the fold change and p-value !? There is neither any warning nor any error ! should I slice the data 3 different combination of each group ?!

The second question I have is about `condition:week_experiment term. `

I wonder how I can set it up in a way that two groups have the same initial value at the beginning (same intercept).

condition specifies the difference across three conditions at time=0,

week gives the difference across time for the reference condition

team accounts for differences in the team variable

and condition:week creates terms which provide for condition-specific differences at each time point after time=0.

You can use a likelihood ratio test, removing the interaction term, to find taxa where there are any condition-specific differences over time. We have a time series example in the workflow.

http://www.bioconductor.org/help/workflows/rnaseqGene/