How to get the differential abundant taxa of the first time point in time series analysis

Question

[leranwangcs]

Hi,

I'm trying to use Deseq2 to do time course analysis. But I'm not sure what is the correct way to design the formula.

Below are the two variables that I used in the model:

Disease_status variable contains two levels: case and control, month variable contains 6 levels: 12, 18, 30, 36, 48, 56,

And my goal is to find the differential abundant taxa between case and control at each time point,

My model is as below:

ddsTC <- DESeqDataSetFromMatrix(countData = count.family + 1,
                                                               colData = metadata.final.deseq,
                                      design = ~ Disease_status + month + Disease_status:month)

ddsTC <- DESeq(ddsTC, test="LRT", reduced = ~ Disease_status + month)

But the outputs confused me at two points:

1. the result for the first timepoint (month 12) is not there.
2. the results include the comparisons of case vs control, and the comparison between month 12 vs each of the other timepoint indicivually. But I'm not really interested in those comparisons since they don't make much sense biologically.

So my question is: how to adjust my model to get me the results of only the comparison between case and control at each timepoint, and to also include the result from the first timepoint (month 12) as well?

I'm thinking if I should modify the model to:

ddsTC <- DESeqDataSetFromMatrix(countData = count.family + 1,
                                                                   colData = metadata.final.deseq,
                                          design = ~ Disease_status:month)

ddsTC <- DESeq(ddsTC, test="LRT", reduced = ~ 1)

Does this model make sense?

Thanks! Leran