I am having troubles with the DESeq2 analysis of time course experiments and was thinking someone could point me to the right direction.
I have 3 different conditions. For conditions 1 and 2 there are time points 0, 8, 16, 24, 48, 72 hours. For condition 3 there are time points 0, 8, 24, 48, 72, 96, 120 hours.
While trying to design a model
DESeqDataSet(dataset, ~condition + time + condition:time) as described here (in the time course section), DESeq2 throws an error
"..the model matrix is not full rank, so the model cannot be fit as specified.
Levels or combinations of levels without any samples have resulted in
column(s) of zeros in the model matrix".
I guess this is because some of the conditions do not have all the time points?
I tried the following:
model <- model.matrix(~condition + time + condition:time, colData(data_dds))
and removing the columns that have only zeros, but since I do not see all the conditions in this model matrix (the first one is always hidden), supplying this matrix to DESeqDataSet gives the same error.
Is there a way to make such a model?
Are there any alternative ways to test condition-specific and time/timepoint-specific effects?