Dear all,

I would need to analyze the following dataset with DESeq2:

labels  cellline    experiment  treatment
A1  A   batch1  control
A2  A   batch1  treated
B1  B   batch1  control
B2  B   batch1  treated
C1  C   batch1  control
C2  C   batch1  treated
D1  D   batch1  control
D2  D   batch1  treated
E1  E   batch1  control
E2  E   batch1  treated
F1  F   batch1  control
F2  F   batch1  treated
G1  G   batch2  control
G2  G   batch2  treated
H1  H   batch2  control
H2  H   batch2  treated
I1  I   batch2  control
I2  I   batch2  treated
J1  J   batch2  control
J2  J   batch2  treated
K1  K   batch2  control
K2  K   batch2  treated
L1  L   batch2  control
L2  L   batch2  treated

here's my model:

dds <- DESeqDataSetFromMatrix(countData = readcounts, colData = infoInd, 
                              design = ~ cellline + experiment + cellline:experiment + treatment)

But I get the following error message:

Error in checkFullRank(modelMatrix) : 
  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.

How to measure the effect of the treatment given that:

• my data were collected in 2 experiments (batch1 and batch2)
• different cell lines have been used (A, B, C, etc.)
• different cell lines have been used in my 2 experiments

Many thanks for your feedback

Statistical analysis is up to you, and I don't have time to provide consultation here. So you can consult with a statistician to arrive at an appropriate analysis plan.

I'll just note that experiment is perfectly confounded with cell line, so you can't simply include both in the design as this leads to the error (there is discussion of this in the DESeq2 vignette).