I have some RNAseq data from a peer. She only has three conditions - control, shRNA1 and shRNA2; shRNA1 or 2 means two independent experiments to introduce the shRNA to cells, and test for knockdown of genes. Unfortunately, she did not conduct a replicate. I.e., I only have three datasets for DESeq comparison.
I am able to run the Rsubread and categorize in the data.frame:
design_shrna=data.frame(batch=c("Ctrl", "shRNA1", "shRNA2"), treatment=c("untr", "tr", "tr"))
but I'm not able to run the DESeq, regardless of Walt or LRT tests:
dLRT <- DESeqDataSetFromMatrix(countData = counts, colData = design_shrna, design = ~ batch + treatment )
They will state this error:
Error in checkFullRank(modelMatrix) : the model matrix is not full rank, so the model cannot be fit as specified.
One or more variables or interaction terms in the design formula are linear
combinations of the others and must be removed.
Please read the vignette section 'Model matrix not full rank':
I read in the DESeq2 manual that DESeq works on duplicates. My questions are:
1) Is there any case where I can use DESeq2 without duplicates? How am I to go about doing it?
2) I tried the option ignoreRank = TRUE, but it still didn't work. Is this necessary in the first place?