I'm using limma in Bioconductor for differential expression analysis of an Affymetrix data set. The goal is to determine the genes that are differentially regulated with the overexpression of an insert gene via a viral vector. The design is such that we have four sets of arrays- vector only, no vector, overexpressed gene (via vector), no inserted gene (but still has vector). This is so that we can account for the expression of the vector itself if there ends up being variation between the viral expression with the insert and without the insert.
It seems like I should be able to setup the contrasts similarly to 'factorial designs'- so my contrasts now are: vecvsnovec = vector - vectorcontrol, insertvsno.insert = insert - no.insert, diffinsertvs_vec = (insert - no.insert) - (vector - vectorcontrol)
Does this make any sense? Now I'm almost thinking that I could probably just do insert vs no insert and leave it at that, to avoid the possibility of overcompensating. At least with the contrast design above, I could just use that one contrast.
Sorry for the vague descriptions, but any input is appreciated.
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What is the difference in your experiment between 'vector only' and 'no inserted gene (but still has the vector)'?
It looks like I was interpreting the experiment wrong...
I think you have only 2 controls vector only = no inserted gene (but still has vector) and no vector, or do you cut the vector and re-ligate for no inserted gene as control for your construct. For protein overexpression, you could expect at least a pathway enrichment, is like you drive the cell over the process involved for that overexpressed gene, so you may be not find any changes when you transfect an empty vector. so maybe you only need this contrast
diffinsertvs_vec = (insert - no.insert)if you not see any significant changes invecvsnovec = vector - vectorcontrol