I have Bulk-RNAseq data from 3 drug exposures (vehicle, low and high dose) x 2 replicates per condition x 6 cell lines. So its a total of 36 samples.

I am interested in the Exposure effect.

I am using DuplicateCorrelation and limma voom, but my cell Line effect is eating all the effect (seen by variant partition).

info <- # is the metadata table
genes <- # counts table, rows are genes, columns are samples

design <- model.matrix( ~ Exposure+ CellLine ,info)

vobj_tmp = voom( genes, design, plot=TRUE)

dupcor <- duplicateCorrelation(vobj_tmp,design,block=info$SampleID)  # I am blocking by sample,  meaning each 2 replicates per condition

vobj = voom( genes, design, plot=TRUE, block=info$SampleID, correlation=dupcor$consensus)

fitDupCor <- lmFit(vobj, design, block=info$SampleID, correlation=dupcor$consensus.correlation)

fitDupCor <- eBayes( fitDupCor )

I got no significance because the effect of the cell lines i hugh (as I observed before in VariantPartition).

1) Am I using the blocking correctly? Or should I block by sampleID in duplicateCorrelation but block by CellLine in voom() ?

2) Is it correctly to use Variant Partition even considering the replicates as independent samples? I am not using duplicateCorrelation for Variant Partition.

gExpr <- DGEList(counts=counts)

gExpr <- calcNormFactors(gExpr)

design <- model.matrix( ~ Exposure+ CellLine ,info)

vobjGenes <- voom(gExpr, design)

geneExpres <-vobjGenes$E

varPart <- fitExtractVarPartModel( vobjGenes, form, info )

vp <- sortCols(varPart)

3) Any other idea on how can I rescue the exposure effect?

Thanks in advance Gimena

If you have complete cases, cell line will be orthogonal to the treatment effect, so the fact that most of the variation is due to cell line should have no effect on being able to detect differences in exposure. Also, you should probably use voomLmFit instead.

fit <- eBayes(voomLmFit(gExpr, design, block = info$SampleID))
topTable(fit, 2)
topTable(fit, 3)

It is not clear to me why you are using duplicateCorrelation at all. None of the information you give about your experiment suggests any random effect or blocking. It is not clear what you mean by "replicates" or why they would not be independent samples.