Brain data, particualrly human brain data have very heterogeneus cell types, so it's important to normalise by cell type/add proportoins of different cell types to the formula when performing differential expression. We have some bulk RNA-seq brain data from disease samples and wildtypes. I have used the package BrainInABlender to get a matrix of the proportions of each cell type in each sample
|Cell type||Sample_1||Sample 2|
The rows are the types of cells, the columns are the samples. I wanted to know what's the best way to add this as a confounding variable in Enrichment Browser (or if that's not possible in DESeq2).
Edit: Current way I've tried to correct for this is in DESeq2. I have transposed the matrix of cell type proportoins then set DESeq's formula:
~ Condition + Condition:Neuron:Microglia:etc
This has drastically reduced the number of genes found to be differentially expressed but I don't know if it's the right way to do it.
Edit 2: When I tried removing the interaction terms, replacing them with +
~ Condition + Neuron + Microglia etc
As suggested on the Bioconductor support section the number of genes went up by an order of magnitude from just using condition which is the opposite of what should have happened. This persisted whether condition was at the start or end of my formula.