I use translating ribosome affinity purification (TRAP - the same principle as RiboTag) to extract translating mRNA from a specific cell type, where ribosomes are GFP-tagged. I have an RNA-seq dataset from TRAP-processed samples, that are enriched in genetic markers specific to this cell type. I want to study the effects of different conditions on this cell type through differential gene expression (DESeq2) and co-expression analysis (WGCNA).
Using DESeq2 on kallisto counts: Out of ~23,000 genes, ~4000 are significantly enriched in my TRAP RNA compared to RNA from the whole tissue input (Total RNA). ~5000 genes are significantly depleted in TRAP RNA compared to Total RNA (these include specific markers of non-target cell types).
My question: Should I filter genes before performing TRAP sample vs TRAP sample comparisons under different conditions, to remove the 5000 depleted genes?
A paper discussing analysis of TRAP datasets talks about filtering microarray probes with intensities lower than that of specific markers of non-target cell types. Would this make sense in an RNAseq scenario?