Dear all, i have a question ,which have bother me for a long time, i have a group of bulk rna-seq data, which were from whole testis , contain control and treated samples, after i was running DEG pipeline , i have got many DEGs ,but when i use IHC to test some of those genes (cell type marker gene ), i found there were significant cell proportion change in different cell types between control and treatment groups ( testes are highly heterogeneous tissue). Are those DEGs represent the proportion change of those different cell types? or the different RNA expression level in specific cell type ? if those "DEGs" were not real DEGs between same cell types, do i have a way to correct the result ? i have exact cell counting of those marked cells, normalized to 1 mm2.
The DEGs, depending on how you conducted your analysis, are statistically significantly differentially expressed between control and treatment. Typically, a statistically significantly differentially expressed gene will, in addition to a low p-value, have an absolute log [base 2] fold-change that is > 2, but not always. An exception may occur in a dataset that has high variability or one that is heteroskedastic, like the one that you may have due to the natural variability in testes tissue.
If you would like further advice, please elaborate on the programs that you have used, and also the key lines from your code.