Dear all:
I have 2 questions using Cibersort deconvoluting cell types. I have single cell RNAseq data from 5 healthy and 5 cases with huge individual variation in some certain cell types.
1) I wonder if I can remove those un-conservative cell types to predict relative proportion with only a subset of cell types presented in single cell RNAseq data. e.g. Cells grouped in to 7 clusters under a certain resolution in single cell data. Then I calculated the relative proportion of each individuals by cell counts (of a certain cell type) dividing all cell counts. Next, I got 3 cell types which are relative conservative across individuals. I wonder if I can only use those 3 cell types to do deconvolution in bulk RNAseq.
2) I observed cell proportion difference between healthy control and cases. Also some genes were differentially expressed. While the strategy of several deconvolution methods is using the same single cell RNAseq profiling as reference to deconvolute cell types in bulk RNAseq from cases and controls. Is that fair ? Cos the prediction models could be different for cases and controls.
Thank you and best wishes!
1 answer
Sorry I made the wrong tag, should be QUESTION not Tutorial.
Response Please see "cell type deconvolution with Cibersort"
Log in to answer this question.