I have two experiments: single cell (SCE) and RNAseq (RNA). Each of these experiments have two groups: control (ctr) and treated (trt).
Experiment 1: I've used Seurat pipeline to perform clustering and cell types identification of SCE. Experiment 2: I have used DESeq2 to identify significant genes (up/down, say n=50) between trt vs ctr from RNAseq.
Now I want to use these 50 significant genes (RNAseq, bulk RNA) to identify which cells from SCE follow a similar expression signature. If these 50 genes would be all up or down, then I could take the average through which I can compare the average of each cell from SCE. However, I herein can't take the mean as some of the genes are down-regulated, considering mean of positive and negative values (fold-changes of significant genes) is not a good parameter to define the overall expression of RNAseq experiment as negative and positive values cancel each other.
What would be the best parameter to represent (positive and negative values)?
I would greatly appreciate any feedback, hint or suggestion.
Thank you, Sofia