I am struggle to figure out a solution to a (seemingly) simple. Using Seurat, I would like to find which genes are most highly expressed with individual marker genes spatial transcriptomic dataset.
I have an integrated dataset from mouse brains with the samples coming from 2 separate conditions (stim and ctrl). I also have a list neuronal activity marker genes (e.g., X, Y, Z). I would like to find which genes are correlated in their expression with each of these marker genes between the two conditions. In other words, which genes are co-expressed with X in the stim and in the ctrl condition, with Y in the stim and ctrl condition, and so on.
I don't have any sample code at this moment, I am quite a novice at coding and bioinformatic data analysis.
Closest I've gotten to finding a similar user issue is this [inconclusive and closed thread1 from 5 years ago.
Any help would be useful. Thank you!
If you are truly interested in examining co-expression then perhaps trying WGCNA on pseudobulk counts data generated from each cluster and sample may be the route to go