Hi! I have processed and clustered my cells (adata), and subsetted the clusters to remove one contaminating cell cluster (adata_subset). However, I would now like to reprocess and recluster the clusters that I have chosen to subset.This requires going back to the beginning with the raw counts, etc. Which I am unsure how to do.
Before processing the original dataset, I created a layer: adata.layers[“counts”] = adata.X.copy(), so that I could save the raw counts here. I made adata.raw the normalized and log scaled version of the adata during my clustering (as suggested in the scanpy tutorial), so calling raw.to_adata() will not help me to get the raw counts for downstream analysis (this is mentioned in an answer to a similar question).
I guess I am wondering how I go about using/calling the counts layer that has my raw counts in the adata_subset object for reprocessing and recluster analysis?