I’m having trouble regressing out cell cycle genes in large datasets as this is taking hours or often getting out of memory errors (with 800G). I’ve tried increasing the n_jobs parameter but it still takes quite long. Why is it faster to regress_out cell cycle genes in Seurat (within an hour)? Is there a difference in these two functions where one might be converting sparse into a dense matrix?