Hi,

I am still practicing the Seurat workflow. I wonder how the pipeline will be the best practice for large datasets. Specifically, I am not sure if I should normalize prior to or after the merging. I list the questions in my mind:

• If I have 6 patients and each patient has two conditions, I will have total 12 datasets
• Should I normalize each data individually and then Merge. Or I can merge all together at the beginning and do rest of QC, i.e subset, NormalizeData/SCTtransform, ScaleData, etc..
• What perspectives needed to consider picking which normalization method (log vs SCT) I should use?
• Do I still need to use NormalizeData/ScaleData if I decide to use SCTransform?

Thank you in advance.