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cells clustering by sample
My dataset contains one cell type from 10 samples. Each sample was sequenced independently and therefore is its own batch as well. When I cluster using desc each sample clusters purely by sample (with minimal overlap)
I have tried varying the learning rate with limited success. Are there other variables to adjust the model to encourage more rigorous batch correction?
Can you try scaling data within each batch and then feed the scaled data into desc?