Question: Can I use seurat to analyze the data after MNNs batch normalized?
gravatar for jiandan123
8 weeks ago by
jiandan1230 wrote:

Does anyone know how to use seurat to analyze MNN normalized single-cell sequencing data? The data I want to re-analyzed compromise several subjects, and it was combined and batch normalized using MNNs (the author used mnnpy to remove the batch effect). They only provided the batch normalized data without the raw count matrix data, so I'm curious whether this batch normalized data can be proceeded by seurat. Because seurat uses the raw matrix data as input data and it uses CCA to remove the batch effect. If yes, could you tell me which seurat tutorial should I use?

ADD COMMENTlink written 8 weeks ago by jiandan1230

which steps of the Seurat analysis are you interested in? Clustering and UMAP should still work; for detecting marker genes etc., I'd recommend to obtain the raw counts. More details can be found in the OSCA documentation

ADD REPLYlink written 8 weeks ago by Friederike5.9k

Thanks for your suggestion. I'd like to compare my data with the published data, and if possible I want to combine these data by seurat. I think it will be more plausible if I use the same input data type.

ADD REPLYlink written 8 weeks ago by jiandan1230

If you want to compare your original data with published data, I don't see how that can be achieved in a meaningful way without the actual raw counts.

ADD REPLYlink written 8 weeks ago by Friederike5.9k

If you can start working on two different raw data from the beginning, then combining them together may not be problem. Rather, this will be more interesting study. Seurat can sometimes be very confusing because most of their functions are still not well established thus i would suggest try with other packages/tools too and do comparative study before making any conclusion.

ADD REPLYlink modified 7 weeks ago • written 7 weeks ago by manojevodevo30
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