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merging independent SuperCell runs #11
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Hi @daskelly, Thanks a lot for you interest in our method! There are two option available to address your question:
Which approach to use highly depends on what you would do at the single-cell level. For instance, if you would analyze your samples together, you can go with the first approach. Please, let me know if this answers your question and don't hesitate to contact me if you have any other questions or suggestions! Bets, |
Hi @mariiabilous thank you! This is really helpful and it does answer my question. Can I ask two follow-up questions?
Thanks for your responsiveness! |
Sure!
The short answer is "No". I expect, that metacells built with an independent approach would be more 'stable' as they are based on the intra-sample heterogeneity. Note, that in the case of a combined approach (all samples together, specifying
It can happen in the combined analysis, different samples have different granularity due to their different complexity and heterogeneity. I think it is acceptable to process samples of different sizes at different graining levels, as long as the size distribution of metacells you are going to combine in the same analyses is acceptable. I wouldn't go with Thank you a lot for your interesting questions! If you try different approaches, I would be happy to know your experience and your thought on which approach was more appropriate in the analyses you performed. |
Thank you @mariiabilous this is helpful and makes a lot of sense! |
Hi, thanks for developing this very nice package!
I have a question about merging SuperCell objects. Let's say I have three samples and I wish to run SuperCell separately on each sample -- e.g. to ensure that metacells are only composed of cells from the same biological specimen. Is there a way to merge these multiple SuperCell objects so that I can then run the weighted PCA and clustering on the combined data? Thanks for any tips!
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