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edward130603 / BayesSpace

Bayesian model for clustering and enhancing the resolution of spatial gene expression experiments.
http://edward130603.github.io/BayesSpace
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Bayespace reference scRNAseq data #110

Open chrkuo opened 1 year ago

chrkuo commented 1 year ago

Thank you for creating such a wonderful tool. Quick question - I read the BayesSapce paper and I am a bit confused - can this tool be used without a reference scRNAseq data. or do I ultimately still need a scRNAseq dataset to run BayesSapce. The vignettes aren't super clear as well.

Appreciate your time

edward130603 commented 1 year ago

Thanks for reaching out. BayesSpace does not use scRNAseq data. In the manuscript, we only used scRNAseq/deconvolution methods for validation of the BayesSpace method.

chrkuo commented 1 year ago

@edward130603 thank you -- since spatial transcriptomics are not single cell resolution after enhancing the clustering and resolution to subspot level - is there downstream analysis to then deconvolute that sub-spot level of resolution?

edward130603 commented 1 year ago

We have not specifically implemented that analysis. One approach to do it would involve the following:

First predict subspot level expression using enhanceFeatures(). I suggest just doing the top HVGs rather than all genes to save compute time. Then use a deconvolution method that works on the logcounts. I believe we used CIBERSORT in the manuscript but you can try another more recent method.