Tools for clustering and enhancing the resolution of spatial gene expression experiments. BayesSpace clusters a low-dimensional representation of the gene expression matrix, incorporating a spatial prior to encourage neighboring spots to cluster together. The method can enhance the resolution of the low-dimensional representation into "sub-spots", for which features such as gene expression or cell type composition can be imputed.
|Bioconductor views||Clustering DataImport GeneExpression ImmunoOncology SingleCell Software Transcriptomics|
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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