BayesSpace: Clustering and Resolution Enhancement of Spatial Transcriptomes

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.

Package details

AuthorEdward Zhao [aut], Matt Stone [aut, cre], Xing Ren [ctb], Raphael Gottardo [ctb]
Bioconductor views Clustering DataImport GeneExpression ImmunoOncology SingleCell Software Transcriptomics
MaintainerMatt Stone <>
LicenseMIT + file LICENSE
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


Try the BayesSpace package in your browser

Any scripts or data that you put into this service are public.

BayesSpace documentation built on Nov. 8, 2020, 8:03 p.m.