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This is the development version of BayesSpace; for the stable release version, see BayesSpace.

Clustering and Resolution Enhancement of Spatial Transcriptomes

Bioconductor version: Development (3.20)

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.

Author: Edward Zhao [aut], Matt Stone [aut, cre], Xing Ren [ctb], Raphael Gottardo [ctb]

Maintainer: Matt Stone <mstone at>

Citation (from within R, enter citation("BayesSpace")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

BayesSpace HTML R Script
Reference Manual PDF


biocViews Clustering, DataImport, GeneExpression, ImmunoOncology, SingleCell, Software, Transcriptomics
Version 1.15.0
In Bioconductor since BioC 3.12 (R-4.0) (3.5 years)
License MIT + file LICENSE
Depends R (>= 4.0.0), SingleCellExperiment
Imports Rcpp (>=, stats, purrr, scater, scran, SummarizedExperiment, coda, rhdf5, S4Vectors, Matrix, assertthat, mclust, RCurl, DirichletReg, xgboost, utils, ggplot2, scales, BiocFileCache, BiocSingular
System Requirements C++11
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Suggests testthat, knitr, rmarkdown, igraph, spatialLIBD, dplyr, viridis, patchwork, RColorBrewer, Seurat
Linking To Rcpp, RcppArmadillo, RcppDist, RcppProgress
Depends On Me
Imports Me RegionalST
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Source Package BayesSpace_1.15.0.tar.gz
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macOS Binary (arm64) BayesSpace_1.15.0.tgz
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