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BayesSpace

This is the released version of BayesSpace; for the devel version, see BayesSpace.

Clustering and Resolution Enhancement of Spatial Transcriptomes


Bioconductor version: Release (3.22)

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], Senbai Kang [aut, cre], Matt Stone [aut], Xing Ren [ctb], Raphael Gottardo [ctb]

Maintainer: Senbai Kang <senbai.kang at chuv.ch>

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

Installation

To install this package, start R (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
 install.packages("BiocManager")
BiocManager::install("BayesSpace")

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

Documentation

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

browseVignettes("BayesSpace")
BayesSpace HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

Version 1.20.0
In Bioconductor since BioC 3.12 (R-4.0) (5 years)
License MIT + file LICENSE
Depends R (>= 4.0.0), SingleCellExperiment
System Requirements C++17
See More
Enhances
Depends On Me
Imports Me RegionalST, OSTA
Suggests Me
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package BayesSpace_1.20.0.tar.gz
Windows Binary (x86_64)
macOS Binary (x86_64) BayesSpace_1.20.0.tgz
macOS Binary (arm64) BayesSpace_1.20.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/BayesSpace
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/BayesSpace
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