BayesSpace

DOI: 10.18129/B9.bioc.BayesSpace    

Clustering and Resolution Enhancement of Spatial Transcriptomes

Bioconductor version: Release (3.14)

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 fredhutch.org>

Installation

To install this package, start R (version "4.1") 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")

 

HTML	R Script	BayesSpace
PDF		Reference Manual
Text		NEWS
Text		LICENSE

Details

biocViews	Clustering, DataImport, GeneExpression, ImmunoOncology, SingleCell, Software, Transcriptomics
Version	1.4.1
In Bioconductor since	BioC 3.12 (R-4.0) (1.5 years)
License	MIT + file LICENSE
Depends	R (>= 4.0.0), SingleCellExperiment
Imports	Rcpp (>= 1.0.4.6), stats, purrr, scater, scran, SummarizedExperiment, coda, rhdf5, S4Vectors, Matrix, assertthat, mclust, RCurl, DirichletReg, xgboost, utils, ggplot2, scales, BiocFileCache, BiocSingular
LinkingTo	Rcpp, RcppArmadillo, RcppDist, RcppProgress
Suggests	testthat, knitr, rmarkdown, igraph, spatialLIBD, dplyr, viridis, patchwork, RColorBrewer, Seurat
SystemRequirements	C++11
Enhances
URL	edward130603.github.io/BayesSpace
BugReports	https://github.com/edward130603/BayesSpace/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	BayesSpace_1.4.1.tar.gz
Windows Binary	BayesSpace_1.4.1.zip (32- & 64-bit)
macOS 10.13 (High Sierra)	BayesSpace_1.4.1.tgz
Source Repository	git clone https://git.bioconductor.org/packages/BayesSpace
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/BayesSpace
Package Short Url	https://bioconductor.org/packages/BayesSpace/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.14	Source Archive