BayesSpace
Clustering and Resolution Enhancement of Spatial Transcriptomes
Bioconductor version: 3.23 · Package version: 1.22.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("BayesSpace") Details
| Maintainer | Senbai Kang <senbai.kang@chuv.ch> |
| Author | Edward Zhao [aut], Senbai Kang [aut, cre], Matt Stone [aut], Xing Ren [ctb], Raphael Gottardo [ctb] |
| License | MIT + file LICENSE |
| URL | edward130603.github.io/BayesSpace |
| Bug Reports | https://github.com/edward130603/BayesSpace/issues |
| System Requirements | C++17 |
| Downloads rank | 762 |
| Source branch | RELEASE_3_23 |
| biocViews | Clustering, DataImport, GeneExpression, ImmunoOncology, SingleCell, Software, Transcriptomics |
Documentation
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Dependencies
Depends: R (>= 4.0.0), SingleCellExperiment
Imports: Rcpp (>= 1.0.4.6), stats, methods, purrr, scater, scran, SummarizedExperiment, coda, rhdf5, S4Vectors, Matrix, magrittr, assertthat, arrow, mclust, RCurl, DirichletReg, xgboost (>= 3.0.0), utils, dplyr, rlang, ggplot2, tibble, rjson, tidyr, scales, microbenchmark, BiocFileCache, BiocSingular, BiocParallel
LinkingTo: Rcpp, RcppArmadillo, RcppDist, RcppProgress
Suggests: testthat, knitr, rmarkdown, igraph, spatialLIBD, viridis, patchwork, RColorBrewer, Seurat
Reverse dependencies
Imports Me (1): RegionalST