This is the released version of clustSIGNAL; for the devel version, see clustSIGNAL.
ClustSIGNAL: a spatial clustering methodBioconductor version: Release (3.21)
clustSIGNAL: clustering of Spatially Informed Gene expression with Neighbourhood Adapted Learning. A tool for adaptively smoothing and clustering gene expression data. clustSIGNAL uses entropy to measure heterogeneity of cell neighbourhoods and performs a weighted, adaptive smoothing, where homogeneous neighbourhoods are smoothed more and heterogeneous neighbourhoods are smoothed less. This not only overcomes data sparsity but also incorporates spatial context into the gene expression data. The resulting smoothed gene expression data is used for clustering and could be used for other downstream analyses.
Author: Pratibha Panwar [cre, aut, ctb] ORCID: 0000-0002-7437-7084 , Boyi Guo [aut], Haowen Zhao [aut], Stephanie Hicks [aut], Shila Ghazanfar [aut, ctb] ORCID: 0000-0001-7861-6997
Maintainer: Pratibha Panwar <pratibhapanwar.4 at gmail.com>
Citation (from within R, entercitation("clustSIGNAL")
): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("clustSIGNAL")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("clustSIGNAL")
Details biocViews Clustering, GeneExpression, SingleCell, Software, Spatial, Transcriptomics Version 1.0.0 In Bioconductor since BioC 3.21 (R-4.5) (< 6 months) License GPL-2 Depends R (>= 4.4.0), SpatialExperiment Imports BiocParallel, BiocNeighbors, bluster(>= 1.16.0), scater, harmony, SingleCellExperiment, SummarizedExperiment, methods, Matrix, reshape2 System Requirements URL https://sydneybiox.github.io/clustSIGNAL/ Bug Reports https://github.com/sydneybiox/clustSIGNAL/issues See More Package Archives
Follow Installation instructions to use this package in your R session.
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