GrabSVG: Granularity-Based Spatially Variable Genes Identifications

Identifying spatially variable genes is critical in linking molecular cell functions with tissue phenotypes. This package implemented a granularity-based dimension-agnostic tool for the identification of spatially variable genes. The detailed description of this method is available at Wang, J. and Li, J. et al. 2023 (Wang, J. and Li, J. (2023), <doi:10.1038/s41467-023-43256-5>).

Version: 0.0.2
Imports: Matrix, sparseMatrixStats, fitdistrplus, RANN, spam
Suggests: knitr, rmarkdown
Published: 2023-12-06
Author: Jinpu Li ORCID iD [aut, cre]
Maintainer: Jinpu Li <castle.lee.f at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: GrabSVG results

Documentation:

Reference manual: GrabSVG.pdf

Downloads:

Package source: GrabSVG_0.0.2.tar.gz
Windows binaries: r-devel: GrabSVG_0.0.2.zip, r-release: GrabSVG_0.0.2.zip, r-oldrel: GrabSVG_0.0.2.zip
macOS binaries: r-release (arm64): GrabSVG_0.0.2.tgz, r-oldrel (arm64): GrabSVG_0.0.2.tgz, r-release (x86_64): GrabSVG_0.0.2.tgz

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