This is the development version of tpSVG; for the stable release version, see tpSVG.
Thin plate models to detect spatially variable genesBioconductor version: Development (3.22)
The goal of `tpSVG` is to detect and visualize spatial variation in the gene expression for spatially resolved transcriptomics data analysis. Specifically, `tpSVG` introduces a family of count-based models, with generalizable parametric assumptions such as Poisson distribution or negative binomial distribution. In addition, comparing to currently available count-based model for spatially resolved data analysis, the `tpSVG` models improves computational time, and hence greatly improves the applicability of count-based models in SRT data analysis.
Author: Boyi Guo [aut, cre] ORCID: 0000-0003-2950-2349 , Lukas M. Weber [ctb] ORCID: 0000-0002-3282-1730 , Stephanie C. Hicks [aut] ORCID: 0000-0002-7858-0231
Maintainer: Boyi Guo <boyi.guo.work at gmail.com>
Citation (from within R, entercitation("tpSVG")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("tpSVG")
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("tpSVG")Follow Installation instructions to use this package in your R session.
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