tpSVG

This is the development version of tpSVG; for the stable release version, see tpSVG.

Thin plate models to detect spatially variable genes

Bioconductor version: Development (3.20)

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] , Lukas M. Weber [ctb] , Stephanie C. Hicks [aut]

Maintainer: Boyi Guo <boyi.guo.work at gmail.com>

Citation (from within R, enter citation("tpSVG")):

Installation

To install this package, start R (version "4.4") 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.

Documentation


Reference Manual	PDF

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	DimensionReduction, GeneExpression, Preprocessing, Regression, Software, Spatial, StatisticalMethod, Transcriptomics
Version	1.1.0
In Bioconductor since	BioC 3.19 (R-4.4) (< 6 months)
License	MIT + file LICENSE
Depends	mgcv, R (>= 4.4)
Imports	stats, BiocParallel, MatrixGenerics, methods, SingleCellExperiment, SummarizedExperiment, SpatialExperiment
System Requirements
URL	https://github.com/boyiguo1/tpSVG
Bug Reports	https://github.com/boyiguo1/tpSVG/issues

Suggests	BiocStyle, knitr, nnSVG, rmarkdown, scran, scuttle, STexampleData, escheR, ggpubr, colorspace, BumpyMatrix, sessioninfo, testthat (>= 3.0.0)
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Build Report	Build Report

Package Archives

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

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository	git clone https://git.bioconductor.org/packages/tpSVG
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/tpSVG
Package Short Url	https://bioconductor.org/packages/tpSVG/
Package Downloads Report	Download Stats