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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 < at>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

intro_to_tpSVG HTML R Script
Reference Manual PDF


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
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Suggests BiocStyle, knitr, nnSVG, rmarkdown, scran, scuttle, STexampleData, escheR, ggpubr, colorspace, BumpyMatrix, sessioninfo, testthat (>= 3.0.0)
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Follow Installation instructions to use this package in your R session.

Source Package tpSVG_1.1.0.tar.gz
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macOS Binary (x86_64) tpSVG_1.1.0.tgz
macOS Binary (arm64) tpSVG_1.1.0.tgz
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