R Observatory: Metrics for SVG version 1.0.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

SVG

1.0.0Package record

Spatially Variable Genes Detection Methods for Spatial Transcriptomics

0packages depend

2.1Kdownloads / year

46.2%test coverage

13/13flavors OK

Overview

About

Maintained by Zaoqu LiuCRAN page ↗GitHub ↗Website ↗Issues ↗

A unified framework for detecting spatially variable genes (SVGs) in spatial transcriptomics data. This package integrates multiple state-of-the-art SVG detection methods including 'MERINGUE' (Moran's I based spatial autocorrelation), 'Giotto' binSpect (binary spatial enrichment test), 'SPARK-X' (non-parametric kernel-based test), and 'nnSVG' (nearest-neighbor Gaussian processes). Each method is implemented with optimized performance through vectorization, parallelization, and 'C++' acceleration where applicable. Methods are described in Miller et al. (2021) doi:10.1101/gr.271288.120, Dries et al. (2021) doi:10.1186/s13059-021-02286-2, Zhu et al. (2021) doi:10.1186/s13059-021-02404-0, and Weber et al. (2023) doi:10.1038/s41467-023-39748-z.

Changes in 1.0.0

First Release

New Features

**Unified interface**: CalSVG() function provides a single entry point for all SVG detection methods
**Six SVG detection methods** implemented with consistent output format:
CalSVG_MERINGUE(): Moran's I with binary spatial network
CalSVG_Seurat(): Moran's I with inverse distance weights
CalSVG_binSpect(): Binary spatial enrichment test (Giotto)
CalSVG_SPARKX(): Non-parametric kernel-based test
CalSVG_nnSVG(): Nearest-neighbor Gaussian processes
CalSVG_MarkVario(): Mark variogram method

Spatial Network Construction

buildSpatialNetwork(): Build spatial neighborhood networks using Delaunay triangulation or KNN

Show all changes in 1.0.0Hide the rest of the changes in 1.0.0

getSpatialNeighbors_Delaunay(): Delaunay triangulation-based network
getSpatialNeighbors_KNN(): K-nearest neighbors network

Statistical Utilities

moranI(): Calculate Moran's I statistic
moranI_test(): Hypothesis testing for spatial autocorrelation
ACAT_combine(): Aggregated Cauchy Association Test for p-value combination
binarize_expression(): Multiple methods for expression binarization

Data Simulation

simulate_spatial_data(): Generate simulated spatial transcriptomics data with known SVGs
Support for multiple spatial patterns: gradient, hotspot, periodic, cluster

Performance

C++ implementation via Rcpp/RcppArmadillo for computationally intensive operations
Parallel processing support via n_threads parameter
Efficient memory usage for large-scale data

Documentation

Comprehensive vignette with mathematical background
Complete function documentation with examples
Benchmark comparison between methods

Dependencies

Core: Matrix, Rcpp, RcppArmadillo
Optional: geometry, RANN, BRISC, CompQuadForm, BiocParallel, spatstat

Authors

Zaoqu Liu (maintainer) - liuzaoqu@163.com

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("SVG", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("Zaoqu-Liu/SVG")

Development version from Zaoqu-Liu/SVG. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-svg

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-SVG

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-SVG

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

Additional issues

donttest

CRAN check page ↗

Slowest check: 3.4 min · r-devel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK14 OK2026-04-22
ERROR13 OK, 1 ERROR2026-04-18
OK14 OK2026-04-10

Show 2 earlier changesHide 2 earlier changes

ERROR13 OK, 1 ERROR2026-04-09
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.0.0

READMEYes · 577 wordsVignettesYes · 1 · dynamicNEWSYes · 67% structured · mentions 1.0.0Citation fileNoWebsiteYes · pkgdown

Help pages: 37 (18 internal)includes a package overview page
Examples that run: 88%14 run in a plain check · 2 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 27%

Vignettes (1)

SVG: A Comprehensive R Package for Spatially Variable Gene Detection

How these are measured

Downloads

2.1K

CRAN downloads in the past year

Rank #17,260 · ~6/day · ~171/mo

Releases R versions

Daily download trend is not available in this view yet.

25430 days

74790 days

2.1K1 year

Compare downloads with other packages →

Also on255 r2u6 autocran

How downloads are counted

Repository

zaoqu-liu/svg ↗Account: Zaoqu-Liu

0Stars

0Forks

0Open issues

0Open PRs

0Releases

Last activity 2026-01-23

Responsiveness

not measured

How these are measured

PracticesBeta

9 development-tooling and community-health practices detected across 5 families in the upstream repository

Checks run against github.com/zaoqu-liu/svg on 2026-10-25.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Governance and community (2)

Code of conductContributing guide

Docs source (3)

pkgdown

GitHub Pages site last deployed 2026-01-23 · The repository has a site deploy workflow

pkgdown site last built 2026-01-23, before release 1.0.0 (2026-02-01)

Coverage (1)

Coverage reporting

Show all practicesHide 1 practice

CRAN release process (1)

cran-comments.md

How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies

17 external dependencies (excludes base and recommended)

Installing SVG adds 2 packages (2 with compiled code, 2.8 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppArmadillo 1.0 MB.

Depends (1)

R >= 4.0.0

Imports (6)

parallelstatsutilsmethodsMASSRcpp

LinkingTo (2)

Rcpp RcppArmadillo

Suggests (14)

BRISC geometry RANN CompQuadForm BiocParallel SpatialExperiment SingleCellExperiment SummarizedExperiment spatstat.geom spatstat.explore testthat knitr rmarkdown covr

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (2)

Zaoqu Liu

Author, Maintainer since 1.0.0 (2026)

SVGbench Contributors

Contributor

Original method implementations

Releases (1)

R
R 4.6.0 released · 2026-04-24
1.0.0Latest
record
2026-02-01 · current release
R
R 4.5.0 released · 2025-04-11

Package metadata

First published: 2026-02-01
Total releases: 1 / 1 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 4.0.0
Bundled data: 198 KB / 1 file
Download size: 1.1 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SVG")

Format

Liu, Z., & Contributors, S. (2026). SVG: Spatially Variable Genes Detection Methods for Spatial Transcriptomics (Version 1.0.0) [Computer software]. https://doi.org/10.32614/CRAN.package.SVG

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SVG version 1.0.0 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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