Package: SVG Type: Package Title: Spatially Variable Genes Detection Methods for Spatial Transcriptomics Version: 1.0.0 Authors@R: c( person("Zaoqu", "Liu", email = "liuzaoqu@163.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0452-742X")), person("SVGbench", "Contributors", role = "ctb", comment = "Original method implementations")) Description: 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) , Dries et al. (2021) , Zhu et al. (2021) , and Weber et al. (2023) . License: MIT + file LICENSE URL: https://github.com/Zaoqu-Liu/SVG, https://zaoqu-liu.github.io/SVG/ BugReports: https://github.com/Zaoqu-Liu/SVG/issues Encoding: UTF-8 LazyData: false Depends: R (>= 4.0.0) Imports: parallel, stats, utils, methods, MASS, Rcpp (>= 1.0.0) Suggests: BRISC, geometry, RANN, CompQuadForm, BiocParallel, SpatialExperiment, SingleCellExperiment, SummarizedExperiment, spatstat.geom, spatstat.explore, testthat (>= 3.0.0), knitr, rmarkdown, covr LinkingTo: Rcpp, RcppArmadillo RoxygenNote: 7.3.3 VignetteBuilder: knitr Config/testthat/edition: 3 Repository: https://zaoqu-liu.r-universe.dev Date/Publication: 2026-01-23 07:10:52 UTC RemoteUrl: https://github.com/Zaoqu-Liu/SVG RemoteRef: HEAD RemoteSha: 2fb606b28dcf4d96a1a0f212341449a633ea37b9 NeedsCompilation: yes Packaged: 2026-10-20 07:30:16 UTC; root Author: Zaoqu Liu [aut, cre] (ORCID: ), SVGbench Contributors [ctb] (Original method implementations) Maintainer: Zaoqu Liu