Spatially Variable Genes Detection Methods for Spatial Transcriptomics R package SVG version 1.0.0 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>. Software Depends: R (>= 4.0.0) Imports: parallel, stats, utils, methods, MASS, Rcpp (>= 1.0.0) LinkingTo: Rcpp, RcppArmadillo Suggests: BRISC, geometry, RANN, CompQuadForm, BiocParallel, SpatialExperiment, SingleCellExperiment, SummarizedExperiment, spatstat.geom, spatstat.explore, testthat (>= 3.0.0), knitr, rmarkdown, covr Zaoqu Liu <liuzaoqu@163.com> Comprehensive R Archive Network (CRAN) Zaoqu Liu [aut, cre] (ORCID: <https://orcid.org/0000-0002-0452-742X>), SVGbench Contributors [ctb] (Original method implementations) MIT + file LICENSE (https://CRAN.R-project.org/package=SVG/LICENSE) 2026-02-01 application/tgz https://CRAN.R-project.org/package=SVG doi:10.32614/CRAN.package.SVG