Package: nnSVG Version: 1.17.0 Title: Scalable identification of spatially variable genes in spatially-resolved transcriptomics data Description: Method for scalable identification of spatially variable genes (SVGs) in spatially-resolved transcriptomics data. The method is based on nearest-neighbor Gaussian processes and uses the BRISC algorithm for model fitting and parameter estimation. Allows identification and ranking of SVGs with flexible length scales across a tissue slide or within spatial domains defined by covariates. Scales linearly with the number of spatial locations and can be applied to datasets containing thousands or more spatial locations. Authors@R: c( person("Lukas M.", "Weber", email = "lmweb012@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3282-1730")), person("Stephanie C.", "Hicks", email = "shicks19@jhu.edu", role = c("aut"), comment = c(ORCID = "0000-0002-7858-0231"))) URL: https://github.com/lmweber/nnSVG BugReports: https://github.com/lmweber/nnSVG/issues License: MIT + file LICENSE Encoding: UTF-8 biocViews: Spatial, SingleCell, Transcriptomics, GeneExpression, Preprocessing Depends: R (>= 4.2) Imports: SpatialExperiment, SingleCellExperiment, SummarizedExperiment, BRISC, BiocParallel, Matrix, matrixStats, stats, methods VignetteBuilder: knitr Suggests: BiocStyle, knitr, rmarkdown, STexampleData, WeberDivechaLCdata, scran, ggplot2, testthat RoxygenNote: 7.2.3 Config/pak/sysreqs: libmagick++-dev gsfonts libicu-dev libssl-dev zlib1g-dev Repository: https://bioc.r-universe.dev Date/Publication: 2026-04-28 12:58:01 UTC RemoteUrl: https://github.com/bioc/nnSVG RemoteRef: HEAD RemoteSha: 93e287a1252fbab3db147357664f66db33a5073c NeedsCompilation: no Packaged: 2026-06-14 07:21:13 UTC; root Author: Lukas M. Weber [aut, cre] (ORCID: ), Stephanie C. Hicks [aut] (ORCID: ) Maintainer: Lukas M. Weber