SVG
Spatially Variable Genes Detection Methods for Spatial Transcriptomics
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | SVG_1.0.0.tar.gz |
1.2 MiB |
1.0.0 |
rolling linux/noble R-4.5 | SVG_1.0.0.tar.gz |
1.2 MiB |
1.0.0 |
rolling source/ R- | SVG_1.0.0.tar.gz |
1.0 MiB |
1.0.0 |
latest linux/jammy R-4.5 | SVG_1.0.0.tar.gz |
1.2 MiB |
1.0.0 |
latest linux/noble R-4.5 | SVG_1.0.0.tar.gz |
1.2 MiB |
1.0.0 |
latest source/ R- | SVG_1.0.0.tar.gz |
1.0 MiB |
1.0.0 |
2026-04-26 source/ R- | SVG_1.0.0.tar.gz |
1.0 MiB |
1.0.0 |
2026-04-23 source/ R- | SVG_1.0.0.tar.gz |
1.0 MiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | SVG_1.0.0.zip |
1.5 MiB |