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.

A unified framework for detecting spatially variable genes (SVGs) in spatial transcriptomics data. This package integrates multiple state-of-the-art SVG detection methods:

• MERINGUE: Moran's I with binary adjacency network

• Seurat: Moran's I with inverse distance weights

• binSpect: Binary spatial enrichment test (from Giotto)

• SPARK-X: Non-parametric kernel-based test

• nnSVG: Nearest-neighbor Gaussian processes

• MarkVario: Mark variogram (from spatstat)

Main Functions

• CalSVG: Unified interface for all SVG methods

• CalSVG_MERINGUE: MERINGUE method (Moran's I with network)

• CalSVG_Seurat: Seurat method (Moran's I with 1/d^2 weights)

• CalSVG_binSpect: Giotto binSpect method

• CalSVG_SPARKX: SPARK-X method

• CalSVG_nnSVG: nnSVG method (requires BRISC)

• CalSVG_MarkVario: Mark variogram method

Utility Functions

• buildSpatialNetwork: Build spatial neighborhood network

• moranI: Calculate Moran's I statistic

• binarize_expression: Binarize gene expression

References

• Miller, B.F. et al. (2022) nnSVG for spatial transcriptomics. Nature Communications.

• Sun, S. et al. (2020) Statistical analysis of spatial expression patterns. Nature Methods.

• Dries, R. et al. (2021) Giotto: a toolbox for spatial transcriptomics. Genome Biology.

• Miller, J.A. et al. (2021) MERINGUE: characterizing spatial gene expression. Genome Research.

See also

Useful links:

• https://github.com/Zaoqu-Liu/SVG

• Report bugs at https://github.com/Zaoqu-Liu/SVG/issues

Author

Maintainer: Zaoqu Liu liuzaoqu@163.com (ORCID)

Other contributors:

• SVGbench Contributors (Original method implementations) [contributor]

Zaoqu Liu liuzaoqu@163.com