scBSP - A Fast Tool for Single-Cell Spatially Variable Genes
Identifications on Large-Scale Data
Identifying spatially variable genes is critical in
linking molecular cell functions with tissue phenotypes. This
package utilizes a granularity-based dimension-agnostic tool,
single-cell big-small patch (scBSP), implementing sparse matrix
operation and KD tree methods for distance calculation, for the
identification of spatially variable genes on large-scale data.
The detailed description of this method is available at Wang,
J. and Li, J. et al. 2023 (Wang, J. and Li, J. (2023),
<doi:10.1038/s41467-023-43256-5>).
