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>).
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=scBSP
to link to this page.
[aut,
cre],
Yiqing Wang [aut]