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 (doi:10.1038/s41467-023-43256-5).
- Version1.0.0
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release05/03/2024
Team
Jinpu Li
Yiqing Wang
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- Imports4 packages
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