Package: scBSP 1.0.0
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>).
Authors:
scBSP_1.0.0.tar.gz
scBSP_1.0.0.zip(r-4.5)scBSP_1.0.0.zip(r-4.4)scBSP_1.0.0.zip(r-4.3)
scBSP_1.0.0.tgz(r-4.4-any)scBSP_1.0.0.tgz(r-4.3-any)
scBSP_1.0.0.tar.gz(r-4.5-noble)scBSP_1.0.0.tar.gz(r-4.4-noble)
scBSP_1.0.0.tgz(r-4.4-emscripten)scBSP_1.0.0.tgz(r-4.3-emscripten)
scBSP.pdf |scBSP.html✨
scBSP/json (API)
| # Install 'scBSP' in R: |
| install.packages('scBSP', repos = c('https://castleli.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/castleli/scbsp/issues
Last updated 7 months agofrom:217bcf185d. Checks:OK: 1 WARNING: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 06 2024 |
| R-4.5-win | WARNING | Nov 06 2024 |
| R-4.5-linux | WARNING | Nov 06 2024 |
| R-4.4-win | WARNING | Nov 06 2024 |
| R-4.4-mac | WARNING | Nov 06 2024 |
| R-4.3-win | WARNING | Nov 06 2024 |
| R-4.3-mac | WARNING | Nov 06 2024 |
Exports:LoadSpatialscBSPSpFilter
Dependencies:dotCall64fitdistrpluslatticeMASSMatrixMatrixGenericsmatrixStatsRANNRcpprlangspamsparseMatrixStatssurvival
