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scBSP  

A Fast Tool for Single-Cell Spatially Variable Genes Identifications on Large-Scale Data
View on CRAN: Click here


Download and install scBSP package within the R console
Install from CRAN:
install.packages("scBSP")

Install from Github:
library("remotes")
install_github("cran/scBSP")

Install by package version:
library("remotes")
install_version("scBSP", "1.0.0")



Attach the package and use:
library("scBSP")
Maintained by
Jinpu Li
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-02-09
Latest Update: 2024-02-09
Description:
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 method 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), ).
How to cite:
Jinpu Li (2024). scBSP: A Fast Tool for Single-Cell Spatially Variable Genes Identifications on Large-Scale Data. R package version 1.0.0, https://cran.r-project.org/web/packages/scBSP. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.0.1 (2024-02-09 19:40)
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Complete documentation for scBSP
Functions, R codes and Examples using the scBSP R package
Full scBSP package functions and examples
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