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SparseDC  

Implementation of SparseDC Algorithm
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("SparseDC", "0.1.17")



Attach the package and use:
library("SparseDC")
Maintained by
Jun Li
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-05-02
Latest Update: 2018-01-04
Description:
Implements the algorithm described in Barron, M., Zhang, S. and Li, J. 2017, "A sparse differential clustering algorithm for tracing cell type changes via single-cell RNA-sequencing data", Nucleic Acids Research, gkx1113, <doi:10.1093/nar/gkx1113>. This algorithm clusters samples from two different populations, links the clusters across the conditions and identifies marker genes for these changes. The package was designed for scRNA-Seq data but is also applicable to many other data types, just replace cells with samples and genes with variables. The package also contains functions for estimating the parameters for SparseDC as outlined in the paper. We recommend that users further select their marker genes using the magnitude of the cluster centers.
How to cite:
Jun Li (2017). SparseDC: Implementation of SparseDC Algorithm. R package version 0.1.17, https://cran.r-project.org/web/packages/SparseDC. Accessed 26 Aug. 2026.
Previous versions and publish date:
(2026-07-09 08:26), 0.1.5 (2017-05-02 12:50), 0.1.12 (2017-09-17 18:16), 0.1.14 (2017-10-19 05:37)
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Complete documentation for SparseDC
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