Package: SparseDC 0.1.17

Jun Li

SparseDC: Implementation of SparseDC Algorithm

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.

Authors:Jun Li [aut, cre], Martin Barron [aut]

SparseDC_0.1.17.tar.gz
SparseDC_0.1.17.tar.gz(r-4.5-noble)SparseDC_0.1.17.tar.gz(r-4.4-noble)
SparseDC_0.1.17.tgz(r-4.4-emscripten)SparseDC_0.1.17.tgz(r-4.3-emscripten)
SparseDC.pdf |SparseDC.html✨
SparseDC/json (API)

# Install 'SparseDC' in R:
install.packages('SparseDC', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 8 scripts 201 downloads 1 mentions 10 exports 0 dependencies

Last updated 7 years agofrom:1926132624. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 08 2024
R-4.5-linuxOKNov 08 2024

Exports:generate_uni_datlambda1_calculatorlambda2_calculatorpre_proc_dataS_funcsim_datasparsedc_clustersparsedc_gapupdate_cupdate_mu

Dependencies:

Sparse Differential Clustering

Martin Barron

Rendered fromSparseDC.Rmdusingknitr::rmarkdownon Nov 08 2024.

Last update: 2017-09-17
Started: 2017-05-02