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ClussCluster

Simultaneous Detection of Clusters and Cluster-Specific Genes in High-Throughput Transcriptome Data

v0.1.0 · Jul 2, 2019 · GPL-3

Description

Implements a new method 'ClussCluster' descried in Ge Jiang and Jun Li, "Simultaneous Detection of Clusters and Cluster-Specific Genes in High-throughput Transcriptome Data" (Unpublished). Simultaneously perform clustering analysis and signature gene selection on high-dimensional transcriptome data sets. To do so, 'ClussCluster' incorporates a Lasso-type regularization penalty term to the objective function of K- means so that cell-type-specific signature genes can be identified while clustering the cells.

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dependencies in R code

Namespace in Imports field not imported from: ‘utils’
  All declared Imports should be used.
NOTE r-devel-linux-x86_64-fedora-gcc

dependencies in R code

Namespace in Imports field not imported from: ‘utils’
  All declared Imports should be used.

Check History

NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
NOTE r-devel-linux-x86_64-fedora-clang

dependencies in R code

Namespace in Imports field not imported from: ‘utils’
  All declared Imports should be used.
NOTE r-devel-linux-x86_64-fedora-gcc

dependencies in R code

Namespace in Imports field not imported from: ‘utils’
  All declared Imports should be used.

Dependency Network

Dependencies Reverse dependencies VennDiagram scales (>= 1.0.0) reshape2 ggplot2 rlang (>= 0.3.4) ClussCluster

Version History

new 0.1.0 Mar 10, 2026