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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and Jun Li, "Simultaneous Detection of Clusters and Cluster-Specific Genes in High-throughput Transcriptome Data" (Unpublished).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.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.10.0) |
| Imports: | stats (≥ 3.5.0), utils (≥ 3.5.0), VennDiagram, scales (≥ 1.0.0), reshape2 (≥ 1.4.3), ggplot2 (≥ 3.1.0), rlang (≥ 0.3.4) |
| Suggests: | knitr, rmarkdown (≥ 1.13) |
| Published: | 2019-07-02 |
| Author: | Li Jun [cre], Jiang Ge [aut], Wang Chuanqi [ctb] |
| Maintainer: | Li Jun <jun.li at nd.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | ClussCluster results |
| Reference manual: | ClussCluster.pdf |
| Vignettes: |
ClussCluster |
| Package source: | ClussCluster_0.1.0.tar.gz |
| Windows binaries: | r-devel: ClussCluster_0.1.0.zip, r-release: ClussCluster_0.1.0.zip, r-oldrel: ClussCluster_0.1.0.zip |
| macOS binaries: | r-release (arm64): ClussCluster_0.1.0.tgz, r-oldrel (arm64): ClussCluster_0.1.0.tgz, r-release (x86_64): ClussCluster_0.1.0.tgz, r-oldrel (x86_64): ClussCluster_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
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