Streamlining the clustering and visualization of time-series gene expression data from RNA-Seq experiments, this tool supports fuzzy c-means and k-means clustering algorithms. It is compatible with outputs from widely-used packages such as 'Seurat', 'Monocle', and 'WGCNA', enabling seamless downstream visualization and analysis. See Lokesh Kumar and Matthias E Futschik (2007) <doi:10.6026/97320630002005> for more details.
Version: 0.1.3 Depends: R (≥ 2.10) Imports: Biobase, circlize, clusterProfiler, colorRamps, ComplexHeatmap, dplyr, e1071, factoextra, ggplot2, grDevices, grid, magrittr, Matrix, methods, purrr, BiocManager, reshape2, scales, SingleCellExperiment, stats, SummarizedExperiment, TCseq, tibble Suggests: igraph, knitr, monocle, pheatmap, rmarkdown, Seurat, WGCNA, utils Published: 2025-06-17 DOI: 10.32614/CRAN.package.ClusterGVis Author: Jun Zhang [aut, cre] Maintainer: Jun Zhang <3219030654 at stu.cpu.edu.cn> BugReports: https://github.com/junjunlab/ClusterGVis/issues License: MIT + file LICENSE URL: https://github.com/junjunlab/ClusterGVis/, https://junjunlab.github.io/ClusterGvis-manual/ NeedsCompilation: no Citation: ClusterGVis citation info Materials: README CRAN checks: ClusterGVis results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=ClusterGVis to link to this page.
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