doi:10.6026/97320630002005> for more details.">

ClusterGVis: One-Step to Cluster and Visualize Gene Expression Data (original) (raw)

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: 0.1.2
Depends: R (≥ 2.10)
Imports: Biobase, circlize, clusterProfiler, colorRamps, ComplexHeatmap, dplyr, e1071, factoextra, ggplot2, grDevices, grid, magrittr, Matrix, methods, Mfuzz, purrr, reshape2, scales, SingleCellExperiment, stats, SummarizedExperiment, TCseq, tibble
Suggests: igraph, monocle, pheatmap, Seurat, WGCNA
Published: 2025-02-14
DOI: 10.32614/CRAN.package.ClusterGVis
Author: Jun Zhang ORCID iD [aut, cre]
Maintainer: Jun Zhang <3219030654 at stu.cpu.edu.cn>
BugReports: https://github.com/junjunlab/ClusterGVis/issues
License: MIT + file
NeedsCompilation: no
Citation: ClusterGVis citation info
Materials: README
CRAN checks: ClusterGVis results

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