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Description

One-Step to Cluster and Visualize Gene Expression Data.

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.

ClusterGVis

To enhance clustering and visualization of time-series gene expression data from RNA-Seq experiments, we present the ClusterGVis package. This tool enables concise and elegant analysis of time-series gene expression data in a simple, one-step operation. Additionally, you can perform enrichment analysis for each cluster using the enrichCluster function, which integrates seamlessly with clusterProfiler. ClusterGVis empowers you to create publication-quality visualizations with ease.

Thanks for the contributions for clusterProfiler and ComplexHeatmap!

Requirements

There are some R package to make sure have been installed for better installing ClusterGVis

BiocManager::install("ComplexHeatmap")
BiocManager::install("clusterProfiler")
BiocManager::install("TCseq")
BiocManager::install("Mfuzz")
BiocManager::install("monocle")
devtools::install_github('cole-trapnell-lab/monocle3')
install.packages("circlize")
install.packages("Seurat")

Installation

You can install the development version of ClusterGVis like so:

# Note: please update your ComplexHeatmap to the latest version!
# install.packages("devtools")
devtools::install_github("junjunlab/ClusterGVis")

Citation

Jun Zhang (2022). ClusterGVis: One-step to Cluster and Visualize Gene Expression Matrix. https://github.com/junjunlab/ClusterGVis

Documentation

The comprehensive documentation: https://junjunlab.github.io/ClusterGvis-manual/

Interactive web App

https://github.com/junjunlab/ClusterGvis-app

Related blogs

Metadata

Version

0.1.2

License

Unknown

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