The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.