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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:

# install from cran
install.packages("ClusterGVis")

# 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

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Version

Install

install.packages('ClusterGVis')

Monthly Downloads

753

Version

0.1.3

License

MIT + file LICENSE

Issues

Pull Requests

Stars

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Maintainer

Junjun Lao

Last Published

June 17th, 2025

Functions in ClusterGVis (0.1.3)

plot_multiple_branches_heatmap2

Create a heatmap to demonstrate the bifurcation of gene expression along multiple branches
prepareDataFromscRNA

Prepare scRNA Data for clusterGvis Analysis
plot_genes_branched_heatmap2

Create a heatmap to demonstrate the bifurcation of gene expression along two branchs which is slightly modified in monocle2
normalized_counts

Return a size-factor normalized and (optionally) log-transformed expression
plot_pseudotime_heatmap2

Plots a pseudotime-ordered, row-centered heatmap which is slightly modified in monocle2
traverseTree

traverseTree function
termanno2

This is a test data for this package test data describtion
pseudotime

Generic to extract pseudotime from CDS object
termanno

This is a test data for this package test data describtion
visCluster

using visCluster to visualize cluster results from clusterData and enrichCluster output
sig_gene_names

This is a test data for this package test data describtion
size_factors

Get the size factors from a cds object.
check_dependency

Check and Install Required Packages
clusterData

Cluster Data Based on Different Methods
exprs,cell_data_set-method

Method to access cds count matrix
cell_data_set

The cell_data_set class from https://github.com/cole-trapnell-lab/monocle3/blob/master/R/cell_data_set.R
getClusters

Determine Optimal Clusters for Gene Expression or Pseudotime Data
filter.std modified by Mfuzz filter.std

using filter.std to filter low expression genes
enrichCluster

Perform GO/KEGG Enrichment Analysis for Multiple Clusters
exps

This is a test data for this package test data describtion
exprs

Generic to access cds count matrix
BEAM_res

This is a test data for this package test data describtion
net

This is a test data for this package test data describtion
%>%

Pipe operator
pre_pseudotime_matrix

Calculate and return a smoothed pseudotime matrix for the given gene list
pseudotime,cell_data_set-method

Method to extract pseudotime from CDS object