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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:

# 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

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Version

Install

install.packages('ClusterGVis')

Version

0.1.2

License

MIT + file LICENSE

Maintainer

Junjun Lao

Last Published

February 14th, 2025

Functions in ClusterGVis (0.1.2)

getClusters

Determine Optimal Clusters for Gene Expression or Pseudotime Data
pre_pseudotime_matrix

Calculate and return a smoothed pseudotime matrix for the given gene list
prepareDataFromscRNA

Prepare scRNA Data for clusterGvis Analysis
exps

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

Pipe operator
BEAM_res

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

traverseTree function
visCluster

using visCluster to visualize cluster results from clusterData and enrichCluster output
plot_genes_branched_heatmap2

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

Cluster Data Based on Different Methods
pseudotime

Generic to extract pseudotime from CDS object
pseudotime,cell_data_set-method

Method to extract pseudotime from CDS object
plot_multiple_branches_heatmap2

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

Perform GO/KEGG Enrichment Analysis for Multiple Clusters
plot_pseudotime_heatmap2

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

Get the size factors from a cds object.
exprs,cell_data_set-method

Method to access cds count matrix
termanno

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

This is a test data for this package test data describtion
termanno2

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

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

Generic to access cds count matrix
net

This is a test data for this package test data describtion
filter.std modified by Mfuzz filter.std

using filter.std to filter low expression genes