MetaDAVis

Introduction

MetaDAVis, interactive Metagenome Data Analysis and Visualization, is a browser-based R Shiny application for analyzing and visualizing 16S and whole-metagenome sequencing results from kingdom to species level. It is designed for researchers who want to run common metagenomics analyses without writing R code.

MetaDAVis includes:

1. Data summary and abundance distribution
2. Diversity analysis
3. Dimension reduction
4. Correlation analysis
5. Heatmap
6. Differential abundance for two-group and multi-group comparisons
7. Bulk download for all completed outputs

Use MetaDAVis Online

MetaDAVis is deployed at:

https://www.gudalab-rtools.net/MetaDAVis

Local Requirements

Recommended versions:

• R >= 4.4.2
• RStudio >= 2024.12.0
• Bioconductor >= 3.20
• Shiny >= 1.10.0

Recommended local build tools:

• Windows: install Rtools for your R version from https://cran.r-project.org/bin/windows/Rtools/
• macOS: install Xcode Command Line Tools with xcode-select --install
• Ubuntu/Debian Linux: install development libraries before installing R packages:

sudo apt-get update
sudo apt-get install -y build-essential gfortran libcurl4-openssl-dev libssl-dev libxml2-dev libfontconfig1-dev libfreetype6-dev libpng-dev libtiff5-dev libjpeg-dev libharfbuzz-dev libfribidi-dev

• Red Hat/CentOS/Fedora Linux: install development libraries before installing R packages:

sudo yum install -y gcc gcc-c++ gcc-gfortran make libcurl-devel openssl-devel libxml2-devel fontconfig-devel freetype-devel libpng-devel libtiff-devel libjpeg-turbo-devel harfbuzz-devel fribidi-devel

Install MetaDAVis Locally

Option 1: Run Directly From GitHub

Open R or RStudio and run:

install.packages("shiny", repos="https://cloud.r-project.org")
library(shiny)
shiny::runGitHub("MetaDAVis", "GudaLab")

Option 2: Download and Run From a Local Folder

Download or clone the MetaDAVis repository:

git clone https://github.com/GudaLab/MetaDAVis.git
cd MetaDAVis

Then open R or RStudio in the MetaDAVis folder and run:

library(shiny)
runApp(".", launch.browser=TRUE)

If you downloaded a ZIP file instead of using Git, unzip it, open R/RStudio in that folder, and run the same runApp() command.

Install All Required R Packages

MetaDAVis checks for missing packages at startup, but installing all dependencies first is recommended for a smoother local launch.

Run this once in R or RStudio:

options(repos= c(CRAN="https://cloud.r-project.org"))
cran_packages<- c(
"shiny",
"DT",
"shinythemes",
"shinyFiles",
"shinyjs",
"shinydashboard",
"ggplot2",
"ggpubr",
"vegan",
"ggfortify",
"ggplotify",
"reshape2",
"tibble",
"scales",
"dunn.test",
"tidyr",
"dplyr",
"devtools",
"patchwork",
"GGally",
"plotly",
"zip",
"filelock",
"shinycssloaders",
"RColorBrewer",
"circlize"
)
missing_cran<-cran_packages[!vapply(cran_packages, requireNamespace, logical(1), quietly=TRUE)]
if (length(missing_cran)) {
install.packages(missing_cran, dependencies=TRUE)
}
if (!requireNamespace("BiocManager", quietly=TRUE)) {
install.packages("BiocManager")
}
bioc_packages<- c(
"phyloseq",
"microbiome",
"ComplexHeatmap",
"qvalue",
"scater",
"DESeq2",
"limma",
"edgeR",
"metagenomeSeq",
"bluster",
"mia",
"lefser"
)
missing_bioc<-bioc_packages[!vapply(bioc_packages, requireNamespace, logical(1), quietly=TRUE)]
if (length(missing_bioc)) {
BiocManager::install(missing_bioc, update=FALSE, ask=FALSE)
}
github_packages<- c(
"microsud/microbiomeutilities",
"biobakery/maaslin3"
)
for (pkgingithub_packages) {
package_name<- sub(".*/", "", pkg)
if (!requireNamespace(package_name, quietly=TRUE)) {
BiocManager::install(pkg, update=FALSE, ask=FALSE)
}
}

If a GitHub package fails to install through BiocManager::install(), install it with devtools:

devtools::install_github("microsud/microbiomeutilities")
devtools::install_github("biobakery/maaslin3")

Tool and Package Summary

MetaDAVis tool	Main R packages used
Upload and preprocessing	tidyr, dplyr, tibble
Group and individual abundance distribution	ggplot2, RColorBrewer
Alpha diversity	phyloseq, ggplot2, ggpubr, RColorBrewer
Beta diversity	phyloseq, vegan, reshape2, ggplot2, ggpubr
PCA-2D	ggfortify, ggplot2, RColorBrewer, dplyr
PCA-3D	plotly, RColorBrewer
t-SNE and UMAP	phyloseq, bluster, patchwork, scater, mia, RColorBrewer, dplyr
Taxa and sample correlation	ggpubr, GGally, ggplot2, RColorBrewer, dplyr
Heatmap	ComplexHeatmap, circlize, scales, ggplotify, RColorBrewer
Wilcoxon and t-test	ggplot2, tibble, qvalue, ComplexHeatmap, ggplotify, RColorBrewer, dplyr
metagenomeSeq	metagenomeSeq, ggplot2, tibble, ComplexHeatmap, ggplotify, dplyr
DESeq2	DESeq2, ggplot2, tibble, qvalue, ComplexHeatmap, ggplotify, dplyr
LEfSe	phyloseq, lefser, mia, tibble, ggplot2, RColorBrewer, dplyr
MaAsLin3	maaslin3, tibble, dplyr
Limma-Voom and edgeR	limma, edgeR, ggplot2, tibble, ComplexHeatmap, ggplotify, circlize, dplyr
Kruskal-Wallis and ANOVA	ggplot2, tibble, qvalue, dunn.test, ComplexHeatmap, ggplotify, RColorBrewer
Bulk download	zip, filelock, base R
User interface	shiny, DT, shinythemes, shinyFiles, shinyjs, shinydashboard, shinycssloaders

Usage

Open the Manual tab inside the MetaDAVis application for the step-by-step tutorial https://github.com/GudaLab/MetaDAVis/blob/main/www/manual/MetaDAVis_manual.pdf, example-data instructions, analysis options, and Bulk Download instructions.

Example data are included in:

www/example_data

Tested Platforms

MetaDAVis has been tested on:

• Linux: Red Hat and Ubuntu
• Windows: 10 and 11

Citation

Jagadesan S, Guda C (2025) MetaDAVis: An R shiny application for metagenomic data analysis and visualization. PLoS ONE 20(4): e0319949. https://doi.org/10.1371/journal.pone.0319949