MetaDAVis


Introduction


MetaDAVis (interactive Metagenome Data Analysis and Visualization) is a browser-based and user-friendly R Shiny application for researchers without programming proficiency to analyze and visualize metagenomics results from kingdom to species level. It comprises six functional analyses.

The package includes the following:
  • Data summary and abundance distribution
  • The data can be visualized in the stacked bar plot for abundance percentage, value, and relative frequency from 2 to 100 Taxa.
    • Group: Samples are grouped by given conditions based on the metadata.
    • Individual: Sample-based plots.
  • Diversity analysis
    • Alpha: Seven different methods was used from the phyloseq package. The results were displayed in a box and violin plot with a summary table.
    • Beta: A total of 42 different diversity metrics were integrated from the phyloseq (unlist(distanceMethodList)) package with six selection methods. Results are visualized by bar and ordination with a summary table.
  • Dimension reduction
    • PCA: The ggfortify and plotly package was used to display plots in 2D(with and without labels and frame) and 3D with their summary table.
    • t-SNE: Six different methods was used from the scater package. The samples were displayed in a t-SNE plot (2 and 3 dimensions) with a summary table.
    • UMAP: Six different methods was used from the scater package. Displays the UMAP plot in sample and cluster-based with a summary table.
  • Correlation analysis
    • Taxa-based: The ggfortify package was used to display plot (with and without labels and frame) and their summary table.
    • Sample-based: Six different methods was used from the scater package. The result was displayed in 2 and 3 dimensions t-SNE plots with a summary table.
  • Heatmap: It was integrated with the ComplexHeatmap package. Display heatmap with and without row and column dendrograms and names.
  • Differential abundance
    • Two groups: Six different analyses were provided using the Wilcoxon Rank Sum test, t-test, metagenomeSeq, DESeq2, Limma-Voom, edgeR, LEfSe, MaAsLin3. These will perform statistical analysis and generate plots and summary tables based on the significant taxa.
    • Multiple groups comparison: Two different analyses, such as Kruskal-Wallis test and ANOVA was used for more than multiple group comparisons. These will perform statistical analysis and generate plots and summary tables based on the significant taxa.

*It provides publication quality plots in seven formats: JPG, TIFF, PDF, SVG, BMP, EPS, and PS and summary tables (.csv format) to visualize and download.


use MetaDAVis online

MetaDAVis is deployed at: https://www.gudalab-rtools.net/MetaDAVis


Launch MetaDAVis using R and GitHub

MetaDAVis were deposited under the GitHub repository: https://github.com/GudaLab/MetaDAVis
Before running the app, the user must have R (>= 4.4.2), RStudio (>= 2024.12.0), Bioconductor (>= 3.20) and Shiny (>= 1.10.0) (Tested with this version).
If users use an older R version, they may encounter errors in installing packages, So the users are recommended to update their R version first.
Once the user opens the R in the command line or Rstudio, need to run the following command in R to install the shiny package.

install.packages('shiny')
library(shiny)

Start the app

Start the R session using RStudio and run these lines:

shiny::runGitHub('MetaDAVis','GudaLab')
or Alternatively, download the source code from GitHub and run the following command in the R session using RStudio:
library(shiny)
runApp('/path/to/the/MetaDAVis-master', launch.browser=TRUE)

Help manual for the usage of MetaDAVis [Download]


Cite:

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


Developed and maintained by

This application was created by Sankarasubramanian Jagdesan and Babu Guda. We share the passion about developing an user-friendly tool for all biologists, especially those who do not have access to bioinformaticians or programming efficency.


Download example data

Qiime2 format
Qiime2 Greengenes Output format
Qiime2 metadata for greengenes
Qiime2 Silva Outpus format
Qiime2 metadata for Silva
MEGAN output format
Megan WGS output format
Megan metadata
Taxa count file (Prepare your input accourding to our count and metadata format)
Count files format
Metadata

After the data is uploaded and checked, it will be displayed in the table summary below.


Number of OTUs

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Metadata

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Display the taxonomy counts for each samples

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Download as csv

Display the metadata file

Display the number of condition based on your metadata

Display the total number of counts in each samples

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Download plot
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Download plot

Boxplot

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Download plot

Result - alpha diversity estimates for each metagenome


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Download as csv

Beta diversity plot

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Result - distance between all the samples


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Download as csv

Result - Permutation test for adonis under reduced model


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Principal Component Analysis (PCA)

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Principal Component Analysis (PCA)

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t-distributed Stochastic Neighbor Embedding (t-SNE)

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Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP)

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Download plot
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Taxa based correlation plot.

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Taxa Samples based correlation plot for selected condition(s).

Download plot

Heatmap using relative abundance

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Download Heatmap

Result - OTUs that were significantly different between two groups

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Download significant

Download as csv

Download all

Download as csv

Download relative frequency

Download as csv

Total counts in each samples

Download as csv

Plot

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Download plot

Result - OTUs that were significantly different between two groups

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Download significant

Download as csv

Download all

Download as csv

Download relative frequency

Download as csv

Total counts in each samples

Download as csv

Plot

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Download plot

Result - OTUs that were significantly different between two groups

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Download significant

Download as csv

Download all

Download as csv

Total counts in each samples

Download as csv

Plot

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Download plot

Result - OTUs that were significantly different between two groups

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Download significant

Download as csv

Download all

Download as csv

Download normalized count

Download as csv

Total counts in each samples

Download as csv

Plot

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Download plot

Result - OTUs that were significantly different between two groups

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Download significant

Download as csv

Total counts in each samples

Download as csv

Plot

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Download plot

Results

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Download results

Download Output as ZIP

Result - OTUs that were significantly different between two groups

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Download significant

Download as csv

Download all

Download as csv

Total counts in each samples

Download as csv

Plot

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Download plot

Result - OTUs that were significantly different between two groups

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Download significant

Download as csv

Download all

Download as csv

Total counts in each samples

Download as csv

Plot

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Download plot

Result - OTUs that were significantly different between multiple groups

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Download significant

Download as csv

Download all

Download as csv

Download relative frequency

Download as csv

Total counts in each samples

Download as csv

Plot

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Download plot

Result - OTUs that were significantly different between multiple groups

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Download significant

Download as csv

Download all

Download as csv

Download relative frequency

Download as csv

Total counts in each samples

Download as csv

Plot

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Download plot