zAMPExplorer

zAMPExplorer is an interactive Shiny application designed to facilitate the downstream analysis of outputs generated by the zAMP pipeline . zAMP itself is a comprehensive DADA2-based bioinformatics pipeline for processing 16S rRNA gene amplicon metagenomic sequences, offering convenient, reproducible, and scalable analysis from raw sequencing reads to taxonomic profiles. The output of zAMP is a phyloseq object, which serves as the input for zAMPExplorer.

A typical phyloseq object contains the following components:

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 5 taxa and 6 samples ]
## sample_data() Sample Data:       [ 6 samples by 4 sample variables ]
## tax_table()   Taxonomy Table:    [ 5 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 5 tips and 4 internal nodes ]
## refseq()      DNAStringSet:      [ 5 reference sequences ]

For more information on the phyloseq package, please visit the official phyloseq documentation.

zAMPExplorer enables users to perform a wide range of microbiota and statistical analyses, including compositional barplot, relative abundance heatmap, community diversity (alpha diversity), community similarity through unsupervised (NMDS/PCoA) and supervised (RDA) ordinations, differential abundance testing using MaAsLin, and community typing (or clustering) of microbial profiles using Dirichlet Multinomial Mixtures (DMM). All of these analyses are made accessible through an intuitive graphical interface, bridging the gap between complex command-line bioinformatics processing and user-friendly data exploration.

Prerequisites and installation

Prerequisites

• Operating system: Windows, macOS, or Linux
• R: Version 4.3.2 or later
• RStudio: Recommended for running the Shiny app
• zAMP: zAMPExplorer is designed to work with output generated from
• microViz: Some functionalities of zAMPExplorer depend on microViz. Since it is not available on CRAN, please install it before running the app.

Installation

Method 1: Install using R-universe

# Install zAMPExplorer from R-universe
install.packages('zAMPExplorer', repos = c('https://metagenlab.r-universe.dev', 'https://cloud.r-project.org'))

Method 2: Install from source (GitHub)

# If not already installed 
if (!requireNamespace("remotes", quietly = TRUE)) {
  install.packages("remotes")
}

#Install zAMPExplorer
remotes::install_github("metagenlab/zAMPExplorer", dependencies = TRUE)

Method 3: Clone the repository and install zAMPExplorer locally

# Clone repository (in bash)
git clone https://github.com/metagenlab/zAMPExplorer.git

# Navigate to the app's directory
cd zAMPExplorer

# Install zAMPExplorer
install.packages(".", repos = NULL, type = "source")

#Then load the library and run the app

# Load zAMPExplorer
library(zAMPExplorer)

# Launch the application
zAMPExplorer::zAMPExplorer_app()

Overview of the interface

zAMPExplorer is divided into several tabs, each dedicated to a specific type of analysis:

### Check Phyloseq Components Upload your phyloseq object here. This object is the output of the zAMP pipeline and serves as the input for all downstream analyses in the app.

Phyloseq Component Tab

Reads QC

Visualize the total number of reads per sample and other read quality metrics.

Reads QC Tab

Taxa Overview

Explore the estimated number of organisms in each sample at different taxonomic levels.

### Compositional Barplot Create interactive barplots to visualize the relative abundance of taxa within your samples.

Compositional Barplot Tab

Heatmap

Generate heatmaps to visualize the relative abundance of taxa across samples and sample groups.

Alpha Diversity

Analyze and visualize alpha diversity metrics, comparing diversity within groups.

### Beta Diversity Explore beta diversity using different distance matrices to assess similarities/differences in microbial communities between samples.

Differential abundance testing (MAaslin2)

Determining associations between microbial features (e.g., taxa) and metadata.

### Community Typing (DMM) Perform community typing using Dirichlet Multinomial Mixture models to infer the optimal number of community types inside the dataset.

DMM Tab

RDA Plot

Perform redundancy analysis (RDA) to explore the association between your samples and explanatory variables.

Troubleshooting and FAQ

Common issues

Issue

App fails to launch. - Solution: Ensure all dependencies are installed by running source("Dependencies.R").

Issue

Plots are not displaying correctly. - Solution: Verify your R version is 4.0 or later and that all necessary libraries are installed.

FAQ

• Q: What file types can I upload?
  • A: zAMPExplorer supports .rds files containing phyloseq objects.
• Q: How do I update the app with new features?
  • A: Pull the latest updates from the GitHub repository, or fork the project and make changes to your fork.

References

The following R packages are integral to the functionality of zAMP Explorer. We highly recommend consulting their respective documentation:

References

The following R packages are integral to the functionality of zAMPExplorer. For detailed information about each package, visit the provided links:

• shiny: Shiny Web Application Framework for R.
• shinydashboard: Create Dashboards with ‘Shiny’.
• shinyWidgets: Custom Input Widgets for Shiny.
• webshot2: Taking Screenshots of Web Pages.
• htmlwidgets: HTML Widgets for R.
• dplyr: A grammar of data manipulation.
• phyloseq: Handling and Analysis of High-Throughput Microbial Community Data.
• DT: An R interface to the JavaScript library DataTables.
• ggplot2: Create Elegant Data Visualizations Using the Grammar of Graphics.
• ggpubr: Publication-Ready Plots Based on ggplot2.
• plotly: Create Interactive Web Graphics via ‘plotly.js’.
• vegan: Community Ecology Package.
• RColorBrewer: ColorBrewer Palettes.
• ComplexHeatmap: Make Complex Heatmaps.
• InteractiveComplexHeatmap: Make Interactive Complex Heatmaps in R.
• microViz: Tools to make microbial community data more accessible.
• microbiome: Microbiome Analytics.
• DirichletMultinomial: Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data.

For detailed information about each package, visit the provided links.

Contributing

Thank you for using zAMPExplorer. We hope it helps you gain deeper insights into your microbiome data (16S amplicons). Please feel free to contribute, suggest features, or report any issues you encounter.

Acknowledgments

We would like to thank the developers of the R packages and tools integrated into zAMPExplorer. Please make sure to acknowledge their contributions in any publications or projects using this tool.