MicrobiomeExplorer

Description

MicrobiomeExplorer is designed to facilitate the analysis of microbiome data, helping scientists and researchers to gain insights into microbial communities. Through this package, users can process, analyze, and visualize data from 16S rRNA gene sequencing, metagenomic, and metatranscriptomic studies. The goal is to provide a comprehensive toolset that improves upon existing workflows by integrating multiple data types and offering advanced graphical outputs. The MicrobiomeExplorer package was developed using R version 4.3.1 (2023-06-16), Platform: aarch64, darwin20 and Running under: macOS Sonoma 14.0. and is intended to be platform-independent, supporting macOS, Windows, and Linux distributions.

Installation

Before installing MicrobiomeExplorer, you must first install its dependencies. Notably, phyloseq and ComplexHeatmap are available through Bioconductor, not CRAN, and require Bioconductor’s installation methods.

Please run the following commands to install the current version of the dependency packages:

To install the current version of MicrobiomeExplorer from GitHub, use:

# Install devtools if not already installed
if (!requireNamespace("devtools", quietly = TRUE))
    install.packages("devtools")
    
# Install MicrobiomeExplorer from GitHub
devtools::install_github("itsSabbir/MicrobiomeExplorer", build_vignettes = TRUE)
#> Skipping install of 'MicrobiomeExplorer' from a github remote, the SHA1 (b9d3fbc1) has not changed since last install.
#>   Use `force = TRUE` to force installation

# Load MicrobiomeExplorer
library(MicrobiomeExplorer)

To run the shinyApp:

runMicrobiomeExplorerApp()

Overview

MicrobiomeExplorer offers a suite of functions that facilitate the exploration and analysis of microbiome data. Here is a list of the main functions along with a brief description:

• calculateStats: Calculates extended statistics (mean, median, standard deviation, variance, range, and interquartile range) for each feature in a microbiome dataset, providing a comprehensive statistical overview essential for preliminary data analysis.

• plotMicrobiomeHeatmap: Creates a comprehensive heatmap for microbiome data analysis, with support for normalization, various clustering methods, and enhanced visualization options using the ComplexHeatmap package.

• advancedRarefactionPlot: Generates rarefaction curves for microbiome count data, useful for comparing species richness among samples with customizable sampling and plot aesthetics.

• calculateAlphaDiversity: Computes various alpha diversity indices (like Shannon, Simpson, Chao1, and ACE) for each sample in a microbiome dataset, facilitating in-depth ecological and diversity studies.

• addData: Adds new data to a MicrobiomeData object, ensuring class compatibility and handling overlapping samples with advanced merging strategies. Supports rRNA16S, Metagenomic, or Metatranscriptomic data types, with specific validation for each..

• mergeData: Helper function to merge data matrices within MicrobiomeData objects, offering advanced merging options for overlapping data (like averaging or prioritizing new/existing data).

• removeData: Removes specified data (rRNA16S, Metagenomic, or Metatranscriptomic) from a MicrobiomeData object, simplifying data management and manipulation.

• updateSampleInfo: Updates the sample information in a MicrobiomeData object, ensuring consistency and integrity of new sample data with existing datasets.

• validateSampleInfo: Validates new sample information against existing data in MicrobiomeData objects, checking for consistency in sample counts, uniqueness, and matching identifiers.

• validate16SRNAData: Checks 16S rRNA gene sequencing data for structure, quality, and content, including numeric values, absence of negative values, minimum column and non-zero entry requirements, and no missing values.

• validateMetagenomicData: Validates metagenomic data for structure and quality, ensuring numeric values, no negative or extremely high values, and adequate dimensions.

• validateMetatranscriptomicData: Ensures metatranscriptomic data integrity by checking format, numeric values, non-negativity, potential outliers, and sequencing depth consistency.

• MicrobiomeData S4 Class: Defines an S4 class for managing microbiome data, including types such as 16S rRNA gene sequencing, metagenomic, and metatranscriptomic data, along with sample information.

• createMicrobiomeDataObject: Initializes a MicrobiomeData object with provided data, performing validation checks on the input data.

• getData: Extracts specified data type (‘rRNA16S’, ‘Metagenomic’, ‘Metatranscriptomic’, ‘SampleInfo’) from a MicrobiomeData object.

• updateData: Updates specific data within a MicrobiomeData object, allowing modification of existing data slots.

• performDifferentialExpression: Conducts differential expression analysis on microbiome data using either DESeq2 or EdgeR methods. It filters data based on count thresholds, normalizes counts, and returns results of the statistical analysis.

• runMicrobiomeExplorerApp: Initiates a Shiny application for the MicrobiomeExplorer package. This app provides an interactive interface for visualizing, analyzing, and exploring microbiome data. It supports various functionalities like plot generation and statistical analysis. The function launches the app in the user’s default web browser and is located in the ./inst/shiny-scripts directory of the MicrobiomeExplorer package.

To list the functions and datasets provided by MicrobiomeExplorer, use:

ls("package:MicrobiomeExplorer")

data(package = "MicrobiomeExplorer") # if applicable

For a comprehensive tutorial on how to use MicrobiomeExplorer, check out the vignettes:

browseVignettes("MicrobiomeExplorer")

The Vignettes will provide in depth documentation on how you can use the shinyapp to validate, normalize, analyzie, and visualze the date. You can get the data in the data/ directory as both will work, download from my respective github section as well.

The package also contains one sample micriobiome dataset presented as a dataframe called microbiome_data.csv. Refer to package vignettes for more details. An overview of the package is illustrated below.

A more standard barebones look:

Contributions

The MicrobiomeExplorer package was developed by Sabbir Hossain. The development of this package was inspired and informed by various established tools and methods within the bioinformatics community. Contributions from existing R packages and other sources are duly noted for each function within the package.

• phyloseq: Enhances data management, particularly in functions like calculate_stats and calculate_alpha_diversity, offering robust handling of complex microbiome datasets.

• ggplot2: Underpins the visualization aspects in plot_microbiome_heatmap and plot_rarefaction, providing elegant and informative data representation.

• vegan: Contributes to diversity analysis, especially in calculate_alpha_diversity and plot_rarefaction, delivering extensive ecological insights.

• dplyr and tidyr: Facilitate efficient data manipulation across the package, crucial for preprocessing and organizing data for analysis.

References

MicrobiomeExplorer integrates methods and insights from various sources, ensuring a robust and versatile tool for the scientific community. Key references include:

• McMurdie, P.J., and Holmes, S. (2013). phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS ONE 8(4): e61217.
• Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York.
• Oksanen, J., et al. (2019). vegan: Community Ecology Package. R package version 2.5-6.

Additional literature and resources that have contributed to the development of MicrobiomeExplorer:

• Callahan, B.J., et al. (2016). DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods, 13(7), 581-583.
• Paulson, J.N., et al. (2013). Differential abundance analysis for microbial marker-gene surveys. Nature Methods, 10(12), 1200-1202.
• Love, M.I., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15(12), 550.

Acknowledgements

This package was developed as part of an assessment for 2023 BCB410H: Applied Bioinformatics course at the University of Toronto, Toronto, CANADA. MicrobiomeExplorer welcomes issues, enhancement requests, and other contributions. To submit an issue, use the GitHub issues.

Equity, Diversity, and Inclusion (EDI)

MicrobiomeExplorer is committed to EDI principles, providing accessible documentation and actively seeking community feedback to cater to a broad audience. Challenges such as data bias, accessibility, and global representation are acknowledged and addressed to the best of the developers’ abilities.

Reproducibility

Reproducibility is ensured through rigorous version control, comprehensive documentation, clear specification of dependencies, automated testing, and continuous integration. A Docker container is also provided to facilitate a consistent and controlled environment for all users.

Package Structure

The MicrobiomeExplorer package is organized as follows:

- MicrobiomeExplorer
  |- .DS_Store
  |- .Rbuildignore
  |- .gitignore
  |- DESCRIPTION
  |- LICENSE
  |- LICENSE.md
  |- MicrobiomeExplorer.Rproj
  |- NAMESPACE
  |- README.Rmd
  |- README.md
  |- mbeUtils.Rmd
  |- data/
     |- microbiomeExample.rda
     |- microbiome_example.rda
  |- inst/
     |- extdata/
        |- microbiomeExampleObjectShin...
        |- microbiome_exampleShiny.csv
  |- man/
     |- AdvancedRarefactionPlot.Rd
     |- MicrobiomeData-class.Rd
     |- addData.Rd
     |- calculate_alpha_diversity.Rd
     |- calculate_stats.Rd
     |- createMicrobiomeDataObject.Rd
     |- getData.Rd
     |- microbiomeExample.Rd
     |- microbiome_example.Rd
     |- performDifferentialExpression.Rd
     |- plot_microbiome_heatmap.Rd
     |- removeData.Rd
     |- runMicrobiomeExplorerApp.Rd
     |- updateData.Rd
     |- updateSampleInfo.Rd
     |- validate16SRNAData.Rd
     |- validateMetagenomicData.Rd
     |- validateMetatranscriptomicData...
     |- validateSampleInfo.Rd
  |- R/
     |- advancedRarefactionPlot.R
     |- calculateAlphaDiversity.R
     |- calculateStats.R
     |- data.R
     |- dataManipulationFunctions.R
     |- dataValidationFunctions.R
     |- microbiomeDataClass.R
     |- performDEAnalysis.R
     |- plotMicrobiomeHeatmap.R
     |- runMicrobiomeExplorer.R
  |- tests/
     |- testthat/
        |- test-AdvancedRarefactionPlot.R
        |- test-DataManipulationFunction...
        |- test-MBDataClass.R
        |- test-calculateStats.R
        |- test-plotMicrobiomeHeatmap.R
        |- testthat.R
  |- vignettes/
     |- .DS_Store
     |- introduction_MicrobiomeExplore...
     |- sabbir.png
  |- shiny-scripts/
     |- app.R