BRCore

BRCore provides a unified framework for identification and ecological interpretation of core microbiomes across time and space, enhancing robustness and reproducibility in microbiome data analysis.

Features

BRCore provides tools for:

• Rarefaction analysis: Calculate pre-rarefaction metrics (add_rarefaction_metrics()) and perform multiple rarefaction (multi_rarefy())
• Core microbiome identification: Identify core microbial taxa using abundance-occupancy distributions (identify_core())
• Neutral model fitting: Fit and visualize neutral community models (fit_neutral_model(), plot_neutral_model())
• Visualization: Plot rarefaction diagnostics, abundance-occupancy curves, and core distributions (plot_rarefaction_metrics(), plot_abundance_occupancy(), plot_core_distribution(), plot_identified_core())

Installation

Quick Install (Recommended)

Install the latest stable version of BRCore from CRAN with:

install.packages("BRCore")

Install the development version of BRCore from GitHub with:

# install.packages("pak")
pak::pak("germs-lab/BRCore")

Note: If you don’t have pak installed, you can use devtools or remotes but you may need to install dependencies manually. pak handles dependencies automatically.

Install with Vignettes

# For the latest development version with vignettes, use:
# install.packages("devtools")
devtools::install_github("germs-lab/BRCore", build_vignettes = TRUE)

# or using remotes
# install.packages("remotes")
remotes::install_github("germs-lab/BRCore", build_vignettes = TRUE)

Note: Building vignettes requires additional time and dependencies. Use this option only if you need local access to documentation

Quick Start

library(BRCore)
library(phyloseq)

# Load example data
data("bcse", package = "BRCore")

# Add rarefaction metrics
bcse_metrics <- add_rarefaction_metrics(data = bcse)

# Perform multiple rarefaction
bcse_rarefied <- multi_rarefy(
  physeq = bcse,
  depth_level = 1000,
  num_iter = 100,
  threads = 4,
  set_seed = 7642
)

# Update phyloseq object with rarefied data
bcse_rare <- update_otu_table(physeq = bcse, otu_rare = bcse_rarefied)

# Identify core microbiome
bcse_core <- identify_core(
  physeq_obj = bcse_rare,
  priority_var = "Crop",
  increase_value = 0.02,
  seed = 2134
)

# Visualize abundance-occupancy distribution
plot_abundance_occupancy(core_result = bcse_core, core_set = "increase")

# Fit and plot neutral model
bcse_neutral <- fit_neutral_model(
  otu_table = bcse_core$otu_table,
  core_set = bcse_core$increase_core,
  abundance_occupancy = bcse_core$abundance_occupancy
)
plot_neutral_model(bcse_neutral)

Documentation

For detailed examples and use cases, see the package vignette:

vignette("BRCore-vignette", package = "BRCore")

Contributing

Contributions to BRCore are welcome! Please see the CONTRIBUTING.md file for guidelines on how to contribute.

Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.