Microbiota analysis pipeline for OGB project

This project provides a pipeline for analyzing microbiota data from the OGB (Oat-Gut-Brain) project. It includes alpha diversity, beta diversity, differential abundance analysis, and visualization of results.

The pipeline is implemented as a Quarto website for interactive exploration of results. It processes metagenomic data (after upstream preprocessing) to characterize microbial communities and compare sample groups.

Repository structure

.
├── code/
│   ├── _quarto.yml
│   ├── data.R
│   ├── funct.R
│   ├── main.R
│   └── ...
├── output/               # Rendered HTML reports
├── preprocessing/
│   ├── README.md         # Raw read QC → MetaPhlAn (and optional HUMAnN)
│   ├── raw_reads/        # Puhti / taxprofiler / HUMAnN scripts
│   └── remove_columns_metaphlan_db_meta4_combined_reports.R
└── README.md

Key files

• code/_quarto.yml — Quarto website configuration
• code/main.R — runs the analysis pipeline
• code/data.R — loads and formats data
• code/funct.R — analysis functions
• preprocessing/README.md — raw read preprocessing (taxprofiler, MetaPhlAn4)
• preprocessing/remove_columns_metaphlan_db_meta4_combined_reports.R — cleans MetaPhlAn tables for this repo

Data flow

[ENA raw FASTQ]
    → taxprofiler (fastp, BBduk, human removal) → MetaPhlAn4 profiles
    → optional HUMAnN3 on host-depleted reads
    → remove_columns_metaphlan_*.R
    → code/data.R + Quarto (output/)

Upstream steps and scripts: preprocessing/README.md.

Usage

Prerequisites

• R (version 4.0 or higher)
• Quarto (version 1.0 or higher)
• Required R packages (see code/main.R)

Installation

1. Clone this repository:

   git clone https://github.com/openresearchlabs/OGB_project.git
   cd OGB_project

2. Install required R packages:

   install.packages(c("package_name"))  # replace with packages from main.R

3. Install Quarto: https://quarto.org/docs/get-started/

Running the analysis

1. Open the project in RStudio or your preferred R environment.

2. Adjust code/_quarto.yml if you need different analysis parameters.

3. Run the main script:

   source("code/main.R")

4. View results by opening output/index.html in a browser.

Customizing the analysis

• code/data.R — data loading and formatting
• code/funct.R — add or change analysis functions
• code/_quarto.yml — report structure and content
• preprocessing/ — upstream metagenomics before this pipeline

Troubleshooting

• Memory: increase the R memory limit if needed:

  memory.limit(size=8000)

• Missing packages:

  if (!requireNamespace("BiocManager", quietly = TRUE))
      install.packages("BiocManager")
  BiocManager::install(c("package1", "package2", "package3"))

• Quarto render fails: check the R console, and confirm Quarto is installed and on your PATH.

For other issues, open an issue on the GitHub repository.