🐷 Pig Metagenomics Pipeline

A comprehensive shotgun metagenomics pipeline for pig gut microbiome analysis: from raw reads to taxonomic profiles, functional annotations, and statistical analysis.

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📋 Table of Contents

• Overview
• Pipeline Workflow
• Directory Structure
• Installation
• Pipeline Steps
• Documentation
• Citation

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Overview

This pipeline processes shotgun metagenomic sequencing data from pig gut samples through quality control, taxonomic profiling, functional annotation, and comprehensive statistical analysis.

Step	Tool	Purpose
1. Quality Control	FastQC, MultiQC	Assess raw read quality
2. Preprocessing	KneadData (Trimmomatic)	Trim adapters, filter low-quality reads
3. Host Removal	KneadData (Bowtie2)	Remove pig genome contamination
4. Taxonomic Profiling	Kraken2 + Bracken	Identify and quantify microbial species
5. Functional Profiling	HUMAnN4	Predict metabolic pathways
6. Statistical Analysis	R (ALDEx2, ANCOM-BC)	Diversity and differential abundance

Project Stats

📊 Samples:     30 pig gut metagenomes
🧬 Sequencing:  Paired-end Illumina (Nextera)
💾 Raw Data:    ~15 GB
🖥️ Platform:    MSI (Minnesota Supercomputing Institute)

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Pipeline Workflow

graph TD
    A[Raw FASTQ] --> B[FastQC]
    B --> C[KneadData<br/>Trimmomatic + Host Removal]
    C --> D[Clean Reads]
    D --> E[Kraken2 + Bracken<br/>Taxonomic Profiling]
    D --> F[HUMAnN4<br/>Functional Profiling]
    E --> G[05_Statistical_Analysis<br/>Diversity & Differential Abundance]
    F --> H[06_Metabolic_Pathways<br/>Pathway Analysis]
    G --> I[Publication Figures]
    H --> I

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📁 Directory Structure

Metagenomics_Pipeline_Pigs_Complex_Diets/
│
├── 📄 README.md                          # This file
├── 📄 LICENSE                            # MIT License
│
├── 📂 docs/                              # Step-by-step documentation
│   ├── 01_pig_genome_index.md            # Build Bowtie2 index for host removal
│   ├── 02_QC_and_Host_Removal.md         # KneadData preprocessing
│   ├── 03_Taxonomic_Kraken2.md           # Kraken2 + Bracken profiling
│   └── 04_Humann4.md                     # HUMAnN4 functional profiling
│
├── 📂 05_Statistical_Analysis/           # R analysis scripts and reports
│   ├── README.md                         # Analysis documentation
│   ├── complex_diets.qmd                 # Quarto source file
│   ├── complex_diets.html                # Rendered HTML report
│   ├── meta.csv                          # Sample metadata
│   └── merged_*_abundance.txt            # Bracken abundance tables
│
├── 📂 06_Metabolic_Pathways/             # HUMAnN4 pathway analysis (coming soon)
│   └── README.md
│
├── 📂 scripts/                           # Pipeline scripts
│   ├── 00_prepare_env.sh
│   ├── 01_download_genome.sh
│   ├── 02_build_index.sbatch
│   ├── 03_kneaddata.sbatch
│   ├── 04_kraken2_batch.sbatch
│   ├── 05_bracken_batch.sbatch
│   └── 06_humann4_batch.sbatch
│
├── 📂 envs/                              # Conda environments
│   └── pig_metagenomics.yml
│
└── 📂 config/                            # Configuration files
    └── samples.txt

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Installation

1. Clone Repository

git clone https://github.com/SudarioRoberto/Metagenomics_Pipeline_Pigs_Complex_Diets.git
cd Metagenomics_Pipeline_Pigs_Complex_Diets

2. Create Conda Environment

mamba env create -f envs/pig_metagenomics.yml
mamba activate pig_metagenomics

3. Download Databases

# Pig genome for host removal
bash scripts/01_download_genome.sh

# Kraken2 standard database
# See docs/03_Taxonomic_Kraken2.md for details

# HUMAnN4 databases
# See docs/04_Humann4.md for details

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Pipeline Steps

Step 1: Build Host Genome Index

Build Bowtie2 index for pig genome (Sus scrofa) to remove host contamination.

sbatch scripts/02_build_index.sbatch

📖 Documentation: 01_pig_genome_index.md

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Step 2: Quality Control & Host Removal

Run KneadData for adapter trimming, quality filtering, and host decontamination.

sbatch scripts/03_kneaddata.sbatch

📖 Documentation: 02_QC_and_Host_Removal.md

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Step 3: Taxonomic Profiling

Classify reads taxonomically using Kraken2 and refine abundances with Bracken.

sbatch scripts/04_kraken2_batch.sbatch
sbatch scripts/05_bracken_batch.sbatch

📖 Documentation: 03_Taxonomic_Kraken2.md

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Step 4: Functional Profiling

Profile metabolic pathways and gene families using HUMAnN4.

sbatch scripts/06_humann4_batch.sbatch

📖 Documentation: 04_Humann4.md

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Step 5: Statistical Analysis

Comprehensive statistical analysis in R including:

• Alpha diversity: Observed, Shannon, Simpson, Chao1, Pielou's evenness
• Beta diversity: PCoA with Bray-Curtis, Jaccard, Aitchison distances
• PERMANOVA: Test for treatment effects
• Differential abundance: ALDEx2 and ANCOM-BC with consensus approach

📖 Documentation: 05_Statistical_Analysis/README.md

🔗 Interactive Report: View Full Analysis

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Step 6: Metabolic Pathway Analysis

Coming soon - Analysis of HUMAnN4 pathway and gene family outputs.

📖 Documentation: 06_Metabolic_Pathways/README.md

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Documentation

Document	Description
01_pig_genome_index.md	Download pig genome, build Bowtie2 index
02_QC_and_Host_Removal.md	KneadData preprocessing workflow
03_Taxonomic_Kraken2.md	Kraken2 + Bracken taxonomic profiling
04_Humann4.md	HUMAnN4 functional profiling
05_Statistical_Analysis/README.md	R statistical analysis guide

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🛠️ Troubleshooting

Java OutOfMemoryError (Trimmomatic)

Add to your script:

export _JAVA_OPTIONS="-Xmx32g"

Bowtie2 not found

Use full path to bin directory:

--bowtie2 /path/to/conda/env/bin

Kraken2 database loading errors

Use memory mapping if RAM is limited:

kraken2 --db $DB --memory-mapping --paired ...

HUMAnN4 command not found

Initialize conda properly:

source ~/.bashrc
eval "$(conda shell.bash hook)"
conda activate humann4_env

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Citation

If you use this pipeline, please cite:

@software{pig_metagenomics_pipeline,
  author = {Sudario, Roberto},
  title = {Pig Metagenomics Pipeline},
  year = {2024},
  url = {https://github.com/SudarioRoberto/Metagenomics_Pipeline_Pigs_Complex_Diets}
}

Tools Used

Tool	Purpose	Citation
KneadData	Quality control and host removal	Huttenhower Lab
Kraken2	Taxonomic classification	Wood et al., 2019
Bracken	Abundance estimation	Lu et al., 2017
HUMAnN4	Functional profiling	Beghini et al., 2021
ALDEx2	Differential abundance	Fernandes et al., 2014
ANCOM-BC	Differential abundance	Lin & Peddada, 2020

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📝 License

This project is licensed under the MIT License - see the LICENSE file for details.