NGS Data Processing Pipeline

This project implements a Next-Generation Sequencing (NGS) data processing pipeline using Snakemake, a workflow management system. The pipeline automates the process of quality control, trimming, alignment, and post-alignment processing of NGS data.

Features

• Quality control using FastQC
• Read trimming with Trimmomatic
• Alignment to a reference genome using BWA-MEM
• SAM to BAM conversion
• BAM file sorting and indexing

Prerequisites

Before running this pipeline, ensure you have the following software installed:

• Python 3.6+
• Snakemake
• FastQC
• Trimmomatic
• BWA
• SAMtools

You can install the Python dependencies using pip:

pip install snakemake

For the other tools, please refer to their respective installation guides.

Usage

1. Clone this repository:

   git clone https://github.com/yourusername/ngs-data-pipeline.git
   cd ngs-data-pipeline
   

2. Modify the pipeline.py script to set the correct paths for your input data, output directory, and reference genome.

3. Run the pipeline:

   python pipeline.py
   

   This will create a Snakefile and execute the workflow.

Pipeline Steps

1. FastQC: Quality control check on raw sequence data.
2. Trimmomatic: Trim adapters and low-quality bases from reads.
3. BWA-MEM: Align trimmed reads to the reference genome.
4. SAMtools: Convert SAM to BAM, sort BAM files, and create BAM indexes.

Customization

You can customize the pipeline by modifying the Snakemake rules in the pipeline.py file. Adjust parameters for each tool or add/remove steps as needed for your specific analysis.

Output

The pipeline generates the following output files for each sample:

• {sample}_fastqc.html: FastQC report
• {sample}_fastqc.zip: Zipped FastQC results
• {sample}_trimmed.fastq: Trimmed reads
• {sample}_aligned.sam: Aligned reads in SAM format
• {sample}.bam: Aligned reads in BAM format
• {sample}_sorted.bam: Sorted BAM file
• {sample}_sorted.bam.bai: BAM index file

Contributing

Contributions to improve the pipeline are welcome. Please fork the repository and submit a pull request with your changes.

License

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

Acknowledgments

• This pipeline uses several open-source bioinformatics tools. Please cite them appropriately in your research.
• Snakemake: Köster, Johannes and Rahmann, Sven. "Snakemake - A scalable bioinformatics workflow engine". Bioinformatics 2018.