Welcome to the Bacterial Genomics repository! This project hosts a structured, reproducible bioinformatics workflow designed for processing, analyzing, and interpreting bacterial Whole Genome Sequencing (WGS) data.
Currently, the pipeline is calibrated for evaluating Salmonella enterica datasets, emphasizing rigorous quality control, assembly, and downstream annotation.
This repository provides a standardized architecture for handling massive sequencing datasets without the chaos. By strictly separating raw data, scripts, and analytical outputs, the workflow ensures that every step—from raw .fastq reads to final .html QC reports—is fully reproducible.
- Automated Data Retrieval: Streamlined fetching of raw sequencing reads (e.g., via SRA Explorer).
- Comprehensive Quality Control: Assessing read viability using FastQC and aggregating metrics into interactive dashboards with MultiQC.
- Modular Architecture: Ready-to-use directories for extending the pipeline into genome assembly and feature annotation.
The repository is organized following bioinformatics best practices to keep code isolated from data:
bacterial_genomics/
├── analysis/ # Downstream analytical outputs (FastQC reports, MultiQC dashboards)
├── annotation/ # Outputs from gene prediction and annotation tools
├── assembly/ # Contigs and scaffolds generated from raw reads
├── data/ # The foundation: Raw reads, trimmed reads, and reference genomes
├── docs/ # Project documentation, lab notes, and literature
├── scripts/ # Bash and Python executables (e.g., environment setup, download scripts)
└── results/ # Synthesized, final data outputs ready for interpretation
Note: Raw sequencing files (*.fastq, *.gz) are ignored by version control to keep the repository lightweight.
git clone https://github.com/THEKINGSTAR/bacterial_genomics.git
cd bacterial_genomics
It is highly recommended to run this pipeline within an isolated environment to prevent dependency conflicts (especially with C-extensions). You can use the provided setup script to initialize your Conda environment:
# Execute the miniconda installation script if Conda is not yet installed
bash scripts/miniconda.sh
# Create and activate your bioinformatics environment
conda create -n genomics_env -c bioconda fastqc multiqc
conda activate genomics_env
Use the provided bash script to download the target WGS datasets (e.g., WGS of Salmonella enterica): bash scripts/sra_explorer_fastq_download.sh
Raw sequencing reads are evaluated for adapter contamination, sequence quality, and duplication levels.
Run FastQC: # Example execution on raw reads fastqc data/raw/*.fastq -o analysis/fastqc/
Aggregate with MultiQC: Compile all individual FastQC reports into a single, scannable dashboard. multiqc analysis/fastqc/ -o analysis/multiqc/
- FastQC: A quality control tool for high throughput sequence data.
- MultiQC: Aggregate results from bioinformatics analyses across many samples into a single report.
- Bash / Shell: For pipeline automation and environment management.
This project is open-source and available under the MIT License.