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CoGe-Pipeline

License: MIT Bash Conda Pipeline

Automated Bacterial Genome Annotation & BGC Discovery Pipeline


Overview

CoGe-Pipeline is an end-to-end, automated bioinformatics pipeline developed for large-scale bacterial genome analysis and secondary metabolite discovery. It was designed as part of the One Day One Genome (ODOG) initiative to process 25–30 bacterial genomes in a reproducible, scalable, and fault-tolerant manner.

The pipeline takes paired-end Illumina reads as input and produces:

  • High-quality genome assemblies
  • Functional annotations
  • Biosynthetic gene cluster (BGC) predictions
  • Comparative BGC clustering results

Pipeline Workflow

Paired-end FASTQ
   ├── FastQC (raw QC)
   ├── fastp (trimming & filtering)
   ├── FastQC (post-trim QC)
   ├── SPAdes (genome assembly)
   ├── QUAST (assembly quality)
   ├── Prokka (genome annotation)
   ├── antiSMASH (BGC prediction)
   └── BiG-SCAPE (comparative BGC clustering)

Key Features

  • Fully automated end-to-end workflow
  • Handles multiple genomes in a single run
  • Robust error handling (failed genomes are skipped, pipeline continues)
  • Resume-friendly: completed steps are not recomputed
  • Conda-based reproducible environments
  • Supports comparative BGC analysis across all genomes
  • Generates interactive BiG-SCAPE HTML visualizations

Tools

Tool Purpose Citation
FastQC Read quality control Andrews S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data
fastp Read trimming & filtering Chen et al. (2018). Bioinformatics, 34(17):i884-i890. DOI:10.1093/bioinformatics/bty560
SPAdes De novo genome assembly Bankevich et al. (2012). J Comput Biol, 19(5):455-477. DOI:10.1089/cmb.2012.0021
QUAST Assembly quality assessment Gurevich et al. (2013). Bioinformatics, 29(8):1072-1075. DOI:10.1093/bioinformatics/btt086
Prokka Genome annotation Seemann T. (2014). Bioinformatics, 30(14):2068-2069. DOI:10.1093/bioinformatics/btu153
antiSMASH Biosynthetic gene cluster detection Blin et al. (2023). Nucleic Acids Res, 51(W1):W46-W50. DOI:10.1093/nar/gkad344
BiG-SCAPE BGC clustering & network analysis Navarro-Muñoz et al. (2020). Nat Chem Biol, 16:60-68. DOI:10.1038/s41589-019-0400-9

Input Requirements

Paired-end Illumina FASTQ files:

sample_R1.fastq.gz
sample_R2.fastq.gz

Important: Sample names must NOT contain spaces or special characters.


Output Structure

results/
 ├── sample1/
 │   ├── fastqc_raw/
 │   ├── fastp_output/
 │   ├── spades_output/
 │   ├── quast_output/
 │   ├── prokka_output/
 │   └── antismash_output/
 ├── bigscape_output/
 │   ├── index.html
 │   ├── network files
 │   └── GCF results
 └── logs/

Installation

A dedicated installation script is provided to:

  • Detect or install Conda automatically
  • Create required Conda environments
  • Install all dependencies (antiSMASH DBs, Pfam, BiG-SCAPE requirements)
bash install.sh

Running the Pipeline

Run the pipeline from the directory containing FASTQ files:

bash genome_pipeline.sh

BiG-SCAPE is executed once after all genomes are processed, enabling comparative analysis across the full dataset.


Results Interpretation

  • antiSMASH outputs identify BGCs per genome
  • BiG-SCAPE outputs cluster BGCs into Gene Cluster Families (GCFs)
  • Interactive visualization available via:
    results/bigscape_output/index.html
    

Applications

  • Comparative bacterial genomics
  • Natural product & secondary metabolite discovery
  • Antibiotic and bioactive compound mining
  • Functional genomics research
  • Large-scale genome annotation projects

Future Scope

  • AI-based BGC novelty prediction
  • Bioactivity prediction models
  • Automated genome & BGC summary reports
  • Integration with metabolomics (LC-MS/MS)

Citation

If you use CoGe-Pipeline in your research, please cite:

CoGe-Pipeline: Automated Bacterial Genome Annotation & BGC Discovery Pipeline
One Day One Genome (ODOG) Initiative
Bharat Genome Database (BGDB)
Navaneeth S Raju
2025. Available at: https://github.com/neonnav/CoGe

Additionally, please cite all the tools used in the pipeline (see Tools table above).


Author

Developed by Navaneeth S Raju as part of the One Day One Genome (ODOG) project


License

This project is released under the MIT License.


Support

For issues, questions, or contributions, please open an issue on GitHub or contact the BGDB team.


If you find this pipeline useful, please consider starring the repository!

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One Day One Genome Project

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