AquaaG: Automated Quality Assessment and Annotation of Genomes

AquaaG is a Python-based pipeline for:

Downloading genomic assemblies from NCBI
Performing quality assessment with QUAST
Annotating genomes:
- Prokaryotic genomes with Prokka
- Eukaryotic genomes with BRAKER3 (Docker-based, repeat masked)
Evaluating annotation completeness with BUSCO

It supports India-specific filtering of assemblies (based on submitter metadata) and can also process user-provided assembly IDs via a file (assembly.txt). AquaaG is designed for production-grade bioinformatics workflows and supports both prokaryotic (PK) and eukaryotic (EK) organisms.

✨ Features

Assembly Fetching
- Automated download from the NCBI Assembly database
- Optional India-specific submitter filtering
Quality Assessment
- Assembly evaluation using QUAST
Annotation
- PK: Prokka-based genome annotation
- EK:
  - RepeatModeler for repeat library construction
  - RepeatMasker for genome masking
  - BRAKER3 gene prediction using GeneMark-ETP and AUGUSTUS
Completeness Evaluation
- BUSCO analysis on predicted protein sets
Flexible Execution Modes
- Species mode: --species "Genus species"
- Kingdom mode: --kingdom Bacteria/Fungi
- Assembly list mode: --assembly-file assembly.txt
- India-only filtering: -I / --india-only
- Any-source mode: -a / --any-source
Parallel & Configurable
- Multi-threaded execution (QUAST, Prokka, BRAKER3, BUSCO)
- All parameters controlled via YAML configuration files

🧩 Requirements

Operating System: Linux (Ubuntu / HPC compatible)
Conda: Miniconda or Anaconda
Docker: Required for eukaryotic annotation
Internet: Required for NCBI, BUSCO datasets, Docker pulls
Disk Space: Minimum 10–20 GB recommended

📦 Installation & Setup

git clone https://github.com/skbinfo/AquaaG.git
cd AquaaG
bash setup_new.sh
source ~/.bashrc
conda activate assembly_tool_env

Verify Installation

quast.py --version
prokka --version
busco --version
docker --version

⚙️ Configuration Files

Eukaryotic Configuration (Eu_config.yaml)

email: "your@email.com"
organism: "Arabidopsis thaliana"
organism_type: "EK"
quast_threads: 50
busco_lineage: "fungi_odb10"
busco_params:
  cpu: 50
braker_params:
  cpus: 50

Prokaryotic Configuration (Pr_config.yaml)

email: "your@email.com"
organism: "Mycobacterium tuberculosis"
organism_type: "PK"
group: "bacteria"
quast_threads: 8
busco_lineage: "bacteria_odb10"
busco_params:
  cpu: 8
prokka_params:
  cpus: 8

🚀 Running AquaaG

python AquaaG.py -c CONFIG.yaml -o OUTPUT_DIR [OPTIONS]

Examples

# Eukaryotic (India-only)
python AquaaG.py -c Eu_config.yaml -o output_eu --species "Arabidopsis thaliana" -I --num-assemblies 1

# Prokaryotic (Kingdom mode)
python AquaaG.py -c Pr_config.yaml -o output_pk --kingdom Bacteria --num-species 3 --num-assemblies 1 -a

📁 Output Structure

Each run produces organized directories containing QUAST reports, annotation outputs, BUSCO summaries, and log files for full reproducibility.

🛠 Troubleshooting

Ensure Docker daemon is running for EK pipelines
Check BUSCO lineage availability
Verify internet connectivity for NCBI downloads
Use -a flag if species-specific filtering is too strict

Figure 1. AquaaG workflow overview

Figure 2. Prokaryotic genome annotation outputs (Prokka)

Figure 3. Eukaryotic genome annotation outputs (BRAKER3)

⬇️ Download AquaaG

git clone https://github.com/skbinfo/AquaaG.git

🤝 Contributions & Acknowledgements

Contributions are welcome via GitHub issues and pull requests. If you use AquaaG in your research, please cite the corresponding publication.