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RREFinder

Bioinformatic detection of RiPP Recognition Elements (RRE) in protein sequences.

RREFinder is a specialized tool for identifying RRE domains, which are crucial for the biosynthesis of many Ribosomally synthesized and Post-translationally modified Peptides (RiPPs). It supports both high-speed precision scanning using HMMER and sensitive exploratory discovery using HH-suite.

🚀 New Features

  • Web Interface: A modern, responsive web dashboard for easy analysis and visualization.
  • Batch Processing: Upload and analyze multiple GenBank (.gbk) or FASTA files simultaneously.
  • Domain Architecture Visualization: Interactive diagrams showing the full domain profile of proteins containing RRE hits.
  • Session History: Persistent storage of past analyses in your browser's local storage.
  • One-Click Sample: Quickly test the tool with the included Nisin sample data.

🛠 Installation

Conda Environment (Recommended)

  1. Clone the repository: 
    git clone https://github.com/QuercusCode/RREFinder-based-analysis.git
cd RREFinder-based-analysis
  2. Create the environment: 
    conda env create -f RREfinder.yml
conda activate RREfinder
  3. (Optional) Setup Exploratory Mode (HHSuite): 
    python setup_RRE_exploratory.py

Docker (Easiest for Deployment)

If you have Docker installed, you can build and run RREFinder without worrying about dependencies:

  1. Build the image: 
    docker build -t rrefinder .
  2. Run the container: 
    docker run -p 5000:5000 rrefinder

This will automatically set up the environment, binaries, and download the necessary databases.

🌐 Running the Web UI

  1. Activate the environment: conda activate RREfinder
  2. Start the Flask server: 
    python app.py
  3. Open your browser and navigate to http://127.0.0.1:5000

💻 Command Line Usage

RREFinder can also be used directly from the terminal:

# Analyze a GenBank file in precision mode
python RRE.py -i my_sequence.gbk -m precision my_project

# Analyze a FASTA file
python RRE.py -i my_proteins.fasta -t fasta my_project

Output results are stored in the output/ directory.

📚 Citations

If you use RREFinder in your research, please cite:

  • RREFinder: Kloosterman AM, Cimermancic P, Elsayed SS, et al. (2020). Expansion of GenBank and the RRE-Finder Tool for the Discovery of Novel RiPPs. (See paper for full citation).
  • HMMER (Precision Mode): Eddy SR. (2011). Accelerated Profile HMM Searches. PLoS Computational Biology, 7(10), e1002195.
  • HH-suite (Exploratory Mode): Steinegger M, et al. (2019). HH-suite3 for homology detection and structure prediction. BMC Bioinformatics, 20(1), 473.

📄 License

This project is licensed under the terms included in the LICENSE file.