py2rely - The Python Pipeline To Rely On

Pythonic to Relion interface for streamlined sub-tomogram averaging on SLURM HPC clusters.

Introduction

py2rely simplifies and accelerates the execution of RELION-based sub-tomogram averaging (STA) workflows on SLURM-based high-performance computing (HPC) systems. Designed for rapid iteration and evaluation of particle picking strategies, py2rely integrates with existing tilt series alignment from AreTomo and particle coordinate storage from copick, making it ideal for automated benchmarking and structure validation.

💫 Key Features

• ⚙️ Automated job preparation: One-command setup of RELION STA workflows including particle extraction, classification, and refinement.
• 🔄 Copick integration: Seamless import of particle coordinates from copick metadata storage.
• 🧭 Tilt series-aware: Direct input of alignment and metadata from AreTomo processing pipelines.
• 🚀 SLURM-native execution: Jobs are launched, monitored, and managed directly on HPC SLURM environments.
• 🧠 Validation-ready: Quickly test new particle picking algorithms and assess their reconstruction outcomes with minimal setup.

🚀 Getting Started

Installation

To create, first we need to generate a conda environment:

conda create -n pyRely python=3.10

Once the environment is created, activate it: conda activate pyRely

Then install the code with: pip install -e .

Basic Usage

py2rely provides a clean, scriptable command-line interface. Run the following command to view all the available sub-commands:

py2rely -h

📚 Documentation

For comprehensive guides, usage examples, and API references, visit the py2rely documentation.

🤝 Contributing

This project adheres to the Contributor Covenant code of conduct. By participating, you are expected to uphold this code. Please report unacceptable behavior to [email protected].

🔒 Security

If you believe you have discovered a security vulnerability, please report it responsibly to [email protected].