gReLU

gReLU enables comprehensive DNA sequence modeling and design pipelines using deep learning approaches.

Key Features:

• Data Preprocessing: Supports preparation of DNA sequence data for modeling workflows.
• Modeling: Provides tools for advanced sequence modeling using deep learning approaches.
• Evaluation: Enables assessment of trained DNA sequence models.
• Interpretation: Supports analysis of model predictions to reveal cis-regulatory grammar.
• Variant Effect Prediction: Predicts effects of genetic variants on regulatory activity.
• Regulatory Element Design: Enables design of synthetic DNA sequences with desired regulatory properties.

Scientific Applications:

• Regulatory Activity Prediction: Predicts cell-type-specific regulatory activity from DNA sequences.
• Cis-Regulatory Grammar Discovery: Reveals rules governing gene regulation through model interpretation.
• Variant Prioritization: Prioritizes genetic variants based on predicted functional impact.
• Synthetic DNA Design: Designs synthetic regulatory elements with specified properties.

Methodology:

gReLU implements deep learning models trained on DNA sequences.