XMU-Kuangnan-Fang-Team/GENetLib
A Python library for Gene–environment interaction analysis via deep learning
Integrates minimax concave penalty (MCP) and L₂-norm regularization within neural network layers to identify gene-environment interactions in high-dimensional genomic data. Handles both scalar and functional (densely-measured) input formats with support for continuous, binary, and survival outcomes, using B-spline basis expansion for functional data analysis. Built on PyTorch with modular architecture enabling flexible model composition across multiple hidden layers and customizable regularization parameters.
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196
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21
Language
Python
License
MIT
Category
Last pushed
Sep 24, 2025
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