ML-based methods for multivariate genetic association analysis
Designed ML-MAGES, a machine-learning framework for shrinkage, pattern discovery, and gene-level aggregation in high-dimensional genetic association studies.
- Uses neural-network-based supervised learning to account for LD-induced inflation.
- Combines effect size shrinkage with flexible clustering of multi-trait association patterns.
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