Grace Tzun-Wen Shaw

The paper develops MoDIFI, a Bayesian framework to prioritize cell lines and regulatory regions for testing noncoding variants associated with neurodevelopmental disorders.

This paper introduces CATMINT, a method to estimate gene-level intolerance across variant categories, showing it outperforms existing metrics and reveals category-specific intolerance patterns in disease genes.

This study shows that adjusting for ancestry improves genome-wide estimates of regional intolerance by incorporating demographic history, leading to better variant classification.

The paper develops a Bayesian method to detect balancing selection across different sequencing technologies and identifies novel genes under selection in complex genomic regions.