Chia-Chi Flora Huang

The paper develops a motif-based model to predict sequence variant effects in AR enhancers and identifies functional classes of transcription factors, validated against mutagenesis data and GWAS risk alleles.

The paper identifies breast cancer risk SNPs that overlap with estrogen receptor binding sites, showing their role in altering estrogen signaling through chromatin interactions.

This study develops snpSTARRseq, a high-throughput method to test non-coding variants from GWAS, showing 37% of prostate cancer risk loci alter enhancer activity.

The paper introduces CWAS, a method linking genetic variation to chromatin states, identifying novel prostate cancer risk loci and regulatory mechanisms not detectable by eQTLs.