Subramanian S. Ajay

This paper develops a genome-wide cardiovascular disease genetic risk assessment test that includes monogenic conditions, risk alleles, pharmacogenomic variants, and polygenic risk scores, showing high performance and scalability.

This study evaluates copy number variant detection in clinical whole genome sequencing, finding it as sensitive as microarrays with additional variants, and identifies clinically significant CNVs in 15% of cases.

The paper introduces ExpansionHunter, a tool for detecting long repeat expansions from PCR-free WGS data, achieving high sensitivity and specificity in identifying pathogenic expansions.