Jae Hoon Sul

CoPheScan improves PheWAS by accounting for linkage disequilibrium, identifying causal associations and reducing false positives in genetic variant analyses.

The paper explores the relationship between genomic ancestry and health outcomes using a biobank linked to electronic health records, finding disease stratification across ancestry clusters.

This study identifies gene sets associated with Tourette Syndrome using genome-wide data, highlighting synaptic and immune-related pathways.

Bisque estimates cell composition in bulk RNA-seq using single-cell data, improving accuracy and efficiency over existing methods.

This study examines genetic risk for bipolar disorder in extended families, finding that both common and rare variants contribute to susceptibility, with no significant segregation of large-effect variants.

ForestQC improves variant quality control by combining filtering and machine learning, outperforming existing methods on whole-genome sequencing datasets.

The paper analyzes genomic diversity in Latin American population isolates, finding increased genetic diversity and consanguinity compared to the Finnish isolate.

This paper develops a statistical method that uses allele-specific expression and eQTL data to improve fine-mapping of causal variants for gene expression, achieving higher specificity than eQTL-only approaches.

The paper introduces a meta-analysis method to identify eQTLs from multi-tissue datasets, detecting more eQTLs and eGenes than previous approaches.

This paper introduces eCAVIAR, a method to compute colocalization posterior probability between GWAS and eQTL signals to identify target genes and tissues for complex traits.