Dongkeun Jang

The paper integrates multiple scRNA-seq datasets to create a comprehensive atlas of human pancreatic islets, identifying 13 cell populations and providing a resource for diabetes research.

The paper describes the Common Fund Data Ecosystem (CFDE), which integrates NIH Common Fund data resources to enable discovery, analysis, and collaboration across heterogeneous datasets.

GWASHub is a cloud-based platform for GWAS meta-analysis that automates data handling, QC, and analysis workflows to improve reproducibility and reduce researcher burden.

The paper introduces the Neurodegenerative Disease Knowledge Portal (NDKP), an open-science platform aggregating genomic datasets for neurodegenerative diseases to enable collaborative analysis and discovery.

This study uses proteome-phenome-wide Mendelian randomization across three ancestries to identify protein-phenotype associations and potential therapeutic targets.

The paper introduces the T1D Knowledge Portal, a resource for querying genetic and functional data related to type 1 diabetes to aid in hypothesis generation and target discovery.

The paper identifies high-resolution eQTLs in kidney tissues using Bayesian fine mapping with integrative priors, improving resolution and functional relevance.

The paper identifies variance-quantitative trait loci (vQTLs) and gene-environment interactions (GEIs) for cardiometabolic serum biomarkers using UK Biobank data.

The paper introduces the Effector Index, an algorithm to predict causal genes at GWAS loci using genomic features, achieving 85% AUC in type 2 diabetes validation.

The paper introduces the Lipid Droplet Knowledge Portal, a resource integrating datasets on lipid droplet biology to uncover new determinants of lipid storage.

A coronary artery disease GWAS of 181,522 cases among 1,165,690 participants yields 241 associations (54 new); an eight-predictor consensus nominates 185 candidate causal genes, 94 with ≥3 predictors.