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Ke Hao

Ke Hao, PhD

About Me

Research Interests:

  • Integrative genomics and xQTLs of disease relevant tissue
  • Health effect of environmental toxin exposure
  • Somatic structure alternation (SV) in cancer genome
  • Algorithm in detecting and genotyping germline CNV and CNV-based association studies

Biography and Research Activities:

Dr. Hao is currently a professor of the Department of Genetics and Genomic Sciences. Dr. Hao received his ScD degree and postdoc training at Harvard University and has extensive expertise in statistical genetics, computational biology and environmental health. Over the past decade, Dr. Hao has contributed significantly in these areas.   He systematically collected large datasets of human tissue samples, and generated molecular trait quantitative loci (xQTLs), including adipose, blood vessel wall, skeleton muscle, lung, liver, brain, placenta, intestine, whole blood, monocyte, macrophage, etc.  Further he integrated the xQTLs with large GWAS data to identify genetic basis of human diseases and discover the mechanism: genetic variants → molecular/cellular alternation → disease.  Dr. Hao developed ensembleCNV tool, which detects and genotypes germline copy number variants (CNV) on large scale population data (e.g GWAS).  EnsembleCNV is the best-performing CNV caller to date, and achieves accuracy and call-rate comparable to SNP genotype, which paves the path for large CNV-based association studies.  Dr. Hao also invented Bio3Air, a system consisted of smartphone APP and wearable devices, for long term monitoring of individual-level air pollution exposure. Bio3Air has been applied to human cohorts in multiple funded studies. 

The productive research of Dr. Hao in diverse and inter-related field lead to a number of high profile papers in Nature GeneticsScienceNature Communications, and Nature Neurosciences


PROFESSOR | Genetics and Genomic Sciences
Research Topics

Biostatistics, Genetics, Mathematical and Computational Biology

Multi-Disciplinary Training Areas

Genetics and Genomic Sciences [GGS]