Our trainees and mentors work across a wide spectrum of cutting-edge statistical, computational, genomic, epidemiological and population-based sciences, including:
- Analytical and statistical methods for emerging -omics technologies (e.g., genomics, transcriptomics, proteomics, metabolomics, lipidomics, epigenomics, microbiomics).
- Integration of biobank-scale datasets, electronic medical records, and -omics data to advance population and precision health.
- Single-cell data analysis, including expression profiling and eQTL studies.
- Bioinformatics approaches to functional genomics and experimentally driven datasets.
- Bridging population genetics and clinical genomics.
- Methodological innovation across the genomic continuum—from pedigree studies to GWAS, sequencing, and post-GWAS analyses.
- Population and evolutionary genetics of common, rare, and complex diseases.
- Evaluation and application of methods to assess genetic and environmental interactions in chronic diseases.
- Epigenetics and complex diseases.
- Characterizing genetic risk factors in complex traits and special populations.
- Development of novel statistical, computational, and machine-learning methods for genetic data from individuals, families, and populations.
- Design and implementation of post-GWAS technologies into population health research: next generation sequencing.
- Development and implementation of population-based family designs.