Bio

I’m a Postdoctoral Scholar in the Department of Biomedical Data Sciences at Stanford University. I’m currently an Associate Member of the Human Pan Reference Genome Project and the coordinator for the HLA working group of the Clinical Genome Resource. Previously, I was at the University of Michigan, where I did my PhD in Anthropology.

My primary research interests are to investigate how natural selection shapes human populations–particularly how infectious disease shapes the genome. By incorporating an evolutionary framework, we can better understand modern health and disease. I am working on detecting regions of the genome that have undergone selection in Mesoamerican populations, and expanding that work to medical relevance today. I am currently working on various HLA related projects, Dengue, and on COVID-19.

Professional Education

  • Doctor of Philosophy, University of Michigan Ann Arbor (2020)
  • Master of Arts, University of Michigan Ann Arbor (2015)
  • Bachelor of Arts, Oberlin College (2009)

Stanford Advisors

Contact

  • Academic
    oagc@stanford.edu
    University - Scholar Department: Biomedical Data Science Position: Postdoctoral Scholar

Additional Info

Links

All Publications

  • Genetic adaptations to potato starch digestion in the Peruvian Andes Jorgensen, K. C., Garcia, O. A., Kiyamu, M., Rivera-Chira, M., Leon-Velarde, F., Brutsaert, T. D., Bigham, A. W. WILEY. 2021: 52

    View details for Web of Science ID 000625180200196

  • Identifying adaptive alleles in the human genome: from selection mapping to functional validation. Human genetics Werren, E. A., Garcia, O. n., Bigham, A. W. 2021; 140 (2): 241–76

    Abstract

    The suite of phenotypic diversity across geographically distributed human populations is the outcome of genetic drift, gene flow, and natural selection throughout human evolution. Human genetic variation underlying local biological adaptations to selective pressures is incompletely characterized. With the emergence of population genetics modeling of large-scale genomic data derived from diverse populations, scientists are able to map signatures of natural selection in the genome in a process known as selection mapping. Inferred selection signals further can be used to identify candidate functional alleles that underlie putative adaptive phenotypes. Phenotypic association, fine mapping, and functional experiments facilitate the identification of candidate adaptive alleles. Functional investigation of candidate adaptive variation using novel techniques in molecular biology is slowly beginning to unravel how selection signals translate to changes in biology that underlie the phenotypic spectrum of our species. In addition to informing evolutionary hypotheses of adaptation, the discovery and functional annotation of adaptive alleles also may be of clinical significance. While selection mapping efforts in non-European populations are growing, there remains a stark under-representation of diverse human populations in current public genomic databases, of both clinical and non-clinical cohorts. This lack of inclusion limits the study of human biological variation. Identifying and functionally validating candidate adaptive alleles in more global populations is necessary for understanding basic human biology and human disease.

    View details for DOI 10.1007/s00439-020-02206-7

    View details for PubMedID 32728809

https://orcid.org/0000-0001-6150-6118