Grand Challenges: Accurate, Equitable, and Transparent Genetic Ancestry Inference
Grant Type: Individual Project Grant
Topics: Social Justice, Health, Ethical, Fair, and Trustworthy Technology
College Represented: CMNS
The proposed project seeks to develop improved computational methods to more accurately infer genetic ancestry at the sub-chromosome level, i.e., segments of chromosomes. To more fully achieve healthcare justice, and to separate genetic factors from social and environmental sources of health disparity, we need to recognize the genetic diversity of individuals at the level of their chromosomal segments. More generally, the information gained from these ancestry inferences is significant in clinical research as well as in the understanding of the general principles governing population genetics, evolution, and the genetic basis of human biology.
PI: Michael Cummings (CMNS),
Professor, Biology and
Institute for Advanced Computer Studies