macsSwigmodels

NamemacsSwigmodels
DescriptionEvery individual’s genome carries within it the history of all the ancestors of that individual. Thus, by analyzing a small number of genomes, we can accurately infer the demographic history of entire human populations. This demographic history helps establish a baseline that is needed for research and discovery in medical genomics. We are using a process to more accurately infer the demographic history of human populations by comparing genomic statistics from millions of genome simulations to real population genomic data. While other researchers have worked with this process using only a few individuals or a portion of a chromosome, we are pushing the limit of computing capabilities by simulating whole chromosomes of hundreds of individuals. Using the whole chromosome allows us to look at more recent demographic history, which is particularly helpful in finding genetic links to disease processes. After publication, we will make our pipeline available so other researchers can apply it to other populations. This project pushes the frontier of genomic research in that it uses new methods, simulates a larger part of the genome, and is being applied to populations not yet thoroughly studied.
OrganizationUniversity of Arizona
DepartmentEcology and Evolutionary Biology
Sponsor Campus GridOSG Connect
Principal Investigator
Ariella Gladstein
Field Of ScienceEvolutionary Sciences
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