Making Sense of Genetic Variation Through Ancestries

Supervisor: Jinko Graham

Researchers study patterns of genetic variation to learn about evolution, migration and population growth, and to identify specific genetic variants that influence inherited traits. A recent breakthrough in the study of genetic variation is the succinct tree sequence (STS), a novel data structure that represents the ancestry of whole genomes and allows the efficient storage of population-scale data. Recently developed software for simulation and inference of STSs from population samples is made freely available as Python modules. This research project will involve getting to know the software, exploring its features and adding 3-5 new tutorials to a collection of existing RMarkdown tutorials for statisticians. We are looking for someone who is curious about data on genetic variation and its uses. Experience with RMarkdown and Python would be an asset.