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Research |
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Our research aims to understand how evolutionary forces are expected to shape genetic diversity within populations, and then uses this understanding to learn about demographic and selective histories and processes from genome sequencing data.
One focus of our research is on developing population genetic theory that lets us predict patterns of diversity and genetic structure under varying models of demography and selection. Another focus is on turning that theory into computational tools to compare model predictions to observations from natural populations. Finally, we have a strong interest in inferring (mostly) human evolutionary history from genetic data, including both ancient history and population structure as well as more recent migrations, movements, and dynamics.
Most of our projects therefore combine at least some of developing mathematical theory, running large-scale simulations, building and maintaining software, and inferring history from whole-genome sequencing data.
Read our lab guidelines and expectations.
- Deep population structure and human origins
- Demographic history of admixed populations
- Inference of dominance and epistatic interactions from genetic data
- The impact of natural selection on diversity statistics and evolutionary dynamics
- Theoretical and computational approaches for diversity statistics and simulation
- Simon Gravel, McGill University
- Brenna Henn, UC Davis
- Andres Moreno, LANGEBIO-Cinvestav
- Kevin Thornton, UC Irvine