I study how geography shapes genetic variation within and among species. Some of my recent research has mapped growth rates in expanding hummingbird populations, applied new population genetic models for simulating evolution in continuous space, and developed a deep-learning method for predicting the spatial location of a sample from its genotype.
I'm currently a NRSA postdoctoral fellow in the Kern Lab at the University of Oregon Institute of Ecology and Evolution, where I'm developing simulation and machine learning tools to help us describe and control for spatial structure in population genetic data.
Scroll down for publication PDFs, links to code, and pictures of animals.
driftR: an interactive population genetic simulation website that allows students to explore the impacts of genetic drift, selection, migration, mutation, and population sizes on a variety of summary statistics.https://cjbattey.shinyapps.io/driftR/
adaptR: simulate selective sweeps and other processes with varying selection over time.https://cjbattey.shinyapps.io/adaptR/
structurePlotter: plot output of genotype clustering algorithms with fancy color selection and a permutation algorithm to deal with label switching.https://cjbattey.shinyapps.io/structurePlotter/