Case Study: University of Copenhagen maps global genetic diversity faster with Julia Computing

Researchers map global genetic diversity using Julia

The University of Copenhagen, working with Peking University and Imperial College London, needed a way to analyze massive genetic datasets and identify trends in global genetic diversity. They turned to Julia Computing and the Julia programming language to make their research code clearer, more reproducible, and easier to work with.

Using Julia, the team georeferenced 92,801 mitochondrial sequences across 4,500+ species and mapped global genetic diversity. Julia Computing helped deliver major performance gains, with the key grid-cell analysis running about 100 times faster than in R, while also supporting a study showing that genetic diversity is 27% higher in the tropics and lower in areas more affected by humans.

University of Copenhagen

Michael Krabbe Borregaard

Co-Author