TreeN93: a non-parametric distance-based method for inferring viral transmission clusters

Summary

Highly-used methods for identifying transmission clusters of rapidly-evolving pathogens from molecular data require a user-determined distance threshold. The choice of threshold is often motivated by epidemiological information known a priori, which may be unfeasible for epidemics without rich epidemiological information. TreeN93 is a fully non-parametric distance-based method for transmission cluster identification that scales polynomially.

Availability and implementation

TreeN93 is implemented in Python 3 and is freely available at https://github.com/niemasd/TreeN93/.