Software and data are available post-publication at the Ramachandran Lab Data Repository. Lab members should contact Sohini Ramachandran for a repository account.
X-chromosomal and autosomal data from the Human Genome Diversity Panel, analyzed in S. Ramachandran, N.A. Rosenberg, M.W. Feldman, and J. Wakeley (2008), "Population differentiation and migration: coalescence times in a two-sex island model for autosomal and X-linked loci". Theor Pop Biol. Vol. 74:291-301
pong is a freely available software package for post-processing output from clustering inference using population genetic data. It combines a a network-graphical approach for analyzing and visualizing membership in latent clusters with an interactive D3.js-based visualization. pong outpaces current solutions by more than an order of magnitude in runtime while providing a user-friendly, interactive visualization of population structure that is more accurate than those produced by current tools. Thus, pong enables unprecedented levels of scale and accuracy in the analysis of population structure from multilocus genotype data.
pong requires Python 2.7 and a modern web browser (e.g. Chrome, Firefox, Safari). pong is not compatible with Internet Explorer. pong is hosted on PyPI and can thus be easily installed with
pip by running:
pip install pong