Predictions of native American population structure using linguistic covariates in a hidden regression framework.

ABSTRACT:

Background

The mainland of the Americas is home to a remarkable diversity of languages, and the relationships between genes and languages have attracted considerable attention in the past. Here we investigate to which extent geography and languages can predict the genetic structure of Native American populations.

Methodology/principal findings

Our approach is based on a Bayesian latent cluster regression model in which cluster membership is explained by geographic and linguistic covariates. After correcting for geographic effects, we find that the inclusion of linguistic information improves the prediction of individual membership to genetic clusters. We further compare the predictive power of Greenberg's and The Ethnologue classifications of Amerindian languages. We report

SUBMITTER: Jay F 

PROVIDER: S-EPMC3031544 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature