A novel parallel approach to the likelihood-based estimation of admixture in population genetics

Giovannini, A., Zanghirati, G., Beaumont, M. A., Chikhi, L. and Barbujani, G. (2009) A novel parallel approach to the likelihood-based estimation of admixture in population genetics. Bioinformatics, 25 (11). pp. 1440-1441. ISSN 1367-4803 doi: 10.1093/bioinformatics/btp136

Abstract/Summary

Inferring population admixture from genetic data and quantifying it is a difficult but crucial task in evolutionary and conservation biology. Unfortunately state-of-the-art probabilistic approaches are computationally demanding. Effectively exploiting the computational power of modern multiprocessor systems can thus have a positive impact to Monte Carlo-based simulation of admixture modeling. A novel parallel approach is briefly described and promising results on its message passing interface (MPI)-based C implementation are reported.