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


BACKGROUND
The software package parLEA is freely available at (http://dm.unife.it/parlea).
Giovannini
Ambra
A
Department of Mathematics and Math4Tech Center, University of Ferrara, Ferrara, Italy. ambra.giovannini@unife.it
Zanghirati
Gaetano
G
Beaumont
Mark A
MA
Chikhi
Lounès
L
Barbujani
Guido
G
D019295:Computational Biology / Q000379:methods*; D019143:Evolution, Molecular; D005828:Genetics, Population / Q000379:methods*; D016013:Likelihood Functions; D009010:Monte Carlo Method