Efficient Recycled Algorithms for Quantitative Trait Models on Phylogenies

Gordon Hiscott; Colin Fox; Matthew Parry; David Bryant

doi:10.1093/gbe/evw064

Efficient Recycled Algorithms for Quantitative Trait Models on Phylogenies

Genome Biol Evol. 2016 May 12;8(5):1338-50. doi: 10.1093/gbe/evw064.

Authors

Gordon Hiscott¹, Colin Fox², Matthew Parry¹, David Bryant³

Affiliations

¹ Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand.
² Department of Physics, University of Otago, Dunedin, New Zealand.
³ Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand david.bryant@otago.ac.nz.

Abstract

We present an efficient and flexible method for computing likelihoods for phenotypic traits on a phylogeny. The method does not resort to Monte Carlo computation but instead blends Felsenstein's discrete character pruning algorithm with methods for numerical quadrature. It is not limited to Gaussian models and adapts readily to model uncertainty in the observed trait values. We demonstrate the framework by developing efficient algorithms for likelihood calculation and ancestral state reconstruction under Wright's threshold model, applying our methods to a data set of trait data for extrafloral nectaries across a phylogeny of 839 Fabales species.

Keywords: comparative method; continuous traits; likelihood algorithm; numerical integration; numerical quadrature; quantitative traits.

MeSH terms

Algorithms*
Fabaceae / genetics*
Monte Carlo Method
Phenotype
Phylogeny*
Quantitative Trait Loci / genetics*