A comparison of bayesian methods for haplotype reconstruction from population genotype data.
In this report, we compare and contrast three previously published Bayesian methods for inferring haplotypes from genotype data in a population sample. We review the methods, emphasizing the differences between them in terms of both the models ("priors") they use and the computational strategies they employ. We introduce a new algorithm that combines the modeling strategy of one method with the computational strategies of another. In comparisons using real and simulated data, this new algorithm outperforms all three existing methods. The new algorithm is included in the software package PHASE, version 2.0, available online (http://www.stat.washington.edu/stephens/software.html).
Department of Statistics, University of Washington, Seattle, WA 98195-4322, USA. stephens@stat.washington.edu
Matthew
M
Stephens
Peter
P
Donnelly
D000465:Algorithms; D001499:Bayes Theorem; D005828:Genetics, Population / Q000379:methods*; D006239:Haplotypes / Q000235:genetics*; D006801:Humans; D020407:Internet; D008957:Models, Genetic; D012107:Research Design; D012984:Software