A Comparison of Bayesian Methods for Haplotype Reconstruction from Population Genotype Data
The American Journal of Human GeneticsPublished 24 October 2003Open access
Matthew Stephens, Peter Donnelly
Citations3,533
SJR quartileQ1
SJR score4.53
SNIP2.47
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TL;DR
A new algorithm is introduced that combines the modeling strategy of one method with the computational strategies of another and outperforms all three existing methods for inferring haplotypes from genotype data in a population sample.
Abstract
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).
Keywords
MedicineBiochemistry, Genetics and Molecular Biology
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