Title | A spatial dirichlet process mixture model for clustering population genetics data. |
Publication Type | Journal Article |
Year of Publication | 2011 |
Authors | Reich, Brian J., and Howard D. Bondell |
Journal | Biometrics |
Volume | 67 |
Issue | 2 |
Pagination | 381-90 |
Date Published | 2011 Jun |
ISSN | 1541-0420 |
Keywords | Algorithms, Animals, Bayes Theorem, Cluster Analysis, Computer Simulation, Genetics, Population, Microsatellite Repeats, Montana, Mustelidae |
Abstract | Identifying homogeneous groups of individuals is an important problem in population genetics. Recently, several methods have been proposed that exploit spatial information to improve clustering algorithms. In this article, we develop a Bayesian clustering algorithm based on the Dirichlet process prior that uses both genetic and spatial information to classify individuals into homogeneous clusters for further study. We study the performance of our method using a simulation study and use our model to cluster wolverines in Western Montana using microsatellite data. |
DOI | 10.1111/j.1541-0420.2010.01484.x |
Alternate Journal | Biometrics |
Original Publication | A spatial dirichlet process mixture model for clustering population genetics data. |
PubMed ID | 20825394 |
PubMed Central ID | PMC3043140 |
Grant List | R01 ES014843-01A2 / ES / NIEHS NIH HHS / United States R01 MH084022 / MH / NIMH NIH HHS / United States R01 MH084022-02 / MH / NIMH NIH HHS / United States 1 R01 MH084022-01A1 / MH / NIMH NIH HHS / United States R01 ES014843 / ES / NIEHS NIH HHS / United States R01 MH084022-03 / MH / NIMH NIH HHS / United States P01 CA142538 / CA / NCI NIH HHS / United States R01 MH084022-01A1 / MH / NIMH NIH HHS / United States |
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