Document Detail


A spatial dirichlet process mixture model for clustering population genetics data.
MedLine Citation:
PMID:  20825394     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
Brian J Reich; Howard D Bondell
Related Documents :
10916254 - Clustering ecg complexes using hermite functions and self-organizing maps.
19552644 - Three estimates of the association between linear growth failure and cognitive ability.
11756254 - Clustering of environments of southern soft red winter wheat region for milling and bak...
8403864 - A computer program for regression analysis of repeated measures using generalized estim...
8907394 - Frequency distribution of wuchereria bancrofti infection in the vector host in relation...
21859134 - A new two-state polymer folding model and its application to α-helical polyalanine.
Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2010-09-03
Journal Detail:
Title:  Biometrics     Volume:  67     ISSN:  1541-0420     ISO Abbreviation:  Biometrics     Publication Date:  2011 Jun 
Date Detail:
Created Date:  2011-06-21     Completed Date:  2011-11-09     Revised Date:  2014-09-20    
Medline Journal Info:
Nlm Unique ID:  0370625     Medline TA:  Biometrics     Country:  United States    
Other Details:
Languages:  eng     Pagination:  381-90     Citation Subset:  IM    
Copyright Information:
© 2010, The International Biometric Society.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Algorithms
Animals
Bayes Theorem
Cluster Analysis*
Computer Simulation
Genetics, Population / methods*
Microsatellite Repeats
Montana
Mustelidae / genetics
Grant Support
ID/Acronym/Agency:
1 R01 MH084022-01A1/MH/NIMH NIH HHS; P01 CA142538/CA/NCI NIH HHS; R01 ES014843/ES/NIEHS NIH HHS; R01 ES014843-01A2/ES/NIEHS NIH HHS; R01 MH084022/MH/NIMH NIH HHS; R01 MH084022-01A1/MH/NIMH NIH HHS; R01 MH084022-02/MH/NIMH NIH HHS; R01 MH084022-03/MH/NIMH NIH HHS
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Mixed-effects state-space models for analysis of longitudinal dynamic systems.
Next Document:  Likelihood methods for binary responses of present components in a cluster.