Random partition models and exchangeability for Bayesian identification of population structure

Bulletin of Mathematical Biology
Jukka CoranderTimo Koski

Abstract

We introduce a Bayesian theoretical formulation of the statistical learning problem concerning the genetic structure of populations. The two key concepts in our derivation are exchangeability in its various forms and random allocation models. Implications of our results to empirical investigation of the population structure are discussed.

References

Apr 1, 1977·Theoretical Population Biology·J F Kingman
Jun 3, 2000·Genetics·J K PritchardP Donnelly
Sep 1, 1992·Proceedings of the National Academy of Sciences of the United States of America·T Nagylaki
Apr 20, 2002·Mathematical Biosciences·Mats Gyllenberg, Timo Koski
Feb 15, 2003·Genetics·Jukka CoranderMikko J Sillanpää
Apr 10, 2004·Bioinformatics·Jukka CoranderMikko J Sillanpää
Jan 22, 2005·Molecular Ecology·Daniel DieringerChristian Schlötterer
Nov 1, 1992·TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·A Fleuriet, D Sperlich

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Citations

Mar 20, 2009·BMC Bioinformatics·Pekka MarttinenJukka Corander
Aug 8, 2009·PLoS Computational Biology·Jing TangJukka Corander
May 28, 2008·TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·Petr SmýkalMiroslav Griga
Sep 10, 2015·IEEE Transactions on Pattern Analysis and Machine Intelligence·Paul BlomstedtJukka Corander
Nov 26, 2008·IEEE Transactions on Pattern Analysis and Machine Intelligence·Pekka MarttinenJukka Corander

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