help button home button Genetics Email Content Delivery
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Originally published as Genetics Published Articles Ahead of Print on June 11, 2007.

Genetics, Vol. 177, 347-358, September 2007, Copyright © 2007
doi:10.1534/genetics.107.071910

This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
genetics.107.071910v1
177/1/347    most recent
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Meligkotsidou, L.
Right arrow Articles by Fearnhead, P.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Meligkotsidou, L.
Right arrow Articles by Fearnhead, P.

Postprocessing of Genealogical Trees

Loukia Meligkotsidou1 and Paul Fearnhead

Department of Mathematics and Statistics, Lancaster University, Lancaster, LA1 4YF, United Kingdom

1 Corresponding author: Department of Mathematics and Statistics, Lancaster University, Lancaster, LA1 4YF, United Kingdom.
E-mail: l.meligotsidou{at}lancaster.ac.uk

We consider inference for demographic models and parameters based upon postprocessing the output of an MCMC method that generates samples of genealogical trees (from the posterior distribution for a specific prior distribution of the genealogy). This approach has the advantage of taking account of the uncertainty in the inference for the tree when making inferences about the demographic model and can be computationally efficient in terms of reanalyzing data under a wide variety of models. We consider a (simulation-consistent) estimate of the likelihood for variable population size models, which uses importance sampling, and propose two new approximate likelihoods, one for migration models and one for continuous spatial models.






HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2007 by the Genetics Society of America.