- THIS ARTICLE
- Full Text
- Full Text (PDF)
- Alert me when this article is cited
- Alert me if a correction is posted
- SERVICES
- Similar articles in this journal
- Similar articles in PubMed
- Alert me to new issues of the journal
- Download to citation manager
- Reprints & Permissions
- CITING ARTICLES
- Citing Articles via HighWire
- Citing Articles via Google Scholar
- GOOGLE SCHOLAR
- Articles by RoyChoudhury, A.
- Articles by Stephens, M.
- Search for Related Content
- PUBMED
- PubMed Citation
- Articles by RoyChoudhury, A.
- Articles by Stephens, M.
Genetics, Vol. 176, 1363-1366, June 2007, Copyright © 2007
doi:10.1534/genetics.105.049080
Fast and Accurate Estimation of the Population-Scaled Mutation Rate,
, From Microsatellite Genotype Data
Arindam RoyChoudhury1 and Matthew Stephens
Department of Statistics, University of Washington, Seattle, Washington 98195-4322
1 Corresponding author: Wakeley Lab, 4092-4100 Biological Laboratories, 16 Divinity Ave., Harvard University, Cambridge, MA 02138.
E-mail: aroy{at}fas.harvard.edu
We present a new approach for estimation of the population-scaled mutation rate,
, from microsatellite genotype data, using the recently introduced "product of approximate conditionals" framework. Comparisons with other methods on simulated data demonstrate that this new approach is attractive in terms of both accuracy and speed of computation. Our simulation experiments also demonstrate that, despite the theoretical advantages of full-likelihood-based methods, methods based on certain summary statistics (specifically, the sample homozygosity) can perform very competitively in practice.
This article has been cited by other articles:
![]() |
F. Rousset and R. Leblois Likelihood and Approximate Likelihood Analyses of Genetic Structure in a Linear Habitat: Performance and Robustness to Model Mis-Specification Mol. Biol. Evol., December 1, 2007; 24(12): 2730 - 2745. [Abstract] [Full Text] [PDF] |
||||
![]() |
P. Beerli Estimation of the Population Scaled Mutation Rate From Microsatellite Data Genetics, November 1, 2007; 177(3): 1967 - 1968. [Full Text] [PDF] |
||||

