The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
A Model-Based Method for Identifying Species Hybrids Using Multilocus Genetic Data
Abstract
We present a statistical method for identifying species hybrids using data on multiple, unlinked markers. The method does not require that allele frequencies be known in the parental species nor that separate, pure samples of the parental species be available. The method is suitable for both markers with fixed allelic differences between the species and markers without fixed differences. The probability model used is one in which parentals and various classes of hybrids (F1's, F2's, and various backcrosses) form a mixture from which the sample is drawn. Using the framework of Bayesian model-based clustering allows us to compute, by Markov chain Monte Carlo, the posterior probability that each individual belongs to each of the distinct hybrid classes. We demonstrate the method on allozyme data from two species of hybridizing trout, as well as on two simulated data sets.
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Citations
Cites
Inference of Population Structure Using Multilocus Genotype Data
Pritchard, J. K., Stephens, M., & Donnelly, P. (2000) · Genetics · doi:10.1093/genetics/155.2.945 · Cited by 33,908
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
On Information and Sufficiency
Kullback, S., & Leibler, R. A. (1951) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177729694 · Cited by 20,193
Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.
Geman, S., & Geman, D. (1984) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1984.4767596 · Cited by 17,949
Monte Carlo sampling methods using Markov chains and their applications.
Hastings, W. K. (1970) · Biometrika · doi:10.1093/biomet/57.1.97 · Cited by 15,195
Molecular Markers, Natural History and Evolution
Avise, J. C. (1994) · Springer eBooks · doi:10.1007/978-1-4615-2381-9 · Cited by 5,242
Detecting immigration by using multilocus genotypes
Rannala, B., & Mountain, J. L. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.17.9197 · Cited by 2,208
Markov Chain Monte Carlo in Practice
Gasparini, M. (1997) · Technometrics · doi:10.1080/00401706.1997.10485132 · Cited by 1,879
The Selection of Prior Distributions by Formal Rules
Kass, R. E., & Wasserman, L. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10477003 · Cited by 1,308
Estimation of Finite Mixture Distributions Through Bayesian Sampling
Diebolt, J., & Robert, C. P. (1994) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1994.tb01985.x · Cited by 912
Cited by
distruct: a program for the graphical display of population structure
Rosenberg, N. A. (2004) · Molecular Ecology Notes · doi:10.1046/j.1471-8286.2003.00566.x · Cited by 4,950
Hybridization as an invasion of the genome
Mallet, J. (2005) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2005.02.010 · Cited by 2,196
Bayesian species delimitation using multilocus sequence data
Yang, Z., & Rannala, B. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0913022107 · Cited by 1,405
VÄHÄ, J., & PRIMMER, C. R. (2006) · Molecular Ecology · doi:10.1111/j.1365-294x.2005.02773.x · Cited by 887
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations
Corander, J., Marttinen, P., Sirén, J., & Tang, J. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-539 · Cited by 874
Metadata
- Authors
- Anderson, E. C., & Thompson, E. A.
- Venue
- Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2002-03-01
- Volume
- 160
- Issue
- 3
- Pages
- 1217-1229
- ISSN
- 0016-6731 (ISSN-L)
- 1943-2631
- OpenAlex
- W2139718698
- Cited by
- 1,498
- References
- 24
- FWCI
- 7.00
- Type
- journal article
- Language
- en
- Open access
- closed
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