The DOI matches its Crossref record.
A New Statistic for Detecting Genetic Differentiation
Abstract
A new statistic for detecting genetic differentiation of subpopulations is described. The statistic can be calculated when genetic data are collected on individuals sampled from two or more localities. It is assumed that haplotypic data are obtained, either in the form of DNA sequences or data on many tightly linked markers. Using a symmetric island model, and assuming an infinite-sites model of mutation, it is found that the new statistic is as powerful or more powerful than previously proposed statistics for a wide range of parameter values.
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Cited by
CARLSSON, J., McDOWELL, J. R., DÍAZ‐JAIMES, P., CARLSSON, J. E. L., BOLES, S. B., GOLD, J. R., & GRAVES, J. E. (2004) · Molecular Ecology · doi:10.1111/j.1365-294x.2004.02336.x · Cited by 184
Kunal, S. P., Kumar, G., Menezes, M. R., & Meena, R. M. (2013) · Conservation Genetics · doi:10.1007/s10592-013-0445-3 · Cited by 55
Munshi-South, J. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003228 · Cited by 20
Metadata
- Authors
- Hudson, R. R.
- Venue
- Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2000-08-01
- Volume
- 155
- Issue
- 4
- Pages
- 2011-2014
- ISSN
- 0016-6731 (ISSN-L)
- 1943-2631
- OpenAlex
- W2170284968
- Cited by
- 637
- References
- 0
- FWCI
- 2.60
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
