The DOI matches its Crossref record; 149 of the 149 references it cites were found in a registry or an index.
Statistical methods in spatial genetics
Abstract
The joint analysis of spatial and genetic data is rapidly becoming the norm in population genetics. More and more studies explicitly describe and quantify the spatial organization of genetic variation and try to relate it to underlying ecological processes. As it has become increasingly difficult to keep abreast with the latest methodological developments, we review the statistical toolbox available to analyse population genetic data in a spatially explicit framework. We mostly focus on statistical concepts but also discuss practical aspects of the analytical methods, highlighting not only the potential of various approaches but also methodological pitfalls.
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Cites
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The trouble with isolation by distance
MEIRMANS, P. G. (2012) · Molecular Ecology · doi:10.1111/j.1365-294x.2012.05578.x · Cited by 624
Application of SNPs for population genetics of nonmodel organisms: new opportunities and challenges
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Circuit‐theory applications to connectivity science and conservation
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DETECTING RANGE EXPANSIONS FROM GENETIC DATA
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Metadata
- Authors
- GUILLOT, G., LEBLOIS, R., COULON, A., & FRANTZ, A. C.
- Venue
- Molecular Ecology
- Publisher
- Wiley
- Published
- 2009-11-17
- Volume
- 18
- Issue
- 23
- Pages
- 4734-4756
- ISSN
- 0962-1083 (ISSN-L)
- 1365-294X
- OpenAlex
- W2142559164
- Cited by
- 409
- References
- 149
- FWCI
- 20.14
- Type
- journal article
- Language
- en
- Open access
- closed
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- GUILLOT, G., LEBLOIS, R., COULON, A., & FRANTZ, A. C. (2009). Statistical methods in spatial genetics. Molecular Ecology. https://doi.org/10.1111/j.1365-294x.2009.04410.x
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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.
