2017
DOI: 10.1111/biom.12667
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Visualizations for Genetic Assignment Analyses Using the Saddlepoint Approximation Method

Abstract: We propose a method for visualizing genetic assignment data by characterizing the distribution of genetic profiles for each candidate source population. This method enhances the assignment method of Rannala and Mountain (1997) by calculating appropriate graph positions for individuals for which some genetic data are missing. An individual with missing data is positioned in the distributions of genetic profiles for a population according to its estimated quantile based on its available data. The quantiles of th… Show more

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Cited by 18 publications
(21 citation statements)
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“…Due to genetic drift and founder effects for the small island populations in our study, some loci were in linkage disequilibrium. This is unlikely to pose a problem due to the robustness of assignment analyses to moderate levels of linkage disequilibrium (McMillan & Fewster, 2017).…”
Section: Discussionmentioning
confidence: 99%
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“…Due to genetic drift and founder effects for the small island populations in our study, some loci were in linkage disequilibrium. This is unlikely to pose a problem due to the robustness of assignment analyses to moderate levels of linkage disequilibrium (McMillan & Fewster, 2017).…”
Section: Discussionmentioning
confidence: 99%
“…These details include the extent of population overlap, patterns of subsetting and hybridization, and the variability of genetic fit within each cluster. Additionally, methods based on relative genetic fit do not distinguish between individuals that have a good fit to all populations and those with a bad fit to all populations; both can be portrayed similarly in plotted outputs (McMillan & Fewster, 2017).…”
Section: Discussionmentioning
confidence: 99%
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