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Using population genetic models, the admixture fraction can also be estimated from the magnitude of this difference.
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Our method uses an HDP to model the admixture of an unknown number of ancestral populations present in individual genomes in a given dataset.
Then, mapped markers were used to run the linkage model and the admixture model, to compare the results obtained using different models and markers and to test the robustness of the results.
We demonstrate this surprising result through an extension of a mechanistic model for the admixture history of a hybrid population.
For the ancestry model, we chose the admixture model with ALPHA being inferred from the data in combination with correlated allele frequencies.
We chose the admixture model as ancestry model and the correlated frequency model as allele frequency model [Falush et al., 2003].
We used the admixture model with the F model of correlated allele frequencies across clusters for the STRUCTURE analysis.
We adopted the admixture model, the correlated allele frequencies model, and we used sampling locations as prior information to assist the clustering (LOCPRIOR option).
This type of model selection problem is akin to estimating K in the admixture model of STRUCTURE/admixture (Falush et al. 2003; Alexander et al. 2009) and is typically challenging.
The admixture model and the correlated allele frequencies model were used.
The admixture model and the allele frequencies correlated model were used to estimate the number of probable clusters (K value).
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