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We next applied a model-based clustering method to infer genetic structure and define the most adequate number of clusters in the whole dataset using the software STRUCTURE v. 2.3.3 (Pritchard et al. 2000).
Detecting the number of clusters of individuals using the software STRUCTURE, a simulation study.
Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.
Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software Structure: a simulation study.
Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software structure: a simulation study.
Evanno, G. et al. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.
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We also used the software STRUCTURE to estimate Fst values for the genetic clusters established for each group, the mean value of 20 runs was calculated.
To detect population stratification that may lead to spurious association results, we used the software Structure 2.2 (http://pritch.bsd.uchicago.edu/software.html) and EIGENSTRAT software (http://genepath.med.harvard.edu/~reich/EIGENSTRAT.htm) to investigate the potential substructure/stratification of our sample.
To further investigate population genetic structure, we used the software STRUCTURE v2.3.2 (Pritchard et al. 2000).
we used the software STRUCTURE [ 17] to infer the population structure.
Finally, we used the software "Structure" 2.2 [ 32] to infer the optimal number of genetic clusters in our dataset.
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