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We may also use SibJoin to explore populations with extreme numbers of individuals.
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To further explore population structure, a neighbor-joining dendrogram was constructed using the program POPULATIONS v1.2.28 (available at bioinformatics.org/∽tryphon/populations), based on the Cavalli-Sforza and Edwards chord distance, DCE (Cavalli-Sforza and Edwards 1967).
In addition, we explore population structuring within and between hosts by comparing the estimates of genetic diversity obtained assuming a 'component population' approach with those using an 'infrapopulation' approach.
To explore population trajectories, we combined shearwater survival, fertility, recruitment and breeding probabilities into a stage demographic model [47].
Classical Multi Dimension Scaling (MDS) was used to explore population substructure and to verify the genetic homogeneity of the sample set prior to analysis.
Spatial multivariate analyses [64] were used to explore population structure without having to make assumptions about an underlying genetic model (sPCA) with the adegenet package [65] in R 2.8.1 (R Development Core Team 2009).
Finally, we use simulations to explore population-level disease dynamics.
HTS has made it possible to explore population genetic variation among human populations (1000 Genomes Project, Altshuler et al., 2010).
We will explore population structure in these two groups as the basis for future admixture mapping studies.
In this study we formulate a theoretical model to explore population dynamics of HIV/AIDS-malaria coinfections.
To thoroughly explore population structure, multiple independent markers are required and intrapopulation variation needs to be evaluated [ 51].
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