Center around the
people and zoom to
of genetic distance. Use PCA axes X:
Y:
Z:
The PCA axes are three of the five first principal components axes. Principal component analysis (PCA) of genome-wide panels of PS markers has become a widely popular method for examining evidence of population stratification in association studies. PCA is a general statistical method for transforming a vector of covariates into orthogonal axes, known as the principal components (PCs), sorted in descending order according to their contribution to the total variation of the original covariates.
This URL can be used to share the selections you have done:
The color shows how (relative to the zoom level) close the populations are to the selected one, on the two other axes. Green is close on both axes, as the upper left dot below, pink is most distant on both axes. If you have two points being close in the graph, but pink, it means they are distant on the two other dimensions. The selected population is always black.