A Genealogical Interpretation of Principal Components Analysis

摘要: Principal components analysis, PCA, is a statistical method commonly used in population genetics to identify structure the distribution of genetic variation across geographical location and ethnic background. However, while often inform about historical demographic processes, little known relationship between fundamental parameters projection samples onto primary axes. Here I show that for SNP data principal can be obtained directly from considering average coalescent times pairs haploid genomes. The result provides framework interpreting PCA projections terms underlying including migration, isolation, admixture. also demonstrate link Wright's f(st) ascertainment has largely simple predictable effect on samples. Using examples human genetics, discuss application these results empirical implications inference.