Recent advances in DNA technologies enable researchers to investigate the genetic diversity across the whole genome within a species and to gain insight into the genetic structures of populations at an unprecedented resolution. Moreover, several recently developed statistical techniques are used to infer the demographic history of populations. However, reconstruction of a complicated demographic history of a large number of interrelated populations remains difficult. In this study, I focused on (1) phylogenetic analysis, (2) principal component analysis, and (3) model-based clustering analysis with the aim of learning by computer simulations how to interpret of a large-scale genomic data set using these methods. Such empirical understandings of these practical analyses must facilitate to set an appropriate model to be tested in the estimation of demographic parameters.
CITATION STYLE
Kimura, R. (2014). Interpretations of Practical Population Genetics Analyses of Genome-Wide SNP Data on Human Demography. In Dynamics of Learning in Neanderthals and Modern Humans Volume 2 (pp. 105–117). Springer Japan. https://doi.org/10.1007/978-4-431-54553-8_12
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