主成分分析
生物
人口
群体遗传学
进化生物学
变化(天文学)
遗传变异
空间变异性
遗传学
统计
人口学
数学
天体物理学
基因
物理
社会学
作者
John Novembre,Matthew Stephens
出处
期刊:Nature Genetics
[Springer Nature]
日期:2008-04-20
卷期号:40 (5): 646-649
被引量:601
摘要
Nearly 30 years ago, Cavalli-Sforza et al. pioneered the use of principal component analysis (PCA) in population genetics and used PCA to produce maps summarizing human genetic variation across continental regions. They interpreted gradient and wave patterns in these maps as signatures of specific migration events. These interpretations have been controversial, but influential, and the use of PCA has become widespread in analysis of population genetics data. However, the behavior of PCA for genetic data showing continuous spatial variation, such as might exist within human continental groups, has been less well characterized. Here, we find that gradients and waves observed in Cavalli-Sforza et al.'s maps resemble sinusoidal mathematical artifacts that arise generally when PCA is applied to spatial data, implying that the patterns do not necessarily reflect specific migration events. Our findings aid interpretation of PCA results and suggest how PCA can help correct for continuous population structure in association studies.
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