A Genealogical Interpretation of Principal Components Analysis
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Abstract
Principal components analysis, PCA, is a statistical method commonly used in population genetics to identify structure in the distribution of genetic variation across geographical location and ethnic background. However, while the method is often used to inform about historical demographic processes, little is known about the relationship between fundamental demographic parameters and the projection of samples onto the primary axes. Here I show that for SNP data the projection of samples onto the principal components can be obtained directly from considering the average coalescent times between pairs of haploid genomes. The result provides a framework for interpreting PCA projections in terms of underlying…
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1Topics & keywords
Topics
Keywords
- Principal component analysis
- Biology
- Coalescent theory
- Inference
- Population genetics
- Population
- Evolutionary biology
- Projection (relational algebra)
UN Sustainable Development Goals
- Reduced inequalities
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