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Infinium Assay for Large-scale SNP Genotyping Applications
Published on: November 19, 2013
Comparison of genetic distance measures using human SNP genotype data
Ondrej Libiger1, Caroline M Nievergelt, Nicholas J Schork
1Scripps Translational Science Institute, Scripps Health, and Scripps Research Institute, La Jolla, CA, USA.
Human Biology
|January 14, 2010
Summary
Choosing the right genetic distance measure is crucial for human population studies. Our comparison of nine methods reveals that while some measures like Wright
Area of Science:
- Population Genetics
- Human Evolutionary Studies
- Bioinformatics
Background:
- Quantifying genetic distance between populations is essential for understanding human evolution and migration.
- Numerous genetic distance measures exist, but their suitability for real-world human populations with complex divergence histories is often unclear.
- The choice of measure can significantly impact research conclusions.
Purpose of the Study:
- To compare the performance and consistency of nine widely used genetic distance measures.
- To evaluate how different measures affect inferences about human population structure and history.
- To identify the most reliable genetic distance measures for analyzing human genomic data.
Main Methods:
- Analyzed high-density whole-genome SNP genotype data from 51 diverse human populations.
- Employed population tree construction and generalized analysis of molecular variance (AMOVA).
- Utilized concordance, consistency, and Procrustes analyses to assess measure similarity and grouping.
Main Results:
- Different genetic distance measures produced contradictory inferences regarding population relationships.
- Wright's F(ST), Latter, Reynolds, and Nei's minimum distance measures showed the highest consistency with other methods.
- Cavalli-Sforza and Edwards distance and Nei's geometric distance were the least consistent.
- Cavalli-Sforza and Edwards distance is sensitive to similar populations, while Reynolds genetic distance excels with divergent populations.
Conclusions:
- The selection of a genetic distance measure significantly influences the interpretation of human population genetic data.
- Measures like Wright's F(ST) and Nei's minimum distance offer greater consistency for general population structure analysis.
- Cavalli-Sforza and Edwards distance may have limitations in studies focusing on human migration history due to lower power.
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