The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
A Genealogical Interpretation of Principal Components Analysis
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PCA clustering is sensitive to the sample size of different ancestries and also to their amount of genetic drift, which exaggerates principal component distances.
“It is notable that PCA clustering is sensitive to the sample size of different ancestries and also to their amount of genetic drift, which exaggerates principal component distances 207,208,211,212 .”
From Ancient DNA analysis (2021) · cites this paper as [208]
The Results section, “Uneven sampling has a strong influence on PCA projections” (page unavailable), says unequal population sample sizes distort PCA space. The two-population example links PC distance to population divergence, but the retrieved passages do not establish the more specific claim that differing amounts of genetic drift exaggerate those distances. (LLM, conf=0.83)
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Cites
Principal components analysis corrects for stratification in genome-wide association studies
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006) · Nature Genetics · doi:10.1038/ng1847 · Cited by 10,248
Population Structure and Eigenanalysis
Patterson, N., Price, A. L., & Reich, D. (2006) · PLoS Genetics · doi:10.1371/journal.pgen.0020190 · Cited by 5,280
Genes mirror geography within Europe
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Y genetic data support the Neolithic demic diffusion model
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The effect of the Neolithic expansion on European molecular diversity
Currat, M., & Excoffier, L. (2005) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2004.2999 · Cited by 210
Flagged first, then by citations
Research works printed but not linked: 12
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- J Baik, 2005, Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices., Ann Probability, 33, 1643, 10.1214/009117905000000233 · DOI
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- S Schaffner, 2005, Calibrating a coalescent simulation of human genome sequence variation., Genome Res, 15, 1576, 10.1101/gr.3709305 · DOI · Paper page
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“Principal Coordinate (PCO) analysis has been recognized as a simple and straight-forward method to group or separate samples in a dataset, and has been used in disease-association studies [22,23].”
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Genomic Insights into the Population History and Adaptive Traits of Latin American Criollo Cattle
Ward, J. A., Ng'ang'a, S. I., Randhawa, I. A. S., McHugo, G. P., O'Grady, J. F., Flórez, J. M., Browne, J. A., Pérez O’Brien, A. M., Landaeta-Hernández, A. J., Garcia, J. F., et al. (2024) · Royal Society Open Science · doi:10.1098/rsos.231388 · Cited by 17
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Metadata
- Authors
- McVean, G.
- Venue
- PLoS Genetics
- Publisher
- Public Library of Science (PLoS)
- Published
- 2009-10-16
- Volume
- 5
- Issue
- 10
- Pages
- e1000686
- ISSN
- 1553-7404
- PMC
- PMC2757795
- Cited by
- 568
- References
- 5
- Language
- en
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