ArticleBMC genetics2020
On rare variants in principal component analysis of population stratification.
Article in BMC genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Genome-wide analysis of inbreeding patterns and candidate genes for adaptation in indigenous chickens of Botswana.Poultry science · 2026Article
- Evaluating confounding in rare variant genome wide association studies.Nature communications · 2026Article
- A spectral component approach leveraging identity-by-descent graphs to address recent population structure in genomic analysis.Genome research · 2026Article
- KANN: estimation of genetic ancestry profiles by nearest neighbor regression.Nucleic acids research · 2026Article
- Whole-genome sequencing analysis of anthropometric traits in 672,976 individuals reveals convergence between rare and common genetic associations.Nature communications · 2026Article
- BeyondFrontiers in genetics · 2026Review
- Confirmation of BIK and SAMHD1 as Prostate Cancer Susceptibility Genes.The Prostate · 2025Article
- SPC: a SPectral Component approach leveraging Identity-by-Descent graphs to address recent population structure in genomic analysis.medRxiv : the preprint server for health sciences · 2025Article
- Genetic Basis of Low-Salinity Tolerance in the Pacific Oyster (Crassostrea gigas) as Revealed by Estimation of Genetic Parameters and Genome-Wide Association Study.Marine biotechnology (New York, N.Y.) · 2025Article
- Comparison of genomic prediction accuracy using different models for egg production traits in Taiwan country chicken.Poultry science · 2024Article
- Genomic Selection for Weaning Weight in Alpine Merino Sheep Based on GWAS Prior Marker Information.Animals : an open access journal from MDPI · 2024Article
- Genome-Wide Association Analysis Identifies theAnimals : an open access journal from MDPI · 2023Article
- Ultra-Rare Variants Identify Biological Pathways and Candidate Genes in the Pathobiology of Non-Syndromic Cleft Palate Only.Biomolecules · 2023Article
- A comparison between similarity matrices for principal component analysis to assess population stratification in sequenced genetic data sets.Briefings in bioinformatics · 2023Article
- First genome-wide data from Italian European beech (Fagus sylvatica L.): Strong and ancient differentiation between Alps and Apennines.PloS one · 2023Article
- Analysis of Common SNPs across Continents Reveals Major Genomic Differences between Human Populations.Genes · 2022Article
- Importance of Including Non-European Populations in Large Human Genetic Studies to Enhance Precision Medicine.Annual review of biomedical data science · 2022Review
- Apportioning archaic variants among modern populations.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
- A deep learning framework for characterization of genotype data.G3 (Bethesda, Md.) · 2022Article
- Recent advances and challenges of rare variant association analysis in the biobank sequencing era.Frontiers in genetics · 2022Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPopulation stratification is a known confounder of genome-wide association studies, as it can lead to false positive results. Principal component analysis (PCA) method is widely applied in the analysis of population structure with common variants. However, it is still unclear about the analysis performance when rare variants are used.
resultsWe derive a mathematical expectation of the genetic relationship matrix. Variance and covariance elements of the expected matrix depend explicitly on allele frequencies of the genetic markers used in the PCA analysis. We show that inter-population variance is solely contained in K principal components (PCs) and mostly in the largest K-1 PCs, where K is the number of populations in the samples. We propose F
conclusionsThe PCA of population stratification performs worse with rare variants than with common ones. It is necessary to restrict the selection to only the common variants when analyzing population stratification with sequencing data.
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