ArticleBMC proceedings2011
Population structure analysis using rare and common functional variants.
Article in BMC proceedings, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00930280 (Genetic and Environmental Risk Factors for Hemorrhagic Stroke), which is not on this map. Cited by 22 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Genetic and Environmental Risk Factors for Hemorrhagic Stroke
Who cites it
22 citing papers in PubMed.
- A spectral component approach leveraging identity-by-descent graphs to address recent population structure in genomic analysis.Genome research · 2026Article
- 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
- A comparison between similarity matrices for principal component analysis to assess population stratification in sequenced genetic data sets.Briefings in bioinformatics · 2023Article
- Taking population stratification into account by local permutations in rare-variant association studies on small samples.Genetic epidemiology · 2021Article
- Controlling for human population stratification in rare variant association studies.Scientific reports · 2021Article
- MI-MAAP: marker informativeness for multi-ancestry admixed populations.BMC bioinformatics · 2020Article
- Article
- LEI: A Novel Allele Frequency-Based Feature Selection Method for Multi-ancestry Admixed Populations.Scientific reports · 2019Article
- On the substructure controls in rare variant analysis: Principal components or variance components?Genetic epidemiology · 2018Article
- Utilizing the Jaccard index to reveal population stratification in sequencing data: a simulation study and an application to the 1000 Genomes Project.Bioinformatics (Oxford, England) · 2016Article
- Population Genomics and the Statistical Values of Race: An Interdisciplinary Perspective on the Biological Classification of Human Populations and Implications for Clinical Genetic Epidemiological Research.Frontiers in genetics · 2016Review
- Rare variation facilitates inferences of fine-scale population structure in humans.Molecular biology and evolution · 2015Article
- The effect of rare variants on inflation of the test statistics in case-control analyses.BMC bioinformatics · 2015Article
- Article
- Mapping asthma-associated variants in admixed populations.Frontiers in genetics · 2015Review
- Adjusting for population stratification and relatedness with sequencing data.BMC proceedings · 2014Article
- Adjusting for population stratification in a fine scale with principal components and sequencing data.Genetic epidemiology · 2013Article
- Adjustment for population stratification via principal components in association analysis of rare variants.Genetic epidemiology · 2013Article
- AncestrySNPminer: a bioinformatics tool to retrieve and develop ancestry informative SNP panels.Genomics · 2012Article
- Comparison of measures of marker informativeness for ancestry and admixture mapping.BMC genomics · 2011Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Next-generation sequencing technologies now make it possible to genotype and measure hundreds of thousands of rare genetic variations in individuals across the genome. Characterization of high-density genetic variation facilitates control of population genetic structure on a finer scale before large-scale genotyping in disease genetics studies. Population structure is a well-known, prevalent, and important factor in common variant genetic studies, but its relevance in rare variants is unclear. We perform an extensive population structure analysis using common and rare functional variants from the Genetic Analysis Workshop 17 mini-exome sequence. The analysis based on common functional variants required 388 principal components to account for 90% of the variation in population structure. However, an analysis based on rare variants required 532 significant principal components to account for similar levels of variation. Using rare variants, we detected fine-scale substructure beyond the population structure identified using common functional variants. Our results show that the level of population structure embedded in rare variant data is different from the level embedded in common variant data and that correcting for population structure is only as good as the level one wishes to correct.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.