ArticlePloS one2012
Rare and low frequency variant stratification in the UK population: description and impact on association tests.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Evaluating confounding in rare variant genome wide association studies.Nature communications · 2026Article
- Controlling for human population stratification in rare variant association studies.Scientific reports · 2021Article
- On the substructure controls in rare variant analysis: Principal components or variance components?Genetic epidemiology · 2018Article
- The impact of a fine-scale population stratification on rare variant association test results.PloS one · 2018Article
- The impact of rare and low-frequency genetic variants in common disease.Genome biology · 2017Review
- Quality Control for the Illumina HumanExome BeadChip.Current protocols in human genetics · 2016Article
- SORL1 rare variants: a major risk factor for familial early-onset Alzheimer's disease.Molecular psychiatry · 2016Article
- 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
- Rare variant association studies: considerations, challenges and opportunities.Genome medicine · 2015Article
- The role of rare variants in systolic blood pressure: analysis of ExomeChip data in HyperGEN African Americans.Human heredity · 2015Article
- Rare-variant association analysis: study designs and statistical tests.American journal of human genetics · 2014Review
- Article
- Adjusting for population stratification in a fine scale with principal components and sequencing data.Genetic epidemiology · 2013Article
- In search of low-frequency and rare variants affecting complex traits.Human molecular genetics · 2013Review
- Meta-analysis methods for genome-wide association studies and beyond.Nature reviews. Genetics · 2013Review
- An overview of STRUCTURE: applications, parameter settings, and supporting software.Frontiers in genetics · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Although variations in allele frequencies at common SNPs have been extensively studied in different populations, little is known about the stratification of rare variants and its impact on association tests. In this paper, we used Affymetrix 500K genotype data from the WTCCC to investigate if variants in three different frequency categories (below 1%, between 1 and 5%, above 5%) show different stratification patterns in the UK population. We found that these patterns are indeed different. The top principal component extracted from the rare variant category shows poor correlations with any principal component or combination of principal components from the low frequency or common variant categories. These results could suggest that a suitable solution to avoid false positive association due to population stratification would involve adjusting for the respective PCs when testing for variants in different allele frequency categories. However, we found this was not the case both on type 2 diabetes data and on simulated data. Indeed, adjusting rare variant association tests on PCs derived from rare variants does no better to correct for population stratification than adjusting on PCs derived from more common variants. Mixed models perform slightly better for low frequency variants than PC based adjustments but less well for the rarest variants. These results call for the need of new methodological developments specifically devoted to address rare variant stratification issues in association tests.
Indexed as
Identifiers
What OpenQuestion holds
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.