ArticlePloS one2011
Accounting for population stratification in practice: a comparison of the main strategies dedicated to genome-wide association studies.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.
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Who cites it
32 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection.Nature genetics · 2018Pooled it
- Power considerations for λ inflation factor in meta-analyses of genome-wide association studies.Genetics research · 2016Pooled it
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- Global and Local Ancestry and its Importance: A Review.Current genomics · 2024Review
- Reviewing the essential roles of remote phenotyping, GWAS and explainable AI in practical marker-assisted selection for drought-tolerant winter wheat breeding.Frontiers in plant science · 2024Review
- GWAS reveals genomic associations with swine inflammation and necrosis syndrome.Mammalian genome : official journal of the International Mammalian Genome Society · 2023Article
- Limitations of principal components in quantitative genetic association models for human studies.eLife · 2023Article
- Identification of Candidate Genes Associated with Yak Body Size Using a Genome-Wide Association Study and Multiple Populations of Information.Animals : an open access journal from MDPI · 2023Article
- Analytical Approaches to Uncover Genetic Associations for Rare Outcomes: Lessons from West Nile Neuroinvasive Disease.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Relative impact of genetic ancestry and neighborhood socioeconomic status on all-cause mortality in self-identified African Americans.PloS one · 2022Article
- Is population structure in the genetic biobank era irrelevant, a challenge, or an opportunity?Human genetics · 2020Review
- Evaluating Neighborhood, Social, and Genetic Influences on Precursors of Alcohol Use Risk Behavior in African American Adolescents.International journal of environmental research and public health · 2019Article
- Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis.Nature communications · 2019Article
- A practical approach to adjusting for population stratification in genome-wide association studies: principal components and propensity scores (PCAPS).Statistical applications in genetics and molecular biology · 2018Article
- Linkage Disequilibrium and Evaluation of Genome-Wide Association Mapping Models in Tetraploid Potato.G3 (Bethesda, Md.) · 2018Article
- Correcting for Population Stratification Reduces False Positive and False Negative Results in Joint Analyses of Host and Pathogen Genomes.Frontiers in genetics · 2018Article
- Identification of growth trait related genes in a Yorkshire purebred pig population by genome-wide association studies.Asian-Australasian journal of animal sciences · 2017Article
- Construction and evaluation of a high-density SNP array for the Pacific oyster (Crassostrea gigas).PloS one · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-Wide Association Studies are powerful tools to detect genetic variants associated with diseases. Their results have, however, been questioned, in part because of the bias induced by population stratification. This is a consequence of systematic differences in allele frequencies due to the difference in sample ancestries that can lead to both false positive or false negative findings. Many strategies are available to account for stratification but their performances differ, for instance according to the type of population structure, the disease susceptibility locus minor allele frequency, the degree of sampling imbalanced, or the sample size. We focus on the type of population structure and propose a comparison of the most commonly used methods to deal with stratification that are the Genomic Control, Principal Component based methods such as implemented in Eigenstrat, adjusted Regressions and Meta-Analyses strategies. Our assessment of the methods is based on a large simulation study, involving several scenarios corresponding to many types of population structures. We focused on both false positive rate and power to determine which methods perform the best. Our analysis showed that if there is no population structure, none of the tests led to a bias nor decreased the power except for the Meta-Analyses. When the population is stratified, adjusted Logistic Regressions and Eigenstrat are the best solutions to account for stratification even though only the Logistic Regressions are able to constantly maintain correct false positive rates. This study provides more details about these methods. Their advantages and limitations in different stratification scenarios are highlighted in order to propose practical guidelines to account for population stratification in Genome-Wide Association Studies.
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