ReviewHeredity2011
Overview of techniques to account for confounding due to population stratification and cryptic relatedness in genomic data association analyses.
Review in Heredity, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Assessment of the functionality and usability of open-source rare variant analysis pipelines.Briefings in bioinformatics · 2025Pooled it
- A Cis-Regulatory Duplication in a Hox Hotspot Implicated in Mimetic Convergence in the Bumble Bee Bombus flavifrons.Molecular ecology · 2026Article
- Dissecting Agronomically favorable genotypes in temperate japonica rice via haplotype analysis of a Japan-MAGIC population.The Plant journal : for cell and molecular biology · 2026Article
- Analysis of Genome-Wide Association Studies.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Quantitative genomics-enabled selection for simultaneous improvement of lint yield and seed traits in cotton (Gossypium hirsutum L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Genetic Parameter and Hyper-Parameter Estimation Underlie Nitrogen Use Efficiency in Bread Wheat.International journal of molecular sciences · 2023Article
- Direct inference and control of genetic population structure from RNA sequencing data.Communications biology · 2023Article
- Transmission disequilibrium analysis of whole genome data in childhood-onset systemic lupus erythematosus.Genes and immunity · 2023Article
- Inferring feature importance with uncertainties with application to large genotype data.PLoS computational biology · 2023Article
- Genetic diversity and selective sweeps in historical and modern Canadian spring wheat cultivars using the 90K SNP array.Scientific reports · 2021Article
- Associations of age, sex, sexual abuse, and genotype with monoamine oxidase a gene methylation.Journal of neural transmission (Vienna, Austria : 1996) · 2021Article
- Penalized linear mixed models for structured genetic data.Genetic epidemiology · 2021Review
- A new method for exploring gene-gene and gene-environment interactions in GWAS with tree ensemble methods and SHAP values.BMC bioinformatics · 2021Article
- DNA methylation and gene expression integration in cardiovascular disease.Clinical epigenetics · 2021Article
- Human Genetics to Identify Therapeutic Targets for NAFLD: Challenges and Opportunities.Frontiers in endocrinology · 2021Review
- Parentage and relatedness reconstruction in Pinus sylvestris using genotyping-by-sequencing.Heredity · 2020Article
- Genome-wide association study of milk and reproductive traits in dual-purpose Xinjiang Brown cattle.BMC genomics · 2019Article
- Population Substructure Has Implications in Validating Next-Generation Cancer Genomics Studies with TCGA.International journal of molecular sciences · 2019Article
- Association between IL1 gene polymorphism and human African trypanosomiasis in populations of sleeping sickness foci of southern Cameroon.PLoS neglected tropical diseases · 2019Article
- Genome wide association study of body weight and feed efficiency traits in a commercial broiler chicken population, a re-visitation.Scientific reports · 2019Article
Corrections and comments
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Authors and funding
1 author.
Funding
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Abstract
Population-based genomic association analyses are more powerful than within-family analyses. However, population stratification (unknown or ignored origin of individuals from multiple source populations) and cryptic relatedness (unknown or ignored covariance between individuals because of their relatedness) are confounding factors in population-based genomic association analyses, which inflate the false-positive rate. As a consequence, false association signals may arise in genomic data association analyses for reasons other than true association between the tested genomic factor (marker genotype, gene or protein expression) and the study phenotype. It is therefore important to correct or account for these confounders in population-based genomic data association analyses. The common correction techniques for population stratification and cryptic relatedness problems are presented here in the phenotype-marker association analysis context, and comments on their suitability for other types of genomic association analyses (for example, phenotype-expression association) are also provided. Even though many of these techniques have originally been developed in the context of human genetics, most of them are also applicable to model organisms and breeding populations.
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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.