ArticleProceedings of the National Academy of Sciences of the United States of America2021
False discovery rate control in genome-wide association studies with population structure.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.
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Who cites it
47 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- GhostKnockoff inference empowers identification of putative causal variants in genome-wide association studies.Nature communications · 2022Pooled it
- Robust Inference With Ghostknockoffs in Genome-Wide Association Studies With Sample Relatedness.Genetic epidemiology · 2026Article
- CIT-Lasso: a scalable approach beyond guilty by association for identifying causal variants from genome-wide summary statistics.Genome biology · 2026Article
- Statistical knockoffs improve biomarker discovery from transcriptomic data.Briefings in bioinformatics · 2026Article
- Establishing standards for genome wide association studies in eusocial insects through a case study in honey bees.Scientific reports · 2026Article
- Genome-wide association study bridging genomics-phenomics gap in natural plant populations.Journal of applied genetics · 2026Review
- Article
- Integrating genome size variation, ISSR-derived genetic structure, and phenotypical traits from the Southern Peruvian Andean maize (Frontiers in plant science · 2026Article
- Phenotype-genotype association for the identification of resistance to stem borers (Frontiers in plant science · 2026Article
- Semiparametric efficient estimation of small genetic effects in large-scale population cohorts.Biostatistics (Oxford, England) · 2025Article
- Dissecting the genetic architecture of pre-harvest sprouting tolerance in Indian dwarf wheat (Triticum sphaerococcum) by multi-locus association analysis.Scientific reports · 2025Article
- Benchmarking interpretability of deep learning for predictive genomics: Recall, precision, and variability of feature attribution.PLoS computational biology · 2025Article
- Knockoff procedure improves susceptibility gene identifications in conditional transcriptome-wide association studies.American journal of human genetics · 2025Article
- It's a wrap: deriving distinct discoveries with FDR control after a GWAS pipeline.bioRxiv : the preprint server for biology · 2025Article
- DrFARM: identification of pleiotropic genetic variants in genome-wide association studies.Nature communications · 2025Article
- Identifying a Genetic Link Between Lung Function and Psoriasis.Annals of human genetics · 2025Article
- Catch me if you can: signal localization with knockoffJournal of the Royal Statistical Society. Series B, Statistical methodology · 2025Article
- From Serendipity to Precision: Integrating AI, Multi-Omics, and Human-Specific Models for Personalized Neuropsychiatric Care.Biomedicines · 2025Review
- Investigating Overlapping Genetic Factors and Novel Causal Genes in Autoimmune Diseases: A Transcriptome-Wide Association and Multiomics Study.International journal of genomics · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
We present a comprehensive statistical framework to analyze data from genome-wide association studies of polygenic traits, producing interpretable findings while controlling the false discovery rate. In contrast with standard approaches, our method can leverage sophisticated multivariate algorithms but makes no parametric assumptions about the unknown relation between genotypes and phenotype. Instead, we recognize that genotypes can be considered as a random sample from an appropriate model, encapsulating our knowledge of genetic inheritance and human populations. This allows the generation of imperfect copies (knockoffs) of these variables that serve as ideal negative controls, correcting for linkage disequilibrium and accounting for unknown population structure, which may be due to diverse ancestries or familial relatedness. The validity and effectiveness of our method are demonstrated by extensive simulations and by applications to the UK Biobank data. These analyses confirm our method is powerful relative to state-of-the-art alternatives, while comparisons with other studies validate most of our discoveries. Finally, fast software is made available for researchers to analyze Biobank-scale datasets.
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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.