ArticleGenetic epidemiology2020
Sequencing and imputation in GWAS: Cost-effective strategies to increase power and genomic coverage across diverse populations.
Article in Genetic epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- Explainable convolutional neural network model provides an alternative genome-wide association perspective on mutations in SARS-CoV-2.Scientific reports · 2026Article
- Skim-sequencing for genomic selection in wheat: a comparison of marker platforms.The plant genome · 2026Article
- Advances in haplotype phasing and genotype imputation.Nature reviews. Genetics · 2026Review
- Sequence-based genome-wide association study reveals genetic and metabolic mechanisms underlying feed efficiency-related traits in beef cattle.Journal of animal science and biotechnology · 2026Article
- Comprehensive genetic screening of the South African Parkinson's disease study collection using the NeuroBooster array.Clinical parkinsonism & related disorders · 2026Article
- Removing array-specific batch effects in GWAS mega-analyses by applying a two-step imputation workflow.Bioinformatics advances · 2026Article
- Alzheimer's disease: genetic background in the era of next-generation sequencing technologies.Brain communications · 2026Review
- Comprehensive genetic screening of the South African Parkinson's disease study collection using the NeuroBooster array.medRxiv : the preprint server for health sciences · 2025Article
- Imputation of ancient canid genomes reveals inbreeding history over the past 10,000 years.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- GDBIG: A Pioneering Birth Cohort Genomic Platform Facilitating Intergenerational Genetic Research.Genomics, proteomics & bioinformatics · 2025Article
- Formal Statistical Replication Analysis in Lung Cancer Genome-Wide Association Studies.medRxiv : the preprint server for health sciences · 2025Article
- Establishing Best Practices for Clinical GWAS: Tackling Imputation and Data Quality Challenges.International journal of molecular sciences · 2025Review
- Enhancing Genomic Prediction Accuracy of Reproduction Traits in Rongchang Pigs Through Machine Learning.Animals : an open access journal from MDPI · 2025Article
- Operationalizing language-based population stratification for widening access to precision genomics in Africa.Frontiers in public health · 2025Article
- Phenome-wide association study in 25,639 pregnant Chinese women reveals loci associated with maternal comorbidities and child health.Cell genomics · 2024Article
- Comparing the effect of imputation reference panel composition in four distinct Latin American cohorts.bioRxiv : the preprint server for biology · 2024Article
- A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome.NPJ genomic medicine · 2024Article
- How local reference panels improve imputation in French populations.Scientific reports · 2024Article
- Evaluation of imputation performance of multiple reference panels in a Pakistani population.medRxiv : the preprint server for health sciences · 2023Article
- Linking Prenatal Environmental Exposures to Lifetime Health with Epigenome-Wide Association Studies: State-of-the-Science Review and Future Recommendations.Environmental health perspectives · 2023Review
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
A key aim for current genome-wide association studies (GWAS) is to interrogate the full spectrum of genetic variation underlying human traits, including rare variants, across populations. Deep whole-genome sequencing is the gold standard to fully capture genetic variation, but remains prohibitively expensive for large sample sizes. Array genotyping interrogates a sparser set of variants, which can be used as a scaffold for genotype imputation to capture a wider set of variants. However, imputation quality depends crucially on reference panel size and genetic distance from the target population. Here, we consider sequencing a subset of GWAS participants and imputing the rest using a reference panel that includes both sequenced GWAS participants and an external reference panel. We investigate how imputation quality and GWAS power are affected by the number of participants sequenced for admixed populations (African and Latino Americans) and European population isolates (Sardinians and Finns), and identify powerful, cost-effective GWAS designs given current sequencing and array costs. For populations that are well-represented in existing reference panels, we find that array genotyping alone is cost-effective and well-powered to detect common- and rare-variant associations. For poorly represented populations, sequencing a subset of participants is often most cost-effective, and can substantially increase imputation quality and GWAS power.
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