ArticleGenetic epidemiology2018
Two-phase designs for joint quantitative-trait-dependent and genotype-dependent sampling in post-GWAS regional sequencing.
Article in Genetic epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed.
- Two-phase sample selection strategies for design and analysis in post-genome-wide association fine-mapping studies.Statistics in medicine · 2021Article
- Estimating Additive Interaction Effect in Stratified Two-Phase Case-Control Design.Human heredity · 2019Article
- Two-phase designs for joint quantitative-trait-dependent and genotype-dependent sampling in post-GWAS regional sequencing.Genetic epidemiology · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
We evaluate two-phase designs to follow-up findings from genome-wide association study (GWAS) when the cost of regional sequencing in the entire cohort is prohibitive. We develop novel expectation-maximization-based inference under a semiparametric maximum likelihood formulation tailored for post-GWAS inference. A GWAS-SNP (where SNP is single nucleotide polymorphism) serves as a surrogate covariate in inferring association between a sequence variant and a normally distributed quantitative trait (QT). We assess test validity and quantify efficiency and power of joint QT-SNP-dependent sampling and analysis under alternative sample allocations by simulations. Joint allocation balanced on SNP genotype and extreme-QT strata yields significant power improvements compared to marginal QT- or SNP-based allocations. We illustrate the proposed method and evaluate the sensitivity of sample allocation to sampling variation using data from a sequencing study of systolic blood pressure.
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Registered trials
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