ArticleProceedings of the National Academy of Sciences of the United States of America2013
Quantitative trait analysis in sequencing studies under trait-dependent sampling.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.
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Who cites it
39 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs.American journal of human genetics · 2015Pooled it
- Meta-analysis of gene-level associations for rare variants based on single-variant statistics.American journal of human genetics · 2013Pooled it
- A novel association test for multiple secondary phenotypes from a case-control GWAS.Genetic epidemiology · 2017Trial
- Overcoming data challenges through enriched validation and targeted sampling to measure whole-person health in electronic health records.Journal of biomedical informatics · 2025Article
- A SEMIPARAMETRIC METHOD FOR RISK PREDICTION USING INTEGRATED ELECTRONIC HEALTH RECORD DATA.The annals of applied statistics · 2024Article
- Article
- Mediation analysis of multiple mediators with incomplete omics data.Genetic epidemiology · 2023Article
- Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants.HGG advances · 2023Article
- Comparison of mixed model based approaches for correcting for population substructure with application to extreme phenotype sampling.BMC genomics · 2022Article
- Two-phase sample selection strategies for design and analysis in post-genome-wide association fine-mapping studies.Statistics in medicine · 2021Article
- Two-Phase Sampling Designs for Data Validation in Settings with Covariate Measurement Error and Continuous Outcome.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2021Article
- Two-wave two-phase outcome-dependent sampling designs, with applications to longitudinal binary data.Statistics in medicine · 2021Article
- Efficient semiparametric inference for two-phase studies with outcome and covariate measurement errors.Statistics in medicine · 2021Article
- Errors in multiple variables in human immunodeficiency virus (HIV) cohort and electronic health record data: statistical challenges and opportunities.Statistical communications in infectious diseases · 2020Article
- PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection.Genome biology · 2020Article
- Multi-trait analysis of rare-variant association summary statistics using MTAR.Nature communications · 2020Article
- STEPS: an efficient prospective likelihood approach to genetic association analyses of secondary traits in extreme phenotype sequencing.Biostatistics (Oxford, England) · 2020Article
- Optimal Designs of Two-Phase Studies.Journal of the American Statistical Association · 2020Article
- Robust Score Tests With Missing Data in Genomics Studies.Journal of the American Statistical Association · 2019Article
- A Cautionary Note on the Effects of Population Stratification Under an Extreme Phenotype Sampling Design.Frontiers in genetics · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
It is not economically feasible to sequence all study subjects in a large cohort. A cost-effective strategy is to sequence only the subjects with the extreme values of a quantitative trait. In the National Heart, Lung, and Blood Institute Exome Sequencing Project, subjects with the highest or lowest values of body mass index, LDL, or blood pressure were selected for whole-exome sequencing. Failure to account for such trait-dependent sampling can cause severe inflation of type I error and substantial loss of power in quantitative trait analysis, especially when combining results from multiple studies with different selection criteria. We present valid and efficient statistical methods for association analysis of sequencing data under trait-dependent sampling. We pay special attention to gene-based analysis of rare variants. Our methods can be used to perform quantitative trait analysis not only for the trait that is used to select subjects for sequencing but for any other traits that are measured. For a particular trait of interest, our approach properly combines the association results from all studies with measurements of that trait. This meta-analysis is substantially more powerful than the analysis of any single study. By contrast, meta-analysis of standard linear regression results (ignoring trait-dependent sampling) can be less powerful than the analysis of a single study. The advantages of the proposed methods are demonstrated through simulation studies and the National Heart, Lung, and Blood Institute Exome Sequencing Project data. The methods are applicable to other types of genetic association studies and nongenetic studies.
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