ArticleGenetic epidemiology2014
A rare variant association test based on combinations of single-variant tests.
Article in Genetic epidemiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Identification of genetic variants associated with tacrolimus metabolism in kidney transplant recipients by extreme phenotype sampling and next generation sequencing.The pharmacogenomics journal · 2019Observational
- Testing an optimally weighted combination of common and/or rare variants with multiple traits.PloS one · 2018Article
- Detecting association of rare and common variants based on cross-validation prediction error.Genetic epidemiology · 2017Article
- Joint Analysis of Multiple Traits in Rare Variant Association Studies.Annals of human genetics · 2016Article
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Authors and funding
2 authors.
Funding
Abstract
Next generation sequencing technologies make direct testing rare variant associations possible. However, the development of powerful statistical methods for rare variant association studies is still underway. Most of existing methods are burden and quadratic tests. Recent studies show that the performance of each of burden and quadratic tests depends strongly upon the underlying assumption and no test demonstrates consistently acceptable power. Thus, combined tests by combining information from the burden and quadratic tests have been proposed recently. However, results from recent studies (including this study) show that there exist tests that can outperform both burden and quadratic tests. In this article, we propose three classes of tests that include tests outperforming both burden and quadratic tests. Then, we propose the optimal combination of single-variant tests (OCST) by combining information from tests of the three classes. We use extensive simulation studies to compare the performance of OCST with that of burden, quadratic and optimal single-variant tests. Our results show that OCST either is the most powerful test or has similar power with the most powerful test. We also compare the performance of OCST with that of the two existing combined tests. Our results show that OCST has better power than the two combined tests.
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Registered trials
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