Test for rare variants by environment interactions in sequencing association studies.

@article{Lin2016TestFR,
  title={Test for rare variants by environment interactions in sequencing association studies.},
  author={Xinyi Lin and Seunggeun Lee and Michael C. Wu and Chaolong Wang and Han Chen and Zilin Li and Xihong Lin},
  journal={Biometrics},
  year={2016},
  volume={72 1},
  pages={
          156-64
        }
}
We consider in this article testing rare variants by environment interactions in sequencing association studies. Current methods for studying the association of rare variants with traits cannot be readily applied for testing for rare variants by environment interactions, as these methods do not effectively control for the main effects of rare variants, leading to unstable results and/or inflated Type 1 error rates. We will first analytically study the bias of the use of conventional burden… Expand
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References

SHOWING 1-10 OF 26 REFERENCES
Optimal tests for rare variant effects in sequencing association studies.
TLDR
This paper proposes a class of tests that include burden tests and SKAT as special cases, and derives an optimal test within this class that maximizes power, and shows that this optimal test outperforms burden testsand SKAT in a wide range of scenarios. Expand
Sequence kernel association tests for the combined effect of rare and common variants.
TLDR
Several sequence kernel association tests are introduced to evaluate the cumulative effect of rare and common variants and can achieve substantial increases in power compared with the most commonly used tests, including the burden and variance-component tests. Expand
Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data.
TLDR
It is shown that the collapsing method, which involves collapsing genotypes across variants and applying a univariate test, is powerful for analyzing rare variants, whereas multivariate analysis is robust against inclusion of noncausal variants. Expand
A Unified Mixed‐Effects Model for Rare‐Variant Association in Sequencing Studies
TLDR
This paper derives a set of two score statistics, testing the group effect by variant characteristics and the heterogeneity effect, and makes a novel modification to these score statistics so that they are independent under the null hypothesis and their asymptotic distributions can be derived. Expand
Rare-variant association testing for sequencing data with the sequence kernel association test.
TLDR
The sequence kernel association test (SKAT) is proposed, a supervised, flexible, computationally efficient regression method to test for association between genetic variants (common and rare) in a region and a continuous or dichotomous trait while easily adjusting for covariates. Expand
A general framework for detecting disease associations with rare variants in sequencing studies.
TLDR
This work provides a general framework for association testing with rare variants by combining mutation information across multiple variant sites within a gene and relating the enriched genetic information to disease phenotypes through appropriate regression models. Expand
Rare-variant association analysis: study designs and statistical tests.
TLDR
An overview of statistical issues in rare-variant association studies with a focus on study designs and statistical tests is provided and various gene- or region-based association tests are compared in terms of their assumptions and performance. Expand
Testing for an Unusual Distribution of Rare Variants
TLDR
This work proposes here the C-alpha test statistic as a novel approach for testing for the presence of this mixture of effects across a set of rare variants, and demonstrates good power relative to existing methods that assess the burden of rare variant in individuals. Expand
Comparison of statistical tests for disease association with rare variants
TLDR
A comprehensive comparison of various statistical tests using simulated data is provided, considering both independent and correlated rare mutations, and representative tests for both CVs and RVs. Expand
A Groupwise Association Test for Rare Mutations Using a Weighted Sum Statistic
TLDR
It is demonstrated that resequencing studies can identify important genetic associations, provided that specialised analysis methods, such as the weighted-sum method, are used. Expand
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