scholarly journals Leveraging population information in family-based rare variant association analyses of quantitative traits

2016 ◽  
Vol 41 (2) ◽  
pp. 98-107 ◽  
Author(s):  
Yu Jiang ◽  
Yunqi Ji ◽  
Alexander B. Sibley ◽  
Yi-Ju Li ◽  
Andrew S. Allen
Keyword(s):  
Rare Variant ◽  
Quantitative Traits ◽  
Rare Variant Association ◽  
Association Analyses ◽  
Population Information ◽  
Family Based

scholarly journals Adjusting for Common Variant Polygenic Scores Improves Yield in Rare Variant Association Analyses

2021 ◽  
Author(s):  
Sean J. Jurgens ◽  
James P. Pirruccello ◽  
Seung Hoan Choi ◽  
Valerie N. Morrill ◽  
Mark D. Chaffin ◽  
...  
Keyword(s):  
Rare Variant ◽  
Quantitative Traits ◽  
Large Scale ◽  
Common Variant ◽  
Sequencing Data ◽  
Rare Variant Association ◽  
Association Analyses ◽  
Polygenic Scores ◽  
Association Discovery ◽  
The Uk

With the emergence of large-scale sequencing data, methods for improving power in rare variant analyses (RVAT) are needed. Here, we show that adjusting for common variant polygenic scores improves the yield in gene-based RVAT across 65 quantitative traits in the UK Biobank (up to 20% increase at α=2.6x10-6), without a marked increase in false-positive rates or genomic inflation. Our results illustrate how adjusting for common variant effects can aid in rare variant association discovery.

A rare variant association test in family-based designs and non-normal quantitative traits

2015 ◽  
Vol 35 (6) ◽  
pp. 905-921 ◽  
Author(s):  
Lajmi Lakhal-Chaieb ◽  
Karim Oualkacha ◽  
Brent J. Richards ◽  
Celia M.T. Greenwood
Keyword(s):  
Rare Variant ◽  
Quantitative Traits ◽  
Association Test ◽  
Rare Variant Association ◽  
Family Based ◽  
Rare Variant Association Test

scholarly journals A Protein Domain and Family Based Approach to Rare Variant Association Analysis

PLoS ONE ◽  
2016 ◽  
Vol 11 (4) ◽  
pp. e0153803 ◽  
Author(s):  
Tom G. Richardson ◽  
Hashem A. Shihab ◽  
Manuel A. Rivas ◽  
Mark I. McCarthy ◽  
Colin Campbell ◽  
...  
Keyword(s):  
Association Analysis ◽  
Rare Variant ◽  
Protein Domain ◽  
Rare Variant Association ◽  
Family Based

scholarly journals A Robust and Powerful Set-Valued Approach to Rare Variant Association Analyses of Secondary Traits in Case-Control Sequencing Studies

Genetics ◽  
2016 ◽  
Vol 205 (3) ◽  
pp. 1049-1062 ◽  
Author(s):  
Guolian Kang ◽  
Wenjian Bi ◽  
Hang Zhang ◽  
Stanley Pounds ◽  
Cheng Cheng ◽  
...  
Keyword(s):  
Rare Variant ◽  
Case Control ◽  
Rare Variant Association ◽  
Association Analyses ◽  
Sequencing Studies ◽  
Secondary Traits

scholarly journals Rare variant association test in family-based sequencing studies

2016 ◽  
pp. bbw083 ◽  
Author(s):  
Xuefeng Wang ◽  
Zhenyu Zhang ◽  
Nathan Morris ◽  
Tianxi Cai ◽  
Seunggeun Lee ◽  
...  
Keyword(s):  
Rare Variant ◽  
Association Test ◽  
Rare Variant Association ◽  
Sequencing Studies ◽  
Family Based ◽  
Rare Variant Association Test

scholarly journals A permutation method for detecting trend correlations in rare variant association studies

2019 ◽  
Vol 101 ◽  
Author(s):  
Lifeng Liu ◽  
Pengfei Wang ◽  
Jingbo Meng ◽  
Lili Chen ◽  
Wensheng Zhu ◽  
...  
Keyword(s):  
Rare Variant ◽  
Type I Error ◽  
Rare Variants ◽  
Association Studies ◽  
Complex Diseases ◽  
Type I ◽  
Phenotypic Variance ◽  
Rare Variant Association ◽  
Significance Level ◽  
Association Analyses

Abstract In recent years, there has been an increasing interest in detecting disease-related rare variants in sequencing studies. Numerous studies have shown that common variants can only explain a small proportion of the phenotypic variance for complex diseases. More and more evidence suggests that some of this missing heritability can be explained by rare variants. Considering the importance of rare variants, researchers have proposed a considerable number of methods for identifying the rare variants associated with complex diseases. Extensive research has been carried out on testing the association between rare variants and dichotomous, continuous or ordinal traits. So far, however, there has been little discussion about the case in which both genotypes and phenotypes are ordinal variables. This paper introduces a method based on the γ-statistic, called OV-RV, for examining disease-related rare variants when both genotypes and phenotypes are ordinal. At present, little is known about the asymptotic distribution of the γ-statistic when conducting association analyses for rare variants. One advantage of OV-RV is that it provides a robust estimation of the distribution of the γ-statistic by employing the permutation approach proposed by Fisher. We also perform extensive simulations to investigate the numerical performance of OV-RV under various model settings. The simulation results reveal that OV-RV is valid and efficient; namely, it controls the type I error approximately at the pre-specified significance level and achieves greater power at the same significance level. We also apply OV-RV for rare variant association studies of diastolic blood pressure.

scholarly journals Family-Based Rare Variant Association Analysis: A Fast and Efficient Method of Multivariate Phenotype Association Analysis

2016 ◽  
Vol 40 (6) ◽  
pp. 502-511 ◽  
Author(s):  
Longfei Wang ◽  
Sungyoung Lee ◽  
Jungsoo Gim ◽  
Dandi Qiao ◽  
Michael Cho ◽  
...  
Keyword(s):  
Association Analysis ◽  
Rare Variant ◽  
Efficient Method ◽  
Rare Variant Association ◽  
Family Based

scholarly journals FARVAT: a family-based rare variant association test

2014 ◽  
Vol 30 (22) ◽  
pp. 3197-3205 ◽  
Author(s):  
Sungkyoung Choi ◽  
Sungyoung Lee ◽  
Sven Cichon ◽  
Markus M. Nöthen ◽  
Christoph Lange ◽  
...  
Keyword(s):  
Rare Variant ◽  
Association Test ◽  
Rare Variant Association ◽  
Family Based ◽  
Rare Variant Association Test
Sign in / Sign up

Export Citation Format

Share Document