Literature DB >> 28864915

A gene-based test of association through an orthogonal decomposition of genotype scores.

Zhongxue Chen1, Kai Wang2.   

Abstract

The burden test and the sequence kernel association test (SKAT) are two popular methods for detecting association with rare variants. Treated as two different sources of association information, they are adaptively combined to form an optimal SKAT (SKAT-O) method for optimal power. We show that the burden test is part of rather than independent of the SKAT. We introduce a new test statistic that is the sum of the burden statistic and a statistic asymptotically independent of the burden statistic. The performance of this new test statistic is demonstrated through extensive simulation studies and applications to a Genetic Analysis Workshop 17 data set and the Ocular Hypertension Treatment Study data.

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Mesh:

Year:  2017        PMID: 28864915     DOI: 10.1007/s00439-017-1839-y

Source DB:  PubMed          Journal:  Hum Genet        ISSN: 0340-6717            Impact factor:   4.132


  24 in total

1.  A new association test based on Chi-square partition for case-control GWA studies.

Authors:  Zhongxue Chen
Journal:  Genet Epidemiol       Date:  2011-08-26       Impact factor: 2.135

2.  Optimal tests for rare variant effects in sequencing association studies.

Authors:  Seunggeun Lee; Michael C Wu; Xihong Lin
Journal:  Biostatistics       Date:  2012-06-14       Impact factor: 5.899

3.  Bayesian analysis of rare variants in genetic association studies.

Authors:  Nengjun Yi; Degui Zhi
Journal:  Genet Epidemiol       Date:  2011-01       Impact factor: 2.135

4.  Is the weighted z-test the best method for combining probabilities from independent tests?

Authors:  Z Chen
Journal:  J Evol Biol       Date:  2011-01-24       Impact factor: 2.411

5.  A general framework for detecting disease associations with rare variants in sequencing studies.

Authors:  Dan-Yu Lin; Zheng-Zheng Tang
Journal:  Am J Hum Genet       Date:  2011-09-01       Impact factor: 11.025

6.  A powerful and adaptive association test for rare variants.

Authors:  Wei Pan; Junghi Kim; Yiwei Zhang; Xiaotong Shen; Peng Wei
Journal:  Genetics       Date:  2014-05-15       Impact factor: 4.562

7.  Detecting associated single-nucleotide polymorphisms on the X chromosome in case control genome-wide association studies.

Authors:  Zhongxue Chen; Hon Keung Tony Ng; Jing Li; Qingzhong Liu; Hanwen Huang
Journal:  Stat Methods Med Res       Date:  2014-09-24       Impact factor: 3.021

8.  Comparison of multiple hazard rate functions.

Authors:  Zhongxue Chen; Hanwen Huang; Peihua Qiu
Journal:  Biometrics       Date:  2015-09-22       Impact factor: 2.571

9.  Genetic association test based on principal component analysis.

Authors:  Zhongxue Chen; Shizhong Han; Kai Wang
Journal:  Stat Appl Genet Mol Biol       Date:  2017-07-26

10.  Design and analysis of multiple diseases genome-wide association studies without controls.

Authors:  Zhongxue Chen; Hanwen Huang; Hon Keung Tony Ng
Journal:  Gene       Date:  2012-08-23       Impact factor: 3.688

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  4 in total

1.  A Powerful Variant-Set Association Test Based on Chi-Square Distribution.

Authors:  Zhongxue Chen; Tong Lin; Kai Wang
Journal:  Genetics       Date:  2017-09-14       Impact factor: 4.562

2.  Integration of methylation QTL and enhancer-target gene maps with schizophrenia GWAS summary results identifies novel genes.

Authors:  Chong Wu; Wei Pan
Journal:  Bioinformatics       Date:  2019-10-01       Impact factor: 6.937

3.  CMAX3: A Robust Statistical Test for Genetic Association Accounting for Covariates.

Authors:  Zhongxue Chen; Yong Zang
Journal:  Genes (Basel)       Date:  2021-10-28       Impact factor: 4.096

4.  Robust tests for combining p-values under arbitrary dependency structures.

Authors:  Zhongxue Chen
Journal:  Sci Rep       Date:  2022-02-24       Impact factor: 4.379

  4 in total

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