Literature DB >> 28672760

Genetic association test based on principal component analysis.

Zhongxue Chen1, Shizhong Han1, Kai Wang1.   

Abstract

Many gene- and pathway-based association tests have been proposed in the literature. Among them, the SKAT is widely used, especially for rare variants association studies. In this paper, we investigate the connection between SKAT and a principal component analysis. This investigation leads to a procedure that encompasses SKAT as a special case. Through simulation studies and real data applications, we compare the proposed method with some existing tests.

Keywords:  gene-based association; pathway-based association; rare variants

Mesh:

Year:  2017        PMID: 28672760     DOI: 10.1515/sagmb-2016-0061

Source DB:  PubMed          Journal:  Stat Appl Genet Mol Biol        ISSN: 1544-6115


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

Authors:  Zhongxue Chen; Kai Wang
Journal:  Hum Genet       Date:  2017-09-01       Impact factor: 4.132

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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