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

文献类型：期刊论文

作者Kang, Guolian1; Bi, Wenjian1; Zhang, Hang2,3; Pounds, Stanley1; Cheng, Cheng1; Shete, Sanjay4; Zou, Fei5; Zhao, Yanlong2; Zhang, Ji-Feng2,3; Yue, Weihua6,7
刊名GENETICS
出版日期2017-03-01
卷号205期号:3页码:1049-1062
关键词secondary traits rare variants association analyses case-control sequencing study set-valued model
ISSN号0016-6731
DOI10.1534/genetics.116.192377
英文摘要In many case-control designs of genome-wide association (GWAS) or next generation sequencing (NGS) studies, extensive data on secondary traits that may correlate and share the common genetic variants with the primary disease are available. Investigating these secondary traits can provide critical insights into the disease etiology or pathology, and enhance the GWAS or NGS results. Methods based on logistic regression (LG) were developed for this purpose. However, for the identification of rare variants (RVs), certain inadequacies in the LG models and algorithmic instability can cause severely inflated type I error, and significant loss of power, when the two traits are correlated and the RV is associated with the disease, especially at stringent significance levels. To address this issue, we propose a novel set-valued (SV) method that models a binary trait by dichotomization of an underlying continuous variable, and incorporate this into the genetic association model as a critical component. Extensive simulations and an analysis of seven secondary traits in a GWAS of benign ethnic neutropenia show that the SV method consistently controls type I error well at stringent significance levels, has larger power than the LG-based methods, and is robust in performance to effect pattern of the genetic variant (risk or protective), rare or common variants, rare or common diseases, and trait distributions. Because of the SV method's striking and profound advantage, we strongly recommend the SV method be employed instead of the LG-based methods for secondary traits analyses in case-control sequencing studies.
资助项目intramural research program of NHLBI ; NIDDK at the National Institutes of Health (NIH) ; CIDR[HHSN268200782096C] ; CIDR[HHSN268201100011I] ; American Lebanese and Syrian Associated Charities ; National Natural Science Foundation of China[11171333] ; National Natural Science Foundation of China[61134013] ; National Natural Science Foundation of China[81571313] ; National Natural Science Foundation of China[81221002]
WOS研究方向Genetics & Heredity
语种英语
WOS记录号WOS:000395807200004
出版者GENETICS SOCIETY AMERICA
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/25018]  
专题系统科学研究所
通讯作者Kang, Guolian; Yue, Weihua
作者单位1.St Jude Childrens Res Hosp, Dept Biostat, Memphis, TN 38105 USA
2.Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China
4.Univ Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USA
5.Univ N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA
6.Peking Univ, Minist Hlth, Key Lab Mental Hlth, Inst Mental Hlth, Beijing 100191, Peoples R China
7.Peking Univ, Hosp 6, Natl Clin Res Ctr Mental Disorders, Beijing 100191, Peoples R China
推荐引用方式
GB/T 7714		 Kang, Guolian,Bi, Wenjian,Zhang, Hang,et al. A Robust and Powerful Set-Valued Approach to Rare Variant Association Analyses of Secondary Traits in Case-Control Sequencing Studies[J]. GENETICS,2017,205(3):1049-1062.
APA Kang, Guolian.,Bi, Wenjian.,Zhang, Hang.,Pounds, Stanley.,Cheng, Cheng.,...&Yue, Weihua.(2017).A Robust and Powerful Set-Valued Approach to Rare Variant Association Analyses of Secondary Traits in Case-Control Sequencing Studies.GENETICS,205(3),1049-1062.
MLA Kang, Guolian,et al."A Robust and Powerful Set-Valued Approach to Rare Variant Association Analyses of Secondary Traits in Case-Control Sequencing Studies".GENETICS 205.3(2017):1049-1062.

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来源：数学与系统科学研究院

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