PSYCH OpenIR  > 中国科学院心理健康重点实验室
A robust and powerful two-step testing procedure for local ancestry adjusted allelic association analysis in admixed populations
Duan, Qing1,2,3; Xu, Zheng1,4,5,7,8; Raffield, Laura M.1; Chang, Suhua9; Wu, Di4,6; Lange, Ethan M.10,11; Reiner, Alex P.12,13; Li, Yun1,2,4,5
2018-04-01
Source PublicationGENETIC EPIDEMIOLOGY
Correspondent Emailyunli@med.unc.edu
ISSN0741-0395
SubtypeArticle
Volume42Issue:3Pages:288-302
Contribution Rank9
Abstract

Genetic association studies in admixed populations allow us to gain deeper understanding of the genetic architecture of human diseases and traits. However, population stratification, complicated linkage disequilibrium (LD) patterns, and the complex interplay of allelic and ancestry effects on phenotypic traits pose challenges in such analyses. These issues may lead to detecting spurious associations and/or result in reduced statistical power. Fortunately, if handled appropriately, these same challenges provide unique opportunities for gene mapping. To address these challenges and to take these opportunities, we propose a robust and powerful two-step testing procedure Local Ancestry Adjusted Allelic (LAAA) association. In the first step, LAAA robustly captures associations due to allelic effect, ancestry effect, and interaction effect, allowing detection of effect heterogeneity across ancestral populations. In the second step, LAAA identifies the source of association, namely allelic, ancestry, or the combination. By jointly modeling allele, local ancestry, and ancestry-specific allelic effects, LAAA is highly powerful in capturing the presence of interaction between ancestry and allele effect. We evaluated the validity and statistical power of LAAA through simulations over a broad spectrum of scenarios. We further illustrated its usefulness by application to the Candidate Gene Association Resource (CARe) African American participants for association with hemoglobin levels. We were able to replicate independent groups' previously identified loci that would have been missed in CARe without joint testing. Moreover, the loci, for which LAAA detected potential effect heterogeneity, were replicated among African Americans from the Women's Health Initiative study. LAAA is freely available at . https://yunliweb.its.unc.edu/LAAA.

KeywordAdmixed Populations Association Analysis Effect Heterogeneity Genome-wide Association Studies Gwas Local Ancestry Population Stratification Testing Procedure
DOI10.1002/gepi.22104
Indexed BySCI
Language英语
Funding OrganizationNational Human Genome Research Institute(R01HG006292 ; National Heart, Lung, and Blood Institute(R01HL129132 ; R01HG006703) ; R21HL126045)
WOS Research AreaGenetics & Heredity ; Mathematical & Computational Biology
WOS SubjectGenetics & Heredity ; Mathematical & Computational Biology
WOS IDWOS:000427473900005
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS KeywordGENOME-WIDE ASSOCIATION ; BLOOD-CELL TRAITS ; GENETIC ASSOCIATION ; AFRICAN-AMERICANS ; VARIANTS ; ADMIXTURE ; INFERENCE ; DESIGN ; STRATIFICATION ; HETEROGENEITY
Citation statistics
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/26055
Collection中国科学院心理健康重点实验室
Affiliation1.Univ N Carolina, Dept Genet, Campus Box 7264, Chapel Hill, NC 27599 USA
2.Univ N Carolina, Curriculum Bioinformat & Computat Biol, Chapel Hill, NC USA
3.Univ N Carolina, Dept Stat, Chapel Hill, NC USA
4.Univ N Carolina, Dept Biostat, Chapel Hill, NC USA
5.Univ N Carolina, Dept Comp Sci, Chapel Hill, NC USA
6.Univ N Carolina, Dept Periodontol, Chapel Hill, NC USA
7.Univ Nebraska, Dept Stat, Lincoln, NE USA
8.Univ Nebraska, Initiat Quantitat Life Sci, Lincoln, NE USA
9.Chinese Acad Sci, Inst Psychol, CAS Key Lab Mental Hlth, Beijing, Peoples R China
10.Univ Colorado, Dept Med, Anschutz Med Campus, Denver, CO USA
11.Univ Colorado, Dept Biostat & Informat, Denver, CO 80202 USA
12.Fred Hutchinson Canc Res Ctr, 1124 Columbia St, Seattle, WA 98104 USA
13.Univ Washington, Dept Epidemiol, Seattle, WA 98195 USA
Recommended Citation
GB/T 7714
Duan, Qing,Xu, Zheng,Raffield, Laura M.,et al. A robust and powerful two-step testing procedure for local ancestry adjusted allelic association analysis in admixed populations[J]. GENETIC EPIDEMIOLOGY,2018,42(3):288-302.
APA Duan, Qing.,Xu, Zheng.,Raffield, Laura M..,Chang, Suhua.,Wu, Di.,...&Li, Yun.(2018).A robust and powerful two-step testing procedure for local ancestry adjusted allelic association analysis in admixed populations.GENETIC EPIDEMIOLOGY,42(3),288-302.
MLA Duan, Qing,et al."A robust and powerful two-step testing procedure for local ancestry adjusted allelic association analysis in admixed populations".GENETIC EPIDEMIOLOGY 42.3(2018):288-302.
Files in This Item:
File Name/Size DocType Version Access License
A robust and powerfu(1410KB)期刊论文出版稿限制开放CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Duan, Qing]'s Articles
[Xu, Zheng]'s Articles
[Raffield, Laura M.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Duan, Qing]'s Articles
[Xu, Zheng]'s Articles
[Raffield, Laura M.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Duan, Qing]'s Articles
[Xu, Zheng]'s Articles
[Raffield, Laura M.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: A robust and powerful two-step testing procedure for local ancestry adjusted allelic association analysis in admixed populations.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.