Analysis of Case-Control Association Studies: SNPs, Imputation and Haplotypes

Handle URI:
http://hdl.handle.net/10754/597553
Title:
Analysis of Case-Control Association Studies: SNPs, Imputation and Haplotypes
Authors:
Chatterjee, Nilanjan; Chen, Yi-Hau; Luo, Sheng; Carroll, Raymond J.
Abstract:
Although prospective logistic regression is the standard method of analysis for case-control data, it has been recently noted that in genetic epidemiologic studies one can use the "retrospective" likelihood to gain major power by incorporating various population genetics model assumptions such as Hardy-Weinberg-Equilibrium (HWE), gene-gene and gene-environment independence. In this article we review these modern methods and contrast them with the more classical approaches through two types of applications (i) association tests for typed and untyped single nucleotide polymorphisms (SNPs) and (ii) estimation of haplotype effects and haplotype-environment interactions in the presence of haplotype-phase ambiguity. We provide novel insights to existing methods by construction of various score-tests and pseudo-likelihoods. In addition, we describe a novel two-stage method for analysis of untyped SNPs that can use any flexible external algorithm for genotype imputation followed by a powerful association test based on the retrospective likelihood. We illustrate applications of the methods using simulated and real data. © Institute of Mathematical Statistics, 2009.
Citation:
Chatterjee N, Chen Y-H, Luo S, Carroll RJ (2009) Analysis of Case-Control Association Studies: SNPs, Imputation and Haplotypes. Statist Sci 24: 489–502. Available: http://dx.doi.org/10.1214/09-STS297.
Publisher:
Institute of Mathematical Statistics
Journal:
Statistical Science
KAUST Grant Number:
KUS-CI-016-04
Issue Date:
Nov-2009
DOI:
10.1214/09-STS297
Type:
Article
ISSN:
0883-4237
Sponsors:
Chatterjee's research was supported by a gene environment initiative grant from the National Heart Lung and Blood Institute (RO1HL091172-01) and by the Intramural Research Program of the National Cancer Institute. Chen's research was supported by the National Science Council of ROC (NSC 95-2118-M-001-022-MY3). Carroll's research was supported by a grant from the National Cancer Institute (CA57030) and by Award Number KUS-CI-016-04, made by King Abdullah University of Science and Technology (KAUST).
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Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorChatterjee, Nilanjanen
dc.contributor.authorChen, Yi-Hauen
dc.contributor.authorLuo, Shengen
dc.contributor.authorCarroll, Raymond J.en
dc.date.accessioned2016-02-25T12:41:56Zen
dc.date.available2016-02-25T12:41:56Zen
dc.date.issued2009-11en
dc.identifier.citationChatterjee N, Chen Y-H, Luo S, Carroll RJ (2009) Analysis of Case-Control Association Studies: SNPs, Imputation and Haplotypes. Statist Sci 24: 489–502. Available: http://dx.doi.org/10.1214/09-STS297.en
dc.identifier.issn0883-4237en
dc.identifier.doi10.1214/09-STS297en
dc.identifier.urihttp://hdl.handle.net/10754/597553en
dc.description.abstractAlthough prospective logistic regression is the standard method of analysis for case-control data, it has been recently noted that in genetic epidemiologic studies one can use the "retrospective" likelihood to gain major power by incorporating various population genetics model assumptions such as Hardy-Weinberg-Equilibrium (HWE), gene-gene and gene-environment independence. In this article we review these modern methods and contrast them with the more classical approaches through two types of applications (i) association tests for typed and untyped single nucleotide polymorphisms (SNPs) and (ii) estimation of haplotype effects and haplotype-environment interactions in the presence of haplotype-phase ambiguity. We provide novel insights to existing methods by construction of various score-tests and pseudo-likelihoods. In addition, we describe a novel two-stage method for analysis of untyped SNPs that can use any flexible external algorithm for genotype imputation followed by a powerful association test based on the retrospective likelihood. We illustrate applications of the methods using simulated and real data. © Institute of Mathematical Statistics, 2009.en
dc.description.sponsorshipChatterjee's research was supported by a gene environment initiative grant from the National Heart Lung and Blood Institute (RO1HL091172-01) and by the Intramural Research Program of the National Cancer Institute. Chen's research was supported by the National Science Council of ROC (NSC 95-2118-M-001-022-MY3). Carroll's research was supported by a grant from the National Cancer Institute (CA57030) and by Award Number KUS-CI-016-04, made by King Abdullah University of Science and Technology (KAUST).en
dc.publisherInstitute of Mathematical Statisticsen
dc.subjectCase-control studiesen
dc.subjectEmpirical-Bayesen
dc.subjectGenetic epidemiologyen
dc.subjectHaplotypesen
dc.subjectModel averagingen
dc.subjectModel robustnessen
dc.subjectModel selectionen
dc.subjectRetrospective studiesen
dc.subjectShrinkageen
dc.titleAnalysis of Case-Control Association Studies: SNPs, Imputation and Haplotypesen
dc.typeArticleen
dc.identifier.journalStatistical Scienceen
dc.contributor.institutionNational Cancer Institute, Bethesda, United Statesen
dc.contributor.institutionInstitute of Statistical Science, Academia Sinica, Nankang, Taiwanen
dc.contributor.institutionUniversity of Texas School of Public Health, Houston, United Statesen
dc.contributor.institutionTexas A and M University, College Station, United Statesen
kaust.grant.numberKUS-CI-016-04en
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