Retrospective versus prospective score tests for genetic association with case‐control data

Biometrics ◽  
2020 ◽  
Author(s):  
Yukun Liu ◽  
Pengfei Li ◽  
Lei Song ◽  
Kai Yu ◽  
Jing Qin
Keyword(s):  
Genetic Association ◽  
Case Control ◽  
Control Data ◽  
Score Tests

scholarly journals Genetic association tests: a method for the joint analysis of family and case-control data

2009 ◽  
Vol 4 (1) ◽  
pp. 2 ◽  
Author(s):  
Courtney Gray-McGuire ◽  
Murielle Bochud ◽  
Robert Goodloe ◽  
Robert C Elston
Keyword(s):  
Genetic Association ◽  
Case Control ◽  
Joint Analysis ◽  
Control Data ◽  
Association Tests ◽  
Genetic Association Tests

scholarly journals Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies

2017 ◽  
Vol 42 (2) ◽  
pp. 146-155 ◽  
Author(s):  
Minsun Song ◽  
William Wheeler ◽  
Neil E. Caporaso ◽  
Maria Teresa Landi ◽  
Nilanjan Chatterjee
Keyword(s):  
Genetic Association ◽  
Case Control ◽  
Genotype Data ◽  
Case Control Studies ◽  
Score Tests ◽  
Gene Environment

scholarly journals Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies

2016 ◽  
Author(s):  
Minsun Song ◽  
William Wheeler ◽  
Neil E. Caporaso ◽  
Maria Teresa Landi ◽  
Nilanjan Chatterjee
Keyword(s):  
Genetic Association ◽  
Association Studies ◽  
Case Control ◽  
Maximum Likelihood Estimates ◽  
Genome Wide Association ◽  
Alternative Methods ◽  
Case Control Studies ◽  
Score Tests ◽  
Gene Environment ◽  
Genome Wide

AbstractBackgroundGenome-wide association studies (GWAS) are now routinely imputed for untyped SNPs based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele count for imputed SNPs as the dosage variable is known to produce valid score test for genetic association.MethodsIn this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic association incorporating gene-environment interactions. We focus on case-control association studies where inference in an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene-environment independence in the underlying population. As increasingly large scale GWAS are being performed through consortia effort where it is preferable to share only summary-level information across studies, we also describe simple mechanisms for implementing score-tests based on standard meta-analysis of “one-step” maximum-likelihood estimates across studies.ResultsApplications of the methods in simulation studies and a dataset from genome-wide association study of lung cancer illustrate ability of the proposed methods to maintain type-I error rates for underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, retrospective methods can lead to considerable efficiency gain for modeling of gene-environment interactions under the assumption of gene-environment independence.ConclusionsProposed methods allow valid analysis of imputed SNPs in case-control studies of gene-environment interaction using alternative strategies that had been earlier available only for genotyped SNPs.

scholarly journals Global, local and focused geographic clustering for case-control data with residential histories

2005 ◽  
Vol 4 (1) ◽  
Author(s):  
Geoffrey M Jacquez ◽  
Andy Kaufmann ◽  
Jaymie Meliker ◽  
Pierre Goovaerts ◽  
Gillian AvRuskin ◽  
...  
Keyword(s):  
Case Control ◽  
Control Data ◽  
Geographic Clustering

scholarly journals Power and sample size for multivariate logistic modeling of unmatched case-control studies

2017 ◽  
Vol 28 (3) ◽  
pp. 822-834
Author(s):  
Mitchell H Gail ◽  
Sebastien Haneuse
Keyword(s):  
Logistic Regression ◽  
Sample Size ◽  
Case Control ◽  
Simulation Methods ◽  
Case Control Studies ◽  
Control Data ◽  
Logistic Analysis ◽  
Sample Size Calculations ◽  
Control Designs ◽  
Univariate Analyses

Sample size calculations are needed to design and assess the feasibility of case-control studies. Although such calculations are readily available for simple case-control designs and univariate analyses, there is limited theory and software for multivariate unconditional logistic analysis of case-control data. Here we outline the theory needed to detect scalar exposure effects or scalar interactions while controlling for other covariates in logistic regression. Both analytical and simulation methods are presented, together with links to the corresponding software.

Genetic association between WNT10B polymorphisms and obesity in a Belgian case–control population is restricted to males

2012 ◽  
Vol 105 (3) ◽  
pp. 489-493 ◽  
Author(s):  
J.K. Van Camp ◽  
S. Beckers ◽  
D. Zegers ◽  
A. Verrijken ◽  
L.F. Van Gaal ◽  
...  
Keyword(s):  
Genetic Association ◽  
Case Control ◽  
Control Population
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