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Accounting for selection and correlation in the analysis of two-stage genome-wide association studies

Title: Accounting for selection and correlation in the analysis of two-stage genome-wide association studies
Author(s): Robertson, DS
Prevost, AT
Bowden, J
Item Type: Journal Article
Abstract: The problem of selection bias has long been recognized in the analysis of two-stage trials, where promising candidates are selected in stage 1 for confirmatory analysis in stage 2. To efficiently correct for bias, uniformly minimum variance conditionally unbiased estimators (UMVCUEs) have been proposed for a wide variety of trial settings, but where the population parameter estimates are assumed to be independent. We relax this assumption and derive the UMVCUE in the multivariate normal setting with an arbitrary known covariance structure. One area of application is the estimation of odds ratios (ORs) when combining a genome-wide scan with a replication study. Our framework explicitly accounts for correlated single nucleotide polymorphisms, as might occur due to linkage disequilibrium. We illustrate our approach on the measurement of the association between 11 genetic variants and the risk of Crohn's disease, as reported in Parkes and others (2007. Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn's disease susceptibility. Nat. Gen.39(7), 830–832.), and show that the estimated ORs can vary substantially if both selection and correlation are taken into account.
Publication Date: 18-Mar-2016
Date of Acceptance: 15-Jan-2016
URI: http://hdl.handle.net/10044/1/43855
DOI: http://dx.doi.org/10.1093/biostatistics/kxw012
ISSN: 1468-4357
Publisher: Oxford University Press
Start Page: 634
End Page: 649
Journal / Book Title: Biostatistics
Volume: 17
Issue: 4
Copyright Statement: © 2016 The Authors. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Mathematical & Computational Biology
Statistics & Probability
Mathematics
Correlated outcomes
Genome-wide scan
Selection bias
Two-stage sample
Uniformly minimum variance conditionally unbiased estimator
GENE-DISEASE ASSOCIATION
UNBIASED ESTIMATION
CONDITIONAL ESTIMATION
EARLY TERMINATION
ADAPTIVE DESIGNS
CLINICAL-TRIALS
ODDS RATIOS
SUSCEPTIBILITY
FUTILITY
POPULATION
Correlated outcomes
Genome-wide scan
Selection bias
Two-stage sample
Uniformly minimum variance conditionally unbiased estimator
Statistics & Probability
0104 Statistics
0604 Genetics
Publication Status: Published
Appears in Collections:Faculty of Medicine
Epidemiology, Public Health and Primary Care



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