Genetic Epidemiology, Psychiatric Genetics, Asthma Genetics and Statistical Genetics Laboratories investigate the pattern of disease in families, particularly identical and non-identical twins, to assess the relative importance of genes and environment in a variety of important health problems.
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PMID
30443694
TITLE
A Fast Method for Estimating Statistical Power of Multivariate GWAS in Real Case Scenarios: Examples from the Field of Imaging Genetics.
ABSTRACT
In GWAS of imaging phenotypes (e.g., by the ENIGMA and CHARGE consortia), the growing number of phenotypes considered presents a statistical challenge that other fields are not experiencing (e.g. psychiatry and the Psychiatric Genetics Consortium). However, the multivariate nature of MRI measurements may also be an advantage as many of the MRI phenotypes are correlated and multivariate methods could be considered. Here, we compared the statistical power of a multivariate GWAS versus the current univariate approach, which consists of multiple univariate analyses. To do so, we used results from twin models to estimate pertinent vectors of SNP effect sizes on brain imaging phenotypes, as well as the residual correlation matrices, necessary to estimate analytically the statistical power. We showed that for subcortical structure volumes and hippocampal subfields, a multivariate GWAS yields similar statistical power to the current univariate approach. Our analytical approach is as accurate but ~ 1000 times faster than simulations and we have released the code to facilitate the investigation of other scenarios, may they be outside the field of imaging genetics.
DATE PUBLISHED
2018 Nov 15
HISTORY
PUBSTATUS PUBSTATUSDATE
received 2017/12/07
accepted 2018/10/19
entrez 2018/11/17 06:00
pubmed 2018/11/18 06:00
medline 2018/11/18 06:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
Couvy-Duchesne B Couvy-Duchesne Baptiste B QIMR Berghofer Medical Research Institute, Brisbane, 4006, Australia. b.couvyduchesne@uq.edu.au.
Strike LT Strike Lachlan T LT Queensland Brain Institute, The University of Queensland, Brisbane, 4072, Australia.
McMahon KL McMahon Katie L KL Centre for Advanced Imaging, The University of Queensland, Brisbane, 4072, Australia.
de Zubicaray GI de Zubicaray Greig I GI Institute of Health and Biomedical Innovations, Queensland Institute of Technology, Brisbane, 4059, Australia.
Thompson PM Thompson Paul M PM Imaging Genetics Center, Keck School of Medicine, University of Southern California, Marina del Rey, Los Angeles, CA, 90292, USA.
Martin NG Martin Nicholas G NG QIMR Berghofer Medical Research Institute, Brisbane, 4006, Australia.
Medland SE Medland Sarah E SE QIMR Berghofer Medical Research Institute, Brisbane, 4006, Australia.
Wright MJ Wright Margaret J MJ Centre for Advanced Imaging, The University of Queensland, Brisbane, 4072, Australia.
INVESTIGATORS
JOURNAL
VOLUME:
ISSUE:
TITLE: Behavior genetics
ISOABBREVIATION: Behav. Genet.
YEAR: 2018
MONTH: Nov
DAY: 15
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Internet
ISSN: 1573-3297
ISSNTYPE: Electronic
MEDLINE JOURNAL
MEDLINETA: Behav Genet
COUNTRY: United States
ISSNLINKING: 0001-8244
NLMUNIQUEID: 0251711
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Journal Article
COMMENTS AND CORRECTIONS
GRANTS
GRANTID AGENCY COUNTRY
R01 HD050735 National Institutes of Health
U54 EB020403 National Institutes of Health
496682 National Health and Medical Research Council
1009064 National Health and Medical Research Council
APP1103623 National Health and Medical Research Council
A7960034 Australian Research Council
A79906588 Australian Research Council
A79801419 Australian Research Council
DP0212016 Australian Research Council
GENERAL NOTE
KEYWORDS
KEYWORD
GWAS
MRI imaging
Multivariate
Statistical power
Twin models
Univariate
MESH HEADINGS
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
OTHER ID's