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A powerful and efficient two-stage method for detecting gene-to-gene interactions in GWAS.
Biostatistics 18, 477-494 (2017)
Verlagsversion
Forschungsdaten
DOI
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For over a decade functional gene-to-gene interaction (epistasis) has been suspected to be a determinant in the "missing heritability" of complex traits. However, searching for epistasis on the genome-wide scale has been challenging due to the prohibitively large number of tests which result in a serious loss of statistical power as well as computational challenges. In this article, we propose a two-stage method applicable to existing case-control data sets, which aims to lessen both of these problems by pre-assessing whether a candidate pair of genetic loci is involved in epistasis before it is actually tested for interaction with respect to a complex phenotype. The pre-assessment is based on a two-locus genotype independence test performed in the sample of cases. Only the pairs of loci that exhibit non-equilibrium frequencies are analyzed via a logistic regression score test, thereby reducing the multiple testing burden. Since only the computationally simple independence tests are performed for all pairs of loci while the more demanding score tests are restricted to the most promising pairs, genome-wide association study (GWAS) for epistasis becomes feasible. By design our method provides strong control of the type I error. Its favourable power properties especially under the practically relevant misspecification of the interaction model are illustrated. Ready-to-use software is available. Using the method we analyzed Parkinson's disease in four cohorts and identified possible interactions within several SNP pairs in multiple cohorts.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Case-control Design ; Epistasis ; Genetic Interactions ; Parkinson’s Disease ; Two-stage Testing
ISSN (print) / ISBN
1465-4644
e-ISSN
1465-4644
Zeitschrift
Biostatistics
Quellenangaben
Band: 18,
Heft: 3,
Seiten: 477-494
Verlag
Oxford University Press
Verlagsort
Oxford [u.a.]
Nichtpatentliteratur
Publikationen
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Epidemiology II (EPI2)
CF Genomics (CF-GEN)
Institute of Human Genetics (IHG)
CF Genomics (CF-GEN)
Institute of Human Genetics (IHG)