Reference : Benchmarking of univariate pleiotropy detection methods applied to epilepsy
Scientific journals : Article
Life sciences : Genetics & genetic processes
Human health sciences : Neurology
Systems Biomedicine
http://hdl.handle.net/10993/51110
Benchmarking of univariate pleiotropy detection methods applied to epilepsy
English
Adesoji, Oluyomi M. [> >]
Schulz, Herbert [> >]
May, Patrick mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core]
Krause, Roland mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core]
Lerche, Holger [> >]
Nothnagel, Michael [> >]
Epilepsies, Ilae Consortium On Complex [> >]
Sep-2022
Human Mutation
John Wiley & Sons, Ltd
43
9
1314-1332
Yes
International
1059-7794
1098-1004
[en] Association ; Epilepsies ; Meta-analysis ; Pleiotropy ; SNPs
[en] AbstractPleiotropy is a widespread phenomenon that may increase insight into the etiology of biological and disease traits. Since genome-wide association studies frequently provide information on a single trait only, only univariate pleiotropy detection methods are applicable, with yet unknown comparative performance. Here, we compared five such methods with respect to their ability to detect pleiotropy, including meta-analysis, ASSET, cFDR, CPBayes, and PLACO, by performing extended computer simulations that varied the underlying etiological model for pleiotropy for a pair of traits, including the number of causal variants, degree of traits’ overlap, effect sizes as well as trait prevalence, and varying sample sizes. Our results indicate that ASSET provides the best trade-off between power and protection against false positives. We then applied ASSET to a previously published ILAE consortium dataset on complex epilepsies, comprising genetic generalized epilepsy and focal epilepsy cases and corresponding controls. We identified a novel candidate locus at 17q21.32 and confirmed locus 2q24.3, previously identified to act pleiotropically on both epilepsy subtypes by a mega-analysis. Functional annotation, tissue-specific expression and regulatory function analysis as well as Bayesian co-localization analysis corroborated this result, rendering 17q21.32 a worthwhile candidate for follow-up studies on pleiotropy in epilepsies.This article is protected by copyright. All rights reserved.
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
Fonds National de la Recherche - FnR
MechEPI
Researchers ; Professionals
http://hdl.handle.net/10993/51110
10.1002/humu.24417
https://onlinelibrary.wiley.com/doi/abs/10.1002/humu.24417
FnR ; FNR11583046 > Roland Krause > MechEPI > Epileptogenesis Of Genetic Epilepsies > 01/04/2018 > 30/06/2021 > 2017

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