OTTERS: a powerful TWAS framework leveraging summary-level reference data
-
Published:2023-03-07
Issue:1
Volume:14
Page:
-
ISSN:2041-1723
-
Container-title:Nature Communications
-
language:en
-
Short-container-title:Nat Commun
Author:
Dai Qile, Zhou Geyu, Zhao HongyuORCID, Võsa UrmoORCID, Franke LudeORCID, Battle AlexisORCID, Teumer AlexanderORCID, Lehtimäki TerhoORCID, Raitakari Olli T., Esko Tõnu, Agbessi Mawussé, Ahsan Habibul, Alves Isabel, Andiappan Anand Kumar, Arindrarto Wibowo, Awadalla Philip, Battle Alexis, Beutner Frank, Jan Bonder Marc, Boomsma Dorret I., Christiansen Mark W., Claringbould Annique, Deelen Patrick, Favé Marie-Julie, Frayling Timothy, Gharib Sina A., Gibson Greg, Heijmans Bastiaan T., Hemani Gibran, Jansen Rick, Kähönen Mika, Kalnapenkis Anette, Kasela Silva, Kettunen Johannes, Kim Yungil, Kirsten Holger, Kovacs Peter, Krohn Knut, Kronberg Jaanika, Kukushkina Viktorija, Kutalik Zoltan, Lee Bernett, Loeffler Markus, Marigorta Urko M., Mei Hailang, Milani Lili, Montgomery Grant W., Müller-Nurasyid Martina, Nauck Matthias, Nivard Michel G., Penninx Brenda, Perola Markus, Pervjakova Natalia, Pierce Brandon L., Powell Joseph, Prokisch Holger, Psaty Bruce M., Ripatti Samuli, Rotzschke Olaf, Rüeger Sina, Saha Ashis, Scholz Markus, Schramm Katharina, Seppälä Ilkka, Slagboom Eline P., Stehouwer Coen D. A., Stumvoll Michael, Sullivan Patrick, ‘t Hoen Peter A. C., Thiery Joachim, Tong Lin, Tönjes Anke, van Dongen Jenny, van Iterson Maarten, van Meurs Joyce, Veldink Jan H., Verlouw Joost, Visscher Peter M., Völker Uwe, Westra Harm-Jan, Wijmenga Cisca, Yaghootka Hanieh, Yang Jian, Zeng Biao, Zhang Futao, Epstein Michael P.ORCID, Yang JingjingORCID,
Abstract
AbstractMost existing TWAS tools require individual-level eQTL reference data and thus are not applicable to summary-level reference eQTL datasets. The development of TWAS methods that can harness summary-level reference data is valuable to enable TWAS in broader settings and enhance power due to increased reference sample size. Thus, we develop a TWAS framework called OTTERS (Omnibus Transcriptome Test using Expression Reference Summary data) that adapts multiple polygenic risk score (PRS) methods to estimate eQTL weights from summary-level eQTL reference data and conducts an omnibus TWAS. We show that OTTERS is a practical and powerful TWAS tool by both simulations and application studies.
Funder
Eesti Teadusagentuur U.S. Department of Health & Human Services | NIH | National Institute on Aging U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences
Publisher
Springer Science and Business Media LLC
Subject
General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry,Multidisciplinary
Reference63 articles.
1. Mancuso, N. et al. Integrating gene expression with summary association statistics to identify genes associated with 30 complex traits. Am. J. Hum. Genet. 100, 473–487 (2017). 2. Gusev, A. et al. Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights. Nat. Genet. 50, 538–548 (2018). 3. Mancuso, N. et al. Large-scale transcriptome-wide association study identifies new prostate cancer risk regions. Nat. Commun. 9, 4079 (2018). 4. Wainberg, M. et al. Opportunities and challenges for transcriptome-wide association studies. Nat. Genet. 51, 592–599 (2019). 5. Strunz, T., Lauwen, S., Kiel, C., Hollander, A. & Weber, B. H. F. A transcriptome-wide association study based on 27 tissues identifies 106 genes potentially relevant for disease pathology in age-related macular degeneration. Sci. Rep. 10, 1584 (2020).
Cited by
17 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
|
|