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OTTERS: a powerful TWAS framework leveraging summary-level reference data

Authors :
Dai, Qile
Zhou, Geyu
Zhao, Hongyu
Võsa, Urmo
Franke, Lude
Battle, Alexis
Teumer, Alexander
Lehtimäki, Terho
Raitakari, Olli T.
Esko, Tõnu
Agbessi, Mawussé
Ahsan, Habibul
Alves, Isabel
Andiappan, Anand Kumar
Arindrarto, Wibowo
Awadalla, Philip
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
Yaghootkar, Hanieh
Yang, Jian
Zeng, Biao
Zhang, Futao
Epstein, Michael P.
Yang, Jingjing
Dai, Qile
Zhou, Geyu
Zhao, Hongyu
Võsa, Urmo
Franke, Lude
Battle, Alexis
Teumer, Alexander
Lehtimäki, Terho
Raitakari, Olli T.
Esko, Tõnu
Agbessi, Mawussé
Ahsan, Habibul
Alves, Isabel
Andiappan, Anand Kumar
Arindrarto, Wibowo
Awadalla, Philip
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
Yaghootkar, Hanieh
Yang, Jian
Zeng, Biao
Zhang, Futao
Epstein, Michael P.
Yang, Jingjing
Publication Year :
2023

Abstract

Most 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.<br />Godkänd;2023;Nivå 0;2023-04-06 (hanlid);Funder: for more funders see the article https://doi.org/10.1038/s41467-023-36862-w

Details

Database :
OAIster
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1400043965
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1038.s41467-023-36862-w