OTTERS: a powerful TWAS framework leveraging summary-level reference data
Dai Qile; Zhou Geyu; Zhao Hongyu; Võsa Urmo; Franke Lude; Battle Alexis; Teumer Alexander; Lehtimäki Terho; Raitakari Olli T.; Esko Tõnu; Consortium eQTLGen; Epstein Michael P., Yang Jingjing
OTTERS: a powerful TWAS framework leveraging summary-level reference data
Dai Qile
Zhou Geyu
Zhao Hongyu
Võsa Urmo
Franke Lude
Battle Alexis
Teumer Alexander
Lehtimäki Terho
Raitakari Olli T.
Esko Tõnu
Consortium eQTLGen
Epstein Michael P., Yang Jingjing
Springer Nature
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2023052346214
https://urn.fi/URN:NBN:fi-fe2023052346214
Tiivistelmä
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.
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