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 et al. · Nat Commun · 2023

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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.

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