OTTERS: a Powerful TWAS Framework Leveraging Summary-level Reference Data

Overview

Journal Nat Commun

Specialty Biology

Date 2023 Mar 7

PMID 36882394

Authors

Qile Dai

Geyu Zhou

Hongyu Zhao

Urmo Vosa

Lude Franke

Alexis Battle

Alexander Teumer

Terho Lehtimaki

Olli T Raitakari

Tonu Esko

Michael P Epstein

Jingjing Yang

Affiliations

Soon will be listed here.

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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