Published in

Oxford University Press, Genetics, 3(207), p. 893-902, 2017

DOI: 10.1534/genetics.117.300270

Links

Tools

Export citation

Search in Google Scholar

A Powerful Framework for Integrating eQTL and GWAS Summary Data

Journal article published in 2017 by Zhiyuan Xu, Chong Wu, Peng Wei, Wei Pan
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Abstract Two new gene-based association analysis methods, called PrediXcan and TWAS for GWAS individual-level and summary data, respectively, were recently proposed to integrate GWAS with eQTL data, alleviating two common problems in GWAS by boosting statistical power and facilitating biological interpretation of GWAS discoveries. Based on a novel reformulation of PrediXcan and TWAS, we propose a more powerful gene-based association test to integrate single set or multiple sets of eQTL data with GWAS individual-level data or summary statistics. The proposed test was applied to several GWAS datasets, including two lipid summary association datasets based on ∼100,000 and ∼189,000 samples, respectively, and uncovered more known or novel trait-associated genes, showcasing much improved performance of our proposed method. The software implementing the proposed method is freely available as an R package.