Nature Communications (Nov 2019)

Improved polygenic prediction by Bayesian multiple regression on summary statistics

  • Luke R. Lloyd-Jones,
  • Jian Zeng,
  • Julia Sidorenko,
  • Loïc Yengo,
  • Gerhard Moser,
  • Kathryn E. Kemper,
  • Huanwei Wang,
  • Zhili Zheng,
  • Reedik Magi,
  • Tõnu Esko,
  • Andres Metspalu,
  • Naomi R. Wray,
  • Michael E. Goddard,
  • Jian Yang,
  • Peter M. Visscher

DOI
https://doi.org/10.1038/s41467-019-12653-0
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 11

Abstract

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Various approaches are being used for polygenic prediction including Bayesian multiple regression methods that require access to individual-level genotype data. Here, the authors extend BayesR to utilise GWAS summary statistics (SBayesR) and show that it outperforms other summary statistic-based methods.