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Improved polygenic prediction by Bayesian multiple regression on summary statistics

Authors :
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
Source :
Nature Communications, Vol 10, Iss 1, Pp 1-11 (2019)
Publication Year :
2019
Publisher :
Nature Portfolio, 2019.

Abstract

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.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723
Volume :
10
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.08ca063725f844dd8f1661fc58a72c97
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-019-12653-0