Nontrivial Replication of Loci Detected by Multi-Trait Methods

Zheng Ning, Yakov A. Tsepilov, Sodbo Zh. Sharapov, Zhipeng Wang, Alexander K. Grishenko, Xiao Feng, Masoud Shirali, Peter K. Joshi, James F. Wilson, Yudi Pawitan, Chris S. Haley, Yurii S. Aulchenko, Xia Shen

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

The ever-growing genome-wide association studies (GWAS) have revealed widespread pleiotropy. To exploit this, various methods that jointly consider associations of a genetic variant with multiple traits have been developed. Most efforts have been made concerning improving GWAS discovery power. However, how to replicate these discovered pleiotropic loci has yet to be discussed thoroughly. Unlike a single-trait scenario, multi-trait replication is not trivial considering the underlying genotype-multi-phenotype map of the associations. Here, we evaluate four methods for replicating multi-trait associations, corresponding to four levels of replication strength. Weak replication cannot justify pleiotropic genetic effects, whereas strong replication using our developed correlation methods can inform consistent pleiotropic genetic effects across the discovery and replication samples. We provide a protocol for replicating multi-trait genetic associations in practice. The described methods are implemented in the free and open-source R package MultiABEL.
Original languageEnglish
JournalFrontiers in Genetics
Publication statusPublished - 3 Feb 2021


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