Multi-trait analysis of genome-wide association summary statistics using MTAG-Reference-Cited by-同舟云学术

Multi-trait analysis of genome-wide association summary statistics using MTAG

Published:2018-01-01 Issue:2 Volume:50 Page:229-237
ISSN:1061-4036
Container-title:Nature Genetics
language:en
Short-container-title:Nat Genet

Author:

Turley Patrick, ,Walters Raymond K.^ORCID,Maghzian Omeed,Okbay Aysu,Lee James J.^ORCID,Fontana Mark Alan,Nguyen-Viet Tuan Anh,Wedow Robbee^ORCID,Zacher Meghan,Furlotte Nicholas A.,Magnusson Patrik^ORCID,Oskarsson Sven,Johannesson Magnus^ORCID,Visscher Peter M.^ORCID,Laibson David,Cesarini David,Neale Benjamin M.,Benjamin Daniel J.^ORCID,

Publisher

Springer Science and Business Media LLC

Subject

Genetics

Link

http://www.nature.com/articles/s41588-017-0009-4.pdf

Reference30 articles.

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2. Porter, H. F. & O’Reilly, P. F. Multivariate simulation framework reveals performance of multi-trait GWAS methods. Sci. Rep. 7, 38837 (2017).

3. Maier, R. et al. Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder. Am. J. Hum. Genet. 96, 283–294 (2015).

4. Hu, Y. et al. Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction. PLoS Genet. 13, e1006836 (2017).

5. Baselmans, B.M.L. et al. Multivariate genome-wide and integrated transcriptome and epigenome-wide analyses of the well-being spectrum. Preprint at bioRxiv https://doi.org/10.1101/115915 (2017).

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