Finding hidden treasures in summary statistics from genome-wide association studies

Florian Privé; Zhihong Zhu; Bjarni J. Vilhjalmsson

doi:10.1038/s41588-021-00824-z

Finding hidden treasures in summary statistics from genome-wide association studies

Florian Privé^*, Zhihong Zhu, Bjarni J. Vilhjalmsson^*

^*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Comment/debate/letter to the editor › Communication

2 Citations (Scopus)

Abstract

Case-case genome-wide association studies (GWAS) within a single genotyped cohort have proven useful in identifying genetic variants explaining different health outcomes, yet they are limited by data availability. A new study by Peyrot and Price proposes a clever statistical method to overcome this problem by inferring case-case GWAS results from a pair of standard case-control GWAS summary statistics that need not be from the same cohort.

Original language	English
Journal	Nature Genetics
Volume	53
Issue	4
Pages (from-to)	431-432
Number of pages	2
ISSN	1061-4036
DOIs	https://doi.org/10.1038/s41588-021-00824-z
Publication status	Published - Apr 2021

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title = "Finding hidden treasures in summary statistics from genome-wide association studies",

abstract = "Case-case genome-wide association studies (GWAS) within a single genotyped cohort have proven useful in identifying genetic variants explaining different health outcomes, yet they are limited by data availability. A new study by Peyrot and Price proposes a clever statistical method to overcome this problem by inferring case-case GWAS results from a pair of standard case-control GWAS summary statistics that need not be from the same cohort.",

author = "Florian Priv{\'e} and Zhihong Zhu and Vilhjalmsson, {Bjarni J.}",

year = "2021",

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AU - Privé, Florian

AU - Zhu, Zhihong

AU - Vilhjalmsson, Bjarni J.

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N2 - Case-case genome-wide association studies (GWAS) within a single genotyped cohort have proven useful in identifying genetic variants explaining different health outcomes, yet they are limited by data availability. A new study by Peyrot and Price proposes a clever statistical method to overcome this problem by inferring case-case GWAS results from a pair of standard case-control GWAS summary statistics that need not be from the same cohort.

AB - Case-case genome-wide association studies (GWAS) within a single genotyped cohort have proven useful in identifying genetic variants explaining different health outcomes, yet they are limited by data availability. A new study by Peyrot and Price proposes a clever statistical method to overcome this problem by inferring case-case GWAS results from a pair of standard case-control GWAS summary statistics that need not be from the same cohort.

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U2 - 10.1038/s41588-021-00824-z

DO - 10.1038/s41588-021-00824-z

M3 - Comment/debate/letter to the editor

C2 - 33833451

AN - SCOPUS:85104167001

SN - 1061-4036

VL - 53

SP - 431

EP - 432

JO - Nature Genetics

JF - Nature Genetics

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Finding hidden treasures in summary statistics from genome-wide association studies

Abstract

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