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

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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Fig. 1: Illustration of the problem addressed by CC-GWAS.


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F.P., Z.Z. and B.J.V. are supported by the Danish National Research Foundation (Niels Bohr Professorship to J. McGrath) and also acknowledge the Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH (R248-2017-2003). B.J.V. is also supported by a Lundbeck Foundation Fellowship (R335-2019-2339).

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Correspondence to Florian Privé or Bjarni J. Vilhjalmsson.

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The authors declare no competing interests.

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Privé, F., Zhu, Z. & Vilhjalmsson, B.J. Finding hidden treasures in summary statistics from genome-wide association studies. Nat Genet 53, 431–432 (2021).

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