Weighting sequence variants based on their annotation increases power of whole-genome association studies

Gardar Sveinbjornsson; Anders Albrechtsen; Florian Zink; Sigurjón A. Gudjonsson; Asmundur Oddson; Gísli Másson; Hilma Holm; Augustine Kong; Unnur Thorsteinsdottir; Patrick Sulem; Daniel F. Gudbjartsson; Kari Stefansson

doi:10.1038/ng.3507

Weighting sequence variants based on their annotation increases power of whole-genome association studies

Gardar Sveinbjornsson, Anders Albrechtsen, Florian Zink, Sigurjón A. Gudjonsson, Asmundur Oddson, Gísli Másson, Hilma Holm, Augustine Kong, Unnur Thorsteinsdottir, Patrick Sulem, Daniel F. Gudbjartsson, Kari Stefansson

Computational and RNA Biology

89 Citations (Scopus)

Abstract

The consensus approach to genome-wide association studies (GWAS) has been to assign equal prior probability of association to all sequence variants tested. However, some sequence variants, such as loss-of-function and missense variants, are more likely than others to affect protein function and are therefore more likely to be causative. Using data from whole-genome sequencing of 2,636 Icelanders and the association results for 96 quantitative and 123 binary phenotypes, we estimated the enrichment of association signals by sequence annotation. We propose a weighted Bonferroni adjustment that controls for the family-wise error rate (FWER), using as weights the enrichment of sequence annotations among association signals. We show that this weighted adjustment increases the power to detect association over the standard Bonferroni correction. We use the enrichment of associations by sequence annotation we have estimated in Iceland to derive significance thresholds for other populations with different numbers and combinations of sequence variants.

Original language	English
Journal	Nature Genetics
Volume	48
Issue number	3
Pages (from-to)	314-317
Number of pages	4
ISSN	1061-4036
DOIs	https://doi.org/10.1038/ng.3507
Publication status	Published - 1 Mar 2016

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title = "Weighting sequence variants based on their annotation increases power of whole-genome association studies",

abstract = "The consensus approach to genome-wide association studies (GWAS) has been to assign equal prior probability of association to all sequence variants tested. However, some sequence variants, such as loss-of-function and missense variants, are more likely than others to affect protein function and are therefore more likely to be causative. Using data from whole-genome sequencing of 2,636 Icelanders and the association results for 96 quantitative and 123 binary phenotypes, we estimated the enrichment of association signals by sequence annotation. We propose a weighted Bonferroni adjustment that controls for the family-wise error rate (FWER), using as weights the enrichment of sequence annotations among association signals. We show that this weighted adjustment increases the power to detect association over the standard Bonferroni correction. We use the enrichment of associations by sequence annotation we have estimated in Iceland to derive significance thresholds for other populations with different numbers and combinations of sequence variants.",

author = "Gardar Sveinbjornsson and Anders Albrechtsen and Florian Zink and Gudjonsson, {Sigurj{\'o}n A.} and Asmundur Oddson and G{\'i}sli M{\'a}sson and Hilma Holm and Augustine Kong and Unnur Thorsteinsdottir and Patrick Sulem and Gudbjartsson, {Daniel F.} and Kari Stefansson",

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T1 - Weighting sequence variants based on their annotation increases power of whole-genome association studies

AU - Sveinbjornsson, Gardar

AU - Albrechtsen, Anders

AU - Zink, Florian

AU - Gudjonsson, Sigurjón A.

AU - Oddson, Asmundur

AU - Másson, Gísli

AU - Holm, Hilma

AU - Kong, Augustine

AU - Thorsteinsdottir, Unnur

AU - Sulem, Patrick

AU - Gudbjartsson, Daniel F.

AU - Stefansson, Kari

PY - 2016/3/1

Y1 - 2016/3/1

N2 - The consensus approach to genome-wide association studies (GWAS) has been to assign equal prior probability of association to all sequence variants tested. However, some sequence variants, such as loss-of-function and missense variants, are more likely than others to affect protein function and are therefore more likely to be causative. Using data from whole-genome sequencing of 2,636 Icelanders and the association results for 96 quantitative and 123 binary phenotypes, we estimated the enrichment of association signals by sequence annotation. We propose a weighted Bonferroni adjustment that controls for the family-wise error rate (FWER), using as weights the enrichment of sequence annotations among association signals. We show that this weighted adjustment increases the power to detect association over the standard Bonferroni correction. We use the enrichment of associations by sequence annotation we have estimated in Iceland to derive significance thresholds for other populations with different numbers and combinations of sequence variants.

AB - The consensus approach to genome-wide association studies (GWAS) has been to assign equal prior probability of association to all sequence variants tested. However, some sequence variants, such as loss-of-function and missense variants, are more likely than others to affect protein function and are therefore more likely to be causative. Using data from whole-genome sequencing of 2,636 Icelanders and the association results for 96 quantitative and 123 binary phenotypes, we estimated the enrichment of association signals by sequence annotation. We propose a weighted Bonferroni adjustment that controls for the family-wise error rate (FWER), using as weights the enrichment of sequence annotations among association signals. We show that this weighted adjustment increases the power to detect association over the standard Bonferroni correction. We use the enrichment of associations by sequence annotation we have estimated in Iceland to derive significance thresholds for other populations with different numbers and combinations of sequence variants.

U2 - 10.1038/ng.3507

DO - 10.1038/ng.3507

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SN - 1061-4036

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EP - 317

JO - Nature: New biology

JF - Nature: New biology

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Weighting sequence variants based on their annotation increases power of whole-genome association studies

Abstract

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