LDAK-GBAT: Fast and powerful gene-based association testing using summary statistics

Takiy-Eddine Berrandou; David Balding; Doug Speed

doi:10.1016/j.ajhg.2022.11.010

LDAK-GBAT: Fast and powerful gene-based association testing using summary statistics

Takiy-Eddine Berrandou^*, David Balding, Doug Speed^*

^*Corresponding author af dette arbejde

Center for Kvantitativ Genetik og Genomforskning, Aarhus

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

8 Citationer (Scopus)

Abstract

We present LDAK-GBAT, a tool for gene-based association testing using summary statistics from genome-wide association studies that is computationally efficient, produces well-calibrated p values, and is significantly more powerful than existing tools. LDAK-GBAT takes approximately 30 min to analyze imputed data (2.9M common, genic SNPs), requiring less than 10 Gb memory. It shows good control of type 1 error given an appropriate reference panel. Across 109 phenotypes (82 from the UK Biobank, 18 from the Million Veteran Program, and nine from the Psychiatric Genetics Consortium), LDAK-GBAT finds on average 19% (SE: 1%) more significant genes than the existing tool sumFREGAT-ACAT, with even greater gains in comparison with MAGMA, GCTA-fastBAT, sumFREGAT-SKAT-O, and sumFREGAT-PCA.

Originalsprog	Engelsk
Tidsskrift	American Journal of Human Genetics
Vol/bind	110
Nummer	1
Sider (fra-til)	23-29
Antal sider	7
ISSN	0002-9297
DOI	https://doi.org/10.1016/j.ajhg.2022.11.010
Status	Udgivet - jan. 2023

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10.1016/j.ajhg.2022.11.010

https://www.medrxiv.org/content/medrxiv/early/2022/07/05/2022.07.01.22277161.full.pdfLicens: CC BY

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abstract = "We present LDAK-GBAT, a tool for gene-based association testing using summary statistics from genome-wide association studies that is computationally efficient, produces well-calibrated p values, and is significantly more powerful than existing tools. LDAK-GBAT takes approximately 30 min to analyze imputed data (2.9M common, genic SNPs), requiring less than 10 Gb memory. It shows good control of type 1 error given an appropriate reference panel. Across 109 phenotypes (82 from the UK Biobank, 18 from the Million Veteran Program, and nine from the Psychiatric Genetics Consortium), LDAK-GBAT finds on average 19% (SE: 1%) more significant genes than the existing tool sumFREGAT-ACAT, with even greater gains in comparison with MAGMA, GCTA-fastBAT, sumFREGAT-SKAT-O, and sumFREGAT-PCA.",

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author = "Takiy-Eddine Berrandou and David Balding and Doug Speed",

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doi = "10.1016/j.ajhg.2022.11.010",

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AU - Balding, David

AU - Speed, Doug

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N2 - We present LDAK-GBAT, a tool for gene-based association testing using summary statistics from genome-wide association studies that is computationally efficient, produces well-calibrated p values, and is significantly more powerful than existing tools. LDAK-GBAT takes approximately 30 min to analyze imputed data (2.9M common, genic SNPs), requiring less than 10 Gb memory. It shows good control of type 1 error given an appropriate reference panel. Across 109 phenotypes (82 from the UK Biobank, 18 from the Million Veteran Program, and nine from the Psychiatric Genetics Consortium), LDAK-GBAT finds on average 19% (SE: 1%) more significant genes than the existing tool sumFREGAT-ACAT, with even greater gains in comparison with MAGMA, GCTA-fastBAT, sumFREGAT-SKAT-O, and sumFREGAT-PCA.

AB - We present LDAK-GBAT, a tool for gene-based association testing using summary statistics from genome-wide association studies that is computationally efficient, produces well-calibrated p values, and is significantly more powerful than existing tools. LDAK-GBAT takes approximately 30 min to analyze imputed data (2.9M common, genic SNPs), requiring less than 10 Gb memory. It shows good control of type 1 error given an appropriate reference panel. Across 109 phenotypes (82 from the UK Biobank, 18 from the Million Veteran Program, and nine from the Psychiatric Genetics Consortium), LDAK-GBAT finds on average 19% (SE: 1%) more significant genes than the existing tool sumFREGAT-ACAT, with even greater gains in comparison with MAGMA, GCTA-fastBAT, sumFREGAT-SKAT-O, and sumFREGAT-PCA.

KW - UK Biobank

KW - complex traits

KW - gene-based association testing

KW - genome-wide association study

KW - statistical genetics

KW - Genome-Wide Association Study

KW - Phenotype

KW - Polymorphism, Single Nucleotide/genetics

KW - Genetic Testing

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DO - 10.1016/j.ajhg.2022.11.010

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JO - American Journal of Human Genetics

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LDAK-GBAT: Fast and powerful gene-based association testing using summary statistics

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