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 for this work

Center for Quantitative Genetics and Genomics

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

7 Citations (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.

Original language	English
Journal	American Journal of Human Genetics
Volume	110
Issue	1
Pages (from-to)	23-29
Number of pages	7
ISSN	0002-9297
DOIs	https://doi.org/10.1016/j.ajhg.2022.11.010
Publication status	Published - Jan 2023

Keywords

UK Biobank
complex traits
gene-based association testing
genome-wide association study
statistical genetics
Genome-Wide Association Study
Phenotype
Polymorphism, Single Nucleotide/genetics
Genetic Testing

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title = "LDAK-GBAT: Fast and powerful gene-based association testing using summary statistics",

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",

year = "2023",

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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

JF - American Journal of Human Genetics

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ER -

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

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Keywords

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