1. LDAK-GBAT: Fast and powerful gene-based association testing using summary statistics.
- Author
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Berrandou, Takiy-Eddine, Balding, David, and Speed, Doug
- Subjects
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FALSE positive error , *GENOME-wide association studies , *STATISTICS , *GENETICS - 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. LDAK-GBAT is a new tool for gene-based association testing using GWAS summary statistics. Applied to 109 phenotypes from large biobanks, LDAK-GBAT finds at least 20% more significant genes than popular tools such as MAGMA and GCTA-FastBAT. Further, LDAK-GBAT is computationally efficient, with good control of type 1 error in simulation studies. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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