LDAK-GBAT:Fast and powerful gene-based association testing using summary statistics
| Autor: | David Balding, Takiy eddine Berrandou, Doug Speed |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Berrandou, T-E, Balding, D & Speed, D 2023, ' LDAK-GBAT : Fast and powerful gene-based association testing using summary statistics ', American Journal of Human Genetics, vol. 110, no. 1, pp. 23-29 . https://doi.org/10.1016/j.ajhg.2022.11.010 Am J Hum Genet |
| DOI: | 10.1016/j.ajhg.2022.11.010 |
| Popis: | We present LDAK-GBAT, a novel tool for gene-based association testing using summary statistics from genome-wide association studies. We first evaluate LDAK-GBAT using ten phenotypes from the UK Biobank. We show that LDAK-GBAT is computationally efficient, taking approximately 30 minutes to analyze imputed data (2.9M common, genic SNPs), and requiring less than 10Gb memory. In total, LDAK-GBAT finds 680 genome-wide significant genes (P≤2.8×10−6), which is at least 25% more than each of five existing tools (MAGMA, GCTA-fastBAT, sumFREGAT-SKAT-O, sumFREGAT-PCA and sumFREGAT-ACAT), and 48% more than found by single-SNP analysis. We then analyze 99 additional phenotypes from the UK Biobank, the Million Veterans Project and the Psychiatric Genetics Consortium. In total, LDAK-GBAT finds 7957 significant genes, which is at least 24% more than the best existing tools, and 42% more than found by single-SNP analysis. |
| Databáze: | OpenAIRE |
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