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Article

Simplifying causal gene identification in GWAS loci

2024-07-29

Abstract excerpt

Genome-wide association studies (GWAS) help to identify disease-linked genetic variants, but pinpointing the most likely causal genes in GWAS loci remains challenging. Existing GWAS gene prioritization tools are powerful but often use complex black box models trained on datasets containing unaddressed biases. Here, we use a data-driven approach to construct a truth set of causal genes in 406 GWAS loci. We train a...

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Identifiers and source

Literature Corpus work
6a6e9cde-f7c6-58da-9ba6-e9e0c59af088
DOI
10.1101/2024.07.26.24311057
Open publication

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Simplifying causal gene identification in GWAS lociDOI 10.1101/2024.07.26.24311057
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