A multi-institutional team of researchers has devised a framework for analyzing multiancestry genomic studies across multiple biobanks.
The researchers built upon a method developed by Vanderbilt University Medical Center (VUMC) scientists to identify disease-associated genes within a multiancestry environment, using data from the Global Biobank Meta-analysis Initiative.
VUMC's Eric Gamazon said the framework "will have broad utility for interpreting genetic associations obtained from genome-wide association studies, improves our ability to identify disease-associated genes—including for rare diseases—and may enhance drug discovery efforts by leveraging genetic information linked to extensive phenomic data."
Gamazon said the approach also yields insights on the methodological challenges of ancestry imbalance in current genomic datasets, and addresses the limitations of transcriptome-wide association studies.
From Vanderbilt University Medical Center
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