Communications of the ACM
Researchers Highlight More Equitable Way to Analyze DNA Data from Understudied Groups
Recent studies have shown that Genome-wide association (GWA) results estimated from self-identified European individuals are not transferable to non-European individuals. Because of this, the insights from the datasets are largely biased toward sampling i
Credit: News from Brown
Brown University scientists led a multi-institutional team in employing new DNA analysis methods to better understand genetic conditions' impact across different populations.
The researchers applied enrichment analysis to resolve underlying bias and underrepresentation in the genome-wide association (GWA) framework.
"We show that data viewed only through a very specific GWA lens may look disparate and irreconcilable," said Brown's Sohini Ramachandran. "Yet, viewed in a more equitable way, with a more expansive methodology, it becomes biologically unified, interpretable, and, importantly, actionable."
The researchers highlighted strong associations of trait determinants while reviewing 25 traits in 600,000-plus individuals from seven human ancestries.
Brown's Lorin Crawford said this method can help to provide more targeted therapies to underrepresented ancestry groups.
From News from Brown
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Abstracts Copyright © 2022 SmithBucklin, Washington, DC, USA
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