New Computational Approach Helps Genomic Researchers Pinpoint Disease-Causing Genetic Variants

The program tracks variants reported by GWASs, then cross-references those of interest against a comprehensive variant catalog generated through robust “next-generation” sequencing in order to pinpoint causal variants.

To confirm the validity of the approach the investigators applied it to the GWAS signals of five human traits for which the causal variants were already known. Results detailed in the August 30, 2012, issue of the American Journal of Human Genetics, revealed that they had successfully placed the known causal variants among the top ten candidates in the majority of the cases. Further application of this method to additional GWASs, including those of hepatitis C virus treatment response, plasma levels of clotting factors, and late-onset Alzheimer's disease, has led to the identification of a number of promising candidate causal variants.

“This approach helps to intergrade the large body of data available in GWASs with the rapidly accumulating sequence data,” said senior author Dr. David B. Goldstein, professor of molecular genetics and microbiology at Duke University.

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Duke University
Roswell Park Cancer Institute