The medical community has increasingly turned to genetic information to understand, treat and prevent disease in humans.
Researchers at the University of Chicago say a computer nicknamed “Beagle” is able to analyze data on 240 complete genomes in just two days, making it one of the most advanced health-related supercomputers on Earth.
Previously, it could take researchers several months in order to analyze information from just one genome. The results from the study, published in the journal Bioinformatics, could dramatically change the way in which doctors and scientists understand the genetic causes of diseases, according to Dr. Elizabeth McNally, the AJ Carlson Professor of Medicine and Human Genetics and director of the Cardiovascular Genetics clinic at the University of Chicago Medicine.
Researchers tested Beagle using raw sequencing data from a sample of 61 human genomes and analyzed it on the computer. Researchers found that not only was Beagle able to analyze the data quickly, but more accurately as well. Researchers explain that previously, clinical geneticists have turned to exome sequencing which looks at less than 2 percent of the genome. While researchers note that 85 percent of disease causing mutations tend to be isolated to this 2 percent region, the other 15 percent stem from non-coded regions – regions that Beagle is able to examine and analyze.
By studying genomes, the set of genes present in a cell or multicellular organism, researchers are able to learn more about inherited, genetic disorders. “By paying close attention to family members with genes that place them at increased risk, but who do not yet show signs of disease, we can investigate early phases of a disorder. In this setting, each patient is a big-data problem,” Dr. McNally explains.
Dr. McNally goes on to explain that the findings from the study have benefits that can be applied at the Cardiovascular Genetics clinic immediately.
Beagle’s efficiency will increase the speed in which genomes are analyzed, produce more meaningful data by analyzing the entire genome, and is a significantly less expensive.