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“An extremely interesting time to be a geneticist”: Using big data to identify rare diseases

With cheaper, faster genetic sequencing, researchers are able to pinpoint rare gene variants that may be contributing to disease.

But to find "the actual, causal rare variant contributing to the trait is like looking for a needle in a haystack," says Stephen Montgomery, PhD, in the video above.

Montgomery and his team have plans to boost the efficacy of using genome sequencing to identify rare diseases by incorporating all of the information from genes that are actually turned on — using RNA in addition to its parent DNA to make that needle really stand out.

Eventually, Montgomery hopes to mix in even more information including details about individual lifestyles, environmental exposures and family histories to glean further insights into the origins of rare disease. His team received a 2014 Big Data for Human Health Seed Grant to support the work.

"We're going to be able to answer very quickly questions about how the genome is influencing our lives and then we're also going to be able to treat (these conditions)," Montgomery says. "This is an extremely interesting time to be a geneticist and these large data sets are just empowering a large number of discoveries."

This effort is part of Stanford Medicine’s Biomedical Data Science Initiative (BDSI), which strives to make powerful transformations in human health and scientific discovery by fostering innovative collaborations among medical researchers, computer scientists, statisticians and physicians. Work being done in this area is the focus of Stanford’s Big Data in Biomedicine conference, which kicks off tomorrow morning.

Previously: Collecting buried biomedical treasure – using big data, All data – big and small – informs large-scale neuroscience project, Registration for Big Data in Biomedicine conference now open, Parent details practical ways to get care and support for your child's rare disease, New search engine designed to help physicians and the public in diagnosing rare diseases and Big data used to help identify patients at risk of deadly high-cholesterol disorder

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