Researchers depict new statistical algorithm to identify genetic variations for common diseases

July 03, 2017

According to Schork, the key to identifying the genetic components of these complex diseases is not to focus on finding single common genetic signatures that people share-but rather to identify whole collections of rare genetic signatures, any one of which may indicate a predisposition toward a disease.

The situation is analogous to asking how someone from outside New York City could get to Times Square in Manhattan. There is no single answer to that question because there are any number of approaches and modes of transportation-from New Jersey, from Brooklyn, from Wall Street, or from the Bronx, and via plane, bus, train, taxi, ferry, bridge, tunnel, subway, or sidewalk.

Regardless of where they start or how they get there, it is possible for many people to wind up at exactly the same spot, though, and Schork says the same is true for many human diseases. There may not be one single genetic marker for many diseases, but multiple markers involving any number of genes, even among people who share the same disease.

Finding these rare signatures requires a great deal more scientific sleuthing, says Schork, and in their Nature Review Genetics article Schork and his colleagues suggest a new approach to discover all the possible combinations.

This approach will require collaborations between mathematicians and computer scientists, who have the skills needed to tease out these elusive genetic markers, and biologists who can shed light on what those genes do.

"Mathematics, statistics, and fancy computers alone won't do it," Schork says. "A much more integrative approach has to occur in order to make sense of DNA sequence data."

Source: Scripps Research Institute