Researching genetic predisposition to rare diseases comes with challenges as unique as those illnesses.
Data on individuals with such diseases is limited, and so is comparable data from similar healthy individuals. While it is possible to utilize public data sets and create synthetic control groups, several challenges make such methods hard to use.
However, St. Jude Children’s Research Hospital has found a way to circumvent those problems, according to the findings published Wednesday, May 11, in Nature Communications.
A group of scientists at St. Jude created a computational tool called CoCoRV — consistent summary counts-based rare variant burden test — that controls for confounding factors and helps identify genes and genetic variants behind rare diseases.
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