Researchers, including Rahul Singh (left), in the Daniell lab’s greenhouse where the production of clinical grade transgenic lettuce occurs.
(Image: Henry Daniell)
Individual genes have the ability to influence more than one trait or characteristic. But this feature is often discovered through a type of analysis called pleiotropy, which requires merging a patient’s data from electronic health records at many different places—a challenge given privacy stipulations. A team at the Perelman School of Medicine created a new method that could make pleiotropy easier to perform and more widely used, called Sum-Share. The statistical model pulls summary-level information from many different sites to generate significant insights.
In a test of the method, published in Nature Communications, Sum-Share’s developers detected more than 1,700 DNA-level variations that could be associated with five different cardiovascular conditions. Using patient-specific information from just one site, which is the current norm, would have found just one variation.
This story is by Frank Otto. Read more at Penn Medicine News.
From Penn Medicine News
Researchers, including Rahul Singh (left), in the Daniell lab’s greenhouse where the production of clinical grade transgenic lettuce occurs.
(Image: Henry Daniell)
Image: Sciepro/Science Photo Library via Getty Images
In honor of Valentine's Day, and as a way of fostering community in her Shakespeare in Love course, Becky Friedman took her students to the University Club for lunch one class period. They talked about the movie "Shakespeare in Love," as part of a broader conversation on how Shakespeare's works are adapted.
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