Cancer cells often have mutations in their DNA that can give scientists clues about how the cancer started or which treatment may be most effective. Finding these mutations can be difficult, but a new method may offer more complete, comprehensive results.
A team of researchers has developed a new framework that can combine three existing methods of finding these large mutations — or structural variants — into a single, more complete picture.
Feng Yue, assistant professor of biochemistry and molecular biology at Penn State College of Medicine, said the new method — published today (Sept. 10) in Nature Genetics — could help researchers find new structural variations within cancer cell DNA and learn more about how those cancers begin.
“We were able to design and use this computational framework to connect the three methods together, to get the most comprehensive view of the genome,” Yue said. “Each method by itself can only review a portion of the structural variations, but when you integrate the results of the three different methods, you can get the most comprehensive view of the cancer genome.”
Structural variants are large mutations in DNA that can result in cancer causing genes being turned on. For
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