Arizona State University (ASU) researchers have developed DeNovoGear, software that uses statistical probabilities to help identify mutations and more accurately pinpoint their source and their possible significance for health.
The researchers say improvements in the accuracy of mutation identification and validation could impact the diagnosis and treatment of mutation-related diseases. DeNovoGear also can be applied to cancer research, in which tumor tissues are genetically compared to normal tissue.
"We are developing methods to allow researchers to make those types of analyses, using advanced, probabilistic methods," says ASU professor Reed Cartwright.
The new method uses a probabilistic algorithm to evaluate the likelihood of mutation at each site in the genome, comparing it with actual sequence data. The technique also will help ongoing efforts to better understand which mutations contribute to sporadic disease or cancer in individuals, the distribution of mutations, and their characteristics across mutations.
"Our goal is to develop software that will allow researchers and clinicians to estimate a range of mutation types, faster, more accurately, and cheaper," Cartwright says.
From Arizona State University
View Full Article
Abstracts Copyright © 2013 Information Inc., Bethesda, Maryland, USA
No entries found