Tracking down gene fusions
September 2020
by DDN Staff  |  Email the author

SHARING OPTIONS:

STANFORD, Calif.—Stanford University researchers are looking to track down gene fusions that can drive cancers proliferation and uncover fusions in individual tumor cells. To do that, they have turned to a single-cell statistical modeling method, and a member of the team presented their method during the Bioinformatics and Artificial Intelligence minisymposium at the AACR Virtual Annual Meeting II in June.
 
In the session, Dr. Roozbeh Dehghannasin, a postdoctoral researcher at the Stanford School of Medicine, described the statistical model designed to detect gene fusions at a single-cell level, explaining that many gene fusions are known to drive cancer development, but limitations in current technologies have hindered fully understanding their functions.
 
The model developed by the Stanford team, which is called SICILIAN, can be integrated into conventional splice alignment tools to detect different RNA variants, such as splice junctions, gene fusions and circular RNA.
 
Dehghannasin said that the team found that SICILIAN detected gene fusions with similar sensitivity but greater specificity than an existing gene fusion detection tool called STAR-Fusion.
Code: E082011

Back
 
CONTACT US
DDNEWS
1000 N West Street, Suite 1200,
Wilmington, Delaware, 19801
Ph: 888-781-0328 |  Fax: 705-528-0270
 
© Copyright 2020 Old River Publications LLC. All righs reserved.  |  Web site managed and designed by OffWhite.