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CICERO
CGC
Data Resource:  CGC
Point of Contact:  
Jinghui Zhang,  
Project

About This Dataset
To discover driver fusions beyond canonical exon-to-exon chimeric transcripts, we developed CICERO, a local assembly-based algorithm that integrates RNA-seq read support with extensive annotation for candidate ranking. CICERO outperforms commonly used methods, achieving a 95% detection rate for 184 independently validated driver fusions including internal tandem duplications and other non-canonical events in 170 pediatric cancer transcriptomes.
Core Data Elements
Additional Data Elements
DATA REPOSITORY
Grant Information
P01CA096832
Core B: Bioinformatics and Biostatistics Core
P30CA021765
Bioinformatics and Biotechnology Shared Resource Core
R01CA216391
Discovery of Somatic Noncoding Variants that Serve as Drivers in Pediatric Cancers
Published In
https://doi.org/10.1186/s13059-020-02043-x