RT Journal
A1 Dzamba, Misko
A1 Ramani, Arun K.
A1 Buczkowicz, Pawel
A1 Jiang, Yue
A1 Yu, Man
A1 Hawkins, Cynthia
A1 Brudno, Michael
T1 Identification of complex genomic rearrangements in cancers using CouGaR
JF Genome Research 
JO Genome Research 
YR 2017 
FD January 01 
VO 27 
IS 1 
SP 107 
OP 117 
DO 10.1101/gr.211201.116 
UL http://genome.cshlp.org/content/27/1/107.abstract 
AB The genomic alterations associated with cancers are numerous and varied, involving both isolated and large-scale complex genomic rearrangements (CGRs). Although the underlying mechanisms are not well understood, CGRs have been implicated in tumorigenesis. Here, we introduce CouGaR, a novel method for characterizing the genomic structure of amplified CGRs, leveraging both depth of coverage (DOC) and discordant pair-end mapping techniques. We applied our method to whole-genome sequencing (WGS) samples from The Cancer Genome Atlas and identify amplified CGRs in at least 5.2% (10+ copies) to 17.8% (6+ copies) of the samples. Furthermore, ∼95% of these amplified CGRs contain genes previously implicated in tumorigenesis, indicating the importance and widespread occurrence of CGRs in cancers. Additionally, CouGaR identified the occurrence of ‘chromoplexy’ in nearly 63% of all prostate cancer samples and 30% of all bladder cancer samples. To further validate the accuracy of our method, we experimentally tested 17 predicted fusions in two pediatric glioma samples and validated 15 of these (88%) with precise resolution of the breakpoints via qPCR experiments and Sanger sequencing, with nearly perfect copy count concordance. Additionally, to further help display and understand the structure of CGRs, we have implemented CouGaR-viz, a generic stand-alone tool for visualization of the copy count of regions, breakpoints, and relevant genes.