Backenroth, DanielHomsy, JasonMurillo, Laura R.Glessner, JoeLin, EdwinBrueckner, MartinaLifton, RichardGoldmuntz, ElizabethChung, Wendy K.Shen, Yufeng2014-08-132014Backenroth, Daniel, Jason Homsy, Laura R. Murillo, Joe Glessner, Edwin Lin, Martina Brueckner, Richard Lifton, Elizabeth Goldmuntz, Wendy K. Chung, and Yufeng Shen. 2014. “CANOES: detecting rare copy number variants from whole exome sequencing data.” Nucleic Acids Research 42 (12): e97. doi:10.1093/nar/gku345. http://dx.doi.org/10.1093/nar/gku345.0305-1048http://nrs.harvard.edu/urn-3:HUL.InstRepos:12717468We present CANOES, an algorithm for the detection of rare copy number variants from exome sequencing data. CANOES models read counts using a negative binomial distribution and estimates variance of the read counts using a regression-based approach based on selected reference samples in a given dataset. We test CANOES on a family-based exome sequencing dataset, and show that its sensitivity and specificity is comparable to that of XHMM. Moreover, the method is complementary to Gaussian approximation-based methods (e.g. XHMM or CoNIFER). When CANOES is used in combination with these methods, it will be possible to produce high accuracy calls, as demonstrated by a much reduced and more realistic de novo rate in results from trio data.en-USCANOES: detecting rare copy number variants from whole exome sequencing dataJournal Article2014-08-1310.1093/nar/gku345