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Updated: Apr 30, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
CANOES: detecting rare copy number variants from whole exome sequencing data
Daniel Backenroth1, Jason Homsy2, Laura R Murillo3
1Departments of Systems Biology and Biomedical Informatics, Columbia University Medical Center, New York, NY 10032, USA JP Sulzberger Columbia Genome Center, Columbia University Medical Center, New York, NY 10032, USA.
Abstract:
We 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.
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