Journal
NUCLEIC ACIDS RESEARCH
Volume 42, Issue 12, Pages -Publisher
OXFORD UNIV PRESS
DOI: 10.1093/nar/gku345
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Funding
- Department of Systems Biology at Columbia University
- JP Sulzberger Columbia Genome Center
- National Institutes of Health (NIH)
- National Heart, Lung and Blood Institute (NHLBI)
- Pediatric Cardiac Genomics Consortium [U01-HL098147, U01-HL098153, U01-HL098163, U01-HL098123, U01-HL098162]
- Harvard Medical School
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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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