CANOES: detecting rare copy number variants from whole exome sequencing data

DSpace/Manakin Repository

CANOES: detecting rare copy number variants from whole exome sequencing data

Citable link to this page

 

 
Title: CANOES: detecting rare copy number variants from whole exome sequencing data
Author: Backenroth, Daniel; Homsy, Jason; Murillo, Laura R.; Glessner, Joe; Lin, Edwin; Brueckner, Martina; Lifton, Richard; Goldmuntz, Elizabeth; Chung, Wendy K.; Shen, Yufeng

Note: Order does not necessarily reflect citation order of authors.

Citation: Backenroth, 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.
Full Text & Related Files:
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.
Published Version: doi:10.1093/nar/gku345
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4081054/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:12717468
Downloads of this work:

Show full Dublin Core record

This item appears in the following Collection(s)

 
 

Search DASH


Advanced Search
 
 

Submitters