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CNView: a visualization and annotation tool for copy number variation from whole-genome sequencing

View ORCID ProfileRyan L. Collins, Matthew R. Stone, Harrison Brand, Joseph T. Glessner, Michael E. Talkowski
doi: https://doi.org/10.1101/049536
Ryan L. Collins
1Psychiatric and Neurodevelopmental Genetics Unit and Molecular Neurogenetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA,
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  • ORCID record for Ryan L. Collins
Matthew R. Stone
1Psychiatric and Neurodevelopmental Genetics Unit and Molecular Neurogenetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA,
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Harrison Brand
1Psychiatric and Neurodevelopmental Genetics Unit and Molecular Neurogenetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA,
2Department of Neurology, Harvard Medical School, Boston, MA 02114, USA,
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Joseph T. Glessner
1Psychiatric and Neurodevelopmental Genetics Unit and Molecular Neurogenetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA,
2Department of Neurology, Harvard Medical School, Boston, MA 02114, USA,
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Michael E. Talkowski
1Psychiatric and Neurodevelopmental Genetics Unit and Molecular Neurogenetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA,
2Department of Neurology, Harvard Medical School, Boston, MA 02114, USA,
3Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02141, USA
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Abstract

Summary Copy number variation (CNV) is a major component of structural differences between individual genomes. The recent emergence of population-scale whole-genome sequencing (WGS) datasets has enabled genome-wide CNV delineation. However, molecular validation at this scale is impractical, so visualization is an invaluable preliminary screening approach when evaluating CNVs. Standardized tools for visualization of CNVs in large WGS datasets are therefore in wide demand.

Methods & Results To address this demand, we developed a software tool, CNView, for normalized visualization, statistical scoring, and annotation of CNVs from population-scale WGS datasets. CNView surmounts challenges of sequencing depth variability between individual libraries by locally adapting to cohort-wide variance in sequencing uniformity at any locus. Importantly, CNView is broadly extensible to any reference genome assembly and most current WGS data types.

Availability and Implementation CNView is written in R, is supported on OS X, MS Windows, and Linux, and is freely distributed under the MIT license. Source code and documentation are available from https://github.com/RCollins13/CNView

Contact talkowski{at}chgr.mgh.harvard.edu

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted April 20, 2016.
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CNView: a visualization and annotation tool for copy number variation from whole-genome sequencing
Ryan L. Collins, Matthew R. Stone, Harrison Brand, Joseph T. Glessner, Michael E. Talkowski
bioRxiv 049536; doi: https://doi.org/10.1101/049536
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CNView: a visualization and annotation tool for copy number variation from whole-genome sequencing
Ryan L. Collins, Matthew R. Stone, Harrison Brand, Joseph T. Glessner, Michael E. Talkowski
bioRxiv 049536; doi: https://doi.org/10.1101/049536

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