Work

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

Year: 2016

Type: preprint

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 [email protected]

Source: bioRxiv (Cold Spring Harbor Laboratory)

DOI: 10.1101/049536

Authors: Ryan L. Collins, Matthew R. Stone, Harrison Brand, Joseph T. Glessner, Michael E. Talkowski

Institutions: Massachusetts General Hospital, Harvard University, Broad Institute

Language: English

Topic: Genomic variations and chromosomal abnormalities

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: Simons Foundation, March of Dimes Foundation, Simons Foundation Autism Research Initiative, National Institutes of Health

Awards: G1726822968, G9000105729, G9000157619