CNVScope: Visually Exploring Copy Number Aberrations in Cancer Genomes

Motivation: DNA copy number (CN) data are a fast-growing source of information used in basic and translational cancer research. Most CN segmentation data are presented without regard to the relationship between chromosomal regions. We offer both a toolkit to help scientists without programming exper...

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Bibliographic Details
Published in:Cancer Informatics 2019, Vol.18, p.1176935119890290-1176935119890290
Main Authors: Dalgleish, James LT, Wang, Yonghong, Zhu, Jack, Meltzer, Paul S
Format: Article
Language:English
Subjects:
Cancer
Cell cycle
Censuses
Chromosomes
Copy number
Datasets
Deoxyribonucleic acid
DNA
Gene loci
Genomes
Genomics
Macintosh personal computers
Multiprocessing
Neuroblastoma
Regression analysis
Segmentation
Software or Database Review
Toolkits
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Summary:Motivation: DNA copy number (CN) data are a fast-growing source of information used in basic and translational cancer research. Most CN segmentation data are presented without regard to the relationship between chromosomal regions. We offer both a toolkit to help scientists without programming experience visually explore the CN interactome and a package that constructs CN interactomes from publicly available data sets. Results: The CNVScope visualization, based on a publicly available neuroblastoma CN data set, clearly displays a distinct CN interaction in the region of the MYCN, a canonical frequent amplicon target in this cancer. Exploration of the data rapidly identified cis and trans events, including a strong anticorrelation between 11q loss and17q gain with the region of 11q loss bounded by the cell cycle regulator CCND1. Availability: The shiny application is readily available for use at http://cnvscope.nci.nih.gov/, and the package can be downloaded from CRAN (https://cran.r-project.org/package=CNVScope), where help pages and vignettes are located. A newer version is available on the GitHub site (https://github.com/jamesdalg/CNVScope/), which features an animated tutorial. The CNVScope package can be locally installed using instructions on the GitHub site for Windows and Macintosh systems. This CN analysis package also runs on a linux high-performance computing cluster, with options for multinode and multiprocessor analysis of CN variant data. The shiny application can be started using a single command (which will automatically install the public data package).
ISSN:1176-9351
1176-9351
DOI:10.1177/1176935119890290