CNVScope: Visually Exploring Copy Number Aberrations in Cancer Genomes. (November 2019)

• Record Type: Journal Article
• Authors: Dalgleish, James LT; Wang, Yonghong; Zhu, Jack; Meltzer, Paul S
• Is Part Of: Cancer informatics. Volume 18(2019)
• Publication Date: 2019-11
• Subjects: copy number -- cancer -- CNV -- CNA -- copy number variation -- visualization -- R -- shiny; Bioinformatics -- Periodicals; Biology -- Data processing -- Periodicals; Cancer -- Periodicals; Cancer -- Research -- Periodicals; Computational biology -- Periodicals; 570.285
• DOI: 10.1177/1176935119890290
• Languages: English
• ISSNs: 1176-9351

Abstract

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 athttp://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).