Genome-wide analysis and visualization of copy number with CNVpytor in igv.js

Author:

Panda Arijit1ORCID,Suvakov Milovan1ORCID,Thorvaldsdottir Helga2,Mesirov Jill P34,Robinson James T3,Abyzov Alexej1ORCID

Affiliation:

1. Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic , Rochester, MN 55905, United States

2. Broad Institute of MIT and Harvard , Cambridge, MA 02142, United States

3. Department of Medicine, University of California San Diego , La Jolla, CA 92093, United States

4. Moores Cancer Center, University of California San Diego , La Jolla, CA 92037, United States

Abstract

Abstract Summary Copy number variation (CNV) and alteration (CNA) analysis is a crucial component in many genomic studies and its applications span from basic research to clinic diagnostics and personalized medicine. CNVpytor is a tool featuring a read depth-based caller and combined read depth and B-allele frequency (BAF) based 2D caller to find CNVs and CNAs. The tool stores processed intermediate data and CNV/CNA calls in a compact HDF5 file—pytor file. Here, we describe a new track in igv.js that utilizes pytor and whole genome variant files as input for on-the-fly read depth and BAF visualization, CNV/CNA calling and analysis. Embedding into HTML pages and Jupiter Notebooks enables convenient remote data access and visualization simplifying interpretation and analysis of omics data. Availability and implementation The CNVpytor track is integrated with igv.js and available at https://github.com/igvteam/igv.js. The documentation is available at https://github.com/igvteam/igv.js/wiki/cnvpytor. Usage can be tested in the IGV-Web app at https://igv.org/app and also on https://github.com/abyzovlab/CNVpytor.

Funder

National Cancer Institute

National Institute of Neurological Disorders and Stroke

Individualized Medicine at Mayo Clinic

Publisher

Oxford University Press (OUP)

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