Are you using CNVpytor—a Python extension of CNVnator—to detect copy number variations (CNVs) and alterations (CNAs) in your cancer research?

NCI Informatics Technology for Cancer Research (ITCR) investigators developed the CNVpytor track, a new feature with igv.js (an embeddable interactive genome visualization component of the Integrative Genomics Viewer). The CNVpytor track allows you to use pytor files and other whole-genome variant files to visualize read depth and B-allele frequency information in real-time. You can embed this tool into HTML pages and Jupyter Notebooks to easily access and visualize genomic data, making it easier for you to analyze and interpret complex omics data.

Corresponding author, Dr. Alexej Abyzov, noted, “CNVpytor simplifies the analysis and inspection of CNVs across the genome like never before. Most importantly, both CNVpytor and its corresponding track in igv.js leverage standard VCF files containing variant data to detect and visualize CNAs. This feature will be crucial for future cancer genomic studies, especially with the rapid growth of whole-genome sequencing data.”