# Canvas: versatile and scalable detection of copy number variants

## TL;DR

Canvas is a new tool for detecting copy number changes in sequencing data, offering scalability and versatility for cancer genomics.

## Contribution

Canvas introduces a scalable and versatile tool for copy number variant detection with integrated inference of cancer ploidy and purity.

## Key findings

- Canvas can process diverse sequencing experiments including tumor-normal and single-sample studies.
- The tool efficiently scales to thousands of samples and integrates into existing pipelines.
- Canvas infers genome-wide parameters like cancer ploidy, purity, and heterogeneity.

## Abstract

Motivation: Increased throughput and diverse experimental designs of large-scale sequencing studies necessi-tate versatile, scalable and robust variant calling tools. In particular, identification of copy number changes re-mains a challenging task due to their complexity, susceptibility to sequencing biases, variation in coverage data and dependence on genome-wide sample properties, such as tumor polyploidy or polyclonality in cancer samples.

Results: We have developed a new tool, Canvas, for identification of copy number changes from diverse se-quencing experiments including whole-genome matched tumor-normal and single-sample normal re-sequencing, as well as whole-exome matched and unmatched tumor-normal studies. In addition to variant calling, Canvas infers genome-wide parameters such as cancer ploidy, purity and heterogeneity. It provides fast and simple to execute workflows that can scale to thousands of samples and can be easily incorporated into existing variant calling pipelines.

Availability: Canvas is distributed under an open source license and can be downloaded from https://github.com/Illumina/canvas.

Contact: eroller@illumina.com

Supplementary information: Supplementary data are available at Bioinformatics online.