Canvas: versatile and scalable detection of copy number variants

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.\n\nResults: 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.\n\nAvailability: Canvas is distributed under an open source license and can be downloaded from https://github.com/Illumina/canvas.\n\nContact: eroller@illumina.com\n\nSupplementary information: Supplementary data are available at Bioinformatics online.