Canvas: versatile and scalable detection of copy number variants

Bioinformatics. 2016 Aug 1;32(15):2375-7. doi: 10.1093/bioinformatics/btw163. Epub 2016 Mar 24.


Motivation: Versatile and efficient variant calling tools are needed to analyze large scale sequencing datasets. In particular, identification of copy number changes remains 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 sequencing 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 easy-to-run workflows that can scale to thousands of samples and can be easily incorporated into variant calling pipelines.

Availability and implementation: Canvas is distributed under an open source license and can be downloaded from


Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

  • Algorithms
  • DNA Copy Number Variations*
  • Exome
  • Humans
  • Neoplasms*
  • Software*