Canvas: versatile and scalable detection of copy number variants
Open accessPublished version of a preprint
Abstract
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 https://github.com/Illumina/canvas. Contact: eroller@illumina.com Supplementary information: Supplementary data are available at Bioinformatics online.
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Genome sequencing has the potential to detect a wide variety of variant types, including single-nucleotide variants and indels, copy number variants, repeat expansions, and pathogenic nonprotein-coding variation that is missed by other NGS approaches.
“Genome sequencing has the potential to detect a wide variety of variant types, including single‐nucleotide variants and indels (out‐performing exome sequencing in protein‐coding regions), copy number variants (CNV),4 repeat expansions,5 and detection of pathogenic nonprotein‐coding variation that is missed by other NGS approaches.”
From Genome sequencing in persistently unsolved white matter disorders (2020) · cites this paper as [4]
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- Authors
- Roller, E., Ivakhno, S., Lee, S., Royce, T., & Tanner, S.
- Affiliations
- Illumina (United States) (US)
- Illumina (United Kingdom) (GB)
- 3 Ashion Analytics, Phoenix, AZ, USA
- Corresponding author
- Roller, Eric
- ORCID
- Tanner, Stephen
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-03-24
- Volume
- 32
- Issue
- 15
- Pages
- 2375-2377
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2952509678
- Cited by
- 206
- References
- 0
- Citations by year
- 2026: 13 · 2025: 23 · 2024: 36 · 2023: 24 · 2022: 23 · 2021: 30 · 2020: 22 · 2019: 14 · 2018: 14 · 2017: 4 · 2016: 2
- FWCI
- 9.14
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Bioinformatics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- copy number variation, Canva, variant calling, tumor ploidy, tumor purity, tumor heterogeneity, exome sequencing, whole genome sequencing, cancer genomics, polyclonality
- MeSH terms
- Algorithms, Humans, Neoplasms, Software, DNA Copy Number Variations, Exome
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