General Information
| Description | Versatile and scalable detection of copy number variants |
| Homepage | https://github.com/Illumina/canvas |
Publications
Canvas: versatile and scalable detection of copy number variants
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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