Abstract
Copy number variations have been linked to numerous genetic diseases including cancer, Parkinson’s disease, pancreatitis, and lupus. While current best practices for CNV detection often require using microarrays for detecting large CNVs or multiplex ligation-dependent probe amplification (MLPA) for gene-sized CNVs, new methods have been developed with the goal of replacing both of these specialized assays with bioinformatic analysis applied to next-generation sequencing (NGS) data. Because NGS is already used by clinical labs to detect small coding variants, this approach reduces associated costs, resources, and analysis time. This chapter provides an overview of the various approaches to CNV detection via NGS data, and examines VS-CNV, a commercial tool developed by Golden Helix, which provides robust CNV calling capabilities for both gene panel and exome data.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chance PF, Pleasure D (1993) Charcot-Marie-tooth syndrome. Arch Neurol 50:1180–1184
Conrad DF, Pinto D, Redon R et al (2010) Origins and functional impact of copy number variation in the human genome. Nature 464:704
Redon R, Ishikawa S, Fitch KR et al (2006) Global variation in copy number in the human genome. Nature 444:444–454
Lupski JR (2007) Genomic rearrangements and sporadic disease. Nat Genet 39:S43–S47
Stankiewicz P, Lupski JR (2010) Structural variation in the human genome and its role in disease. Annu Rev Med 61:437–455
Fromer M, Moran JL, Chambert K et al (2012) Discovery and statistical genotyping of copy-number variation from whole-exome sequencing depth. Am J Hum Genet 91:597–607
Yau C (2013) OncoSNP-SEQ: a statistical approach for the identification of somatic copy number alterations from next-generation sequencing of cancer genomes. Bioinformatics 29(19):2482–2484
Boeva V, Popova T, Bleakley K et al (2012) Control-FREEC: a tool for assessing copy number; allelic content using next-generation sequencing data. Bioinformatics 28(3):423–425
Mayrhofer M, DiLorenzo S, Isaksson A (2013) Patchwork: allele-specific copy number analysis of whole-genome sequenced tumor tissue. Genome Biol 14(3):1
Miller CA, Hampton O, Coarfa C et al (2011) ReadDepth: a parallel R package for detecting copy number alterations from short sequencing reads. PLoS One 6(1):e16327
Packer JS, Maxwell EK, O’Dushlaine C et al (2016) CLAMMS: a scalable algorithm for calling common and rare copy number variants from exome sequencing data. Bioinformatics 32(1):133–135
Jiang Y, Oldridge DA, Diskin SJ et al (2015) CODEX: a normalization and copy number variation detection method for whole exome sequencing. Nucleic Acids Res 43(6):e39
Krumm N, Sudmant PH, Ko A et al (2012) Copy number variation detection and genotyping from exome sequence data. Genome Res 22(8):1525–1532
Johansson LF, Dijk F, Boer EN et al (2016) CoNVaDING: single exon variation detection in targeted NGS data. Hum Mutat 37(5):457–464
Pugh TJ, Amr SS, Bowser MJ et al (2015) VisCap: inference and visualization of germ-line copy-number variants from targeted clinical sequencing data. Genet Med 18(7):712–719
Talevish E, Shain AH, Botton T et al (2016). CNVkit: Genome-Wide copy number detection and visualization from targeted DNA sequencing. PLoS Computational Biology 12(4):e1004873
Xi R, Luquette J, Hadjipanayis A et al (2010) BIC-seq: a fast algorithm for detection of copy number alterations based on high-throughput sequencing data. Genome Biol 11(1):1
Koller D, Friedman N (2009) Probabilistic graphical models: principles and techniques. MIT Press, Cambridge
Backenroth D, Homsy J, Murillo LR et al (2014) CANOES: detecting rare copy number variants from whole exome sequencing data. Nucleic Acids Res 42(12):e97
Olshen AB, Venkatraman E, Lucito R et al (2004) Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 5(4):557–572
Koboldt DC, Zhang Q, Larson DE et al (2012) VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res 22(3):568–576
Sathirapongsasuti JF, Lee H, Horst BA et al (2011) Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV. Bioinformatics 27(19):2648–2654
Iacocca MA, Wang J, Dron JS et al (2017) Use of next-generation sequencing to detect LDLR gene copy number variation in familial hypercholesterolemia. J Lipid Res 58(11):2202–2209
Zhang J, Baran J, Cros A et al (2011) International cancer genome consortium data portal—a one-stop shop for cancer genomics data. Database (Oxford). https://doi.org/10.1093/database/bar026
Craig DW, Liang W, Venkata Y et al (2013) Interim analysis of the Mmrf Commpass trial, a longitudinal study in multiple myeloma relating clinical outcomes to genomic and immunophenotypic profiles. Blood 122(21):532
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this protocol
Cite this protocol
Fortier, N., Rudy, G., Scherer, A. (2018). Detection of CNVs in NGS Data Using VS-CNV. In: Bickhart, D. (eds) Copy Number Variants. Methods in Molecular Biology, vol 1833. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8666-8_9
Download citation
DOI: https://doi.org/10.1007/978-1-4939-8666-8_9
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-8665-1
Online ISBN: 978-1-4939-8666-8
eBook Packages: Springer Protocols