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DECoN: A Detection and Visualization Tool for Exonic Copy Number Variants

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Variant Calling

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2493))

Abstract

Detection of copy number variants from targeted sequencing, including whole-exome sequencing, can be particularly difficult since the break points of the CNV are not always captured. Here we describe DECoN, a software tool which uses changes in read depth to identify CNVs that affect whole exons. It is optimized for clinical use and allows for interactive visualization of CNVs identified.

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References

  1. Plagnol V, Curtis J, Epstein M, Mok KY, Stebbings E, Grigoriadou S, Wood NW, Hambleton S, Burns SO, Thrasher AJ, Kumararatne D (2012) A robust model for read count data in exome sequencing experiments and implications for copy number variant calling. Bioinformatics 28(21):2747–2754

    Article  CAS  Google Scholar 

  2. Fromer M, Moran JL, Chambert K, Banks E, Bergen SE, Ruderfer DM, Handsaker RE, McCarroll SA, O’Donovan MC, Owen MJ, Kirov G (2012) Discovery and statistical genotyping of copy-number variation from whole-exome sequencing depth. Am J Hum Genet 91(4):597–607

    Article  CAS  Google Scholar 

  3. de Ligt J, Boone PM, Pfundt R, Vissers LE, Richmond T, Geoghegan J, O'Moore K, de Leeuw N, Shaw C, Brunner HG, Lupski JR (2013) Detection of clinically relevant copy number variants with whole-exome sequencing. Hum Mutat 34(10):1439–1448

    Article  Google Scholar 

  4. Li J, Lupat R, Amarasinghe KC, Thompson ER, Doyle MA, Ryland GL, Tothill RW, Halgamuge SK, Campbell IG, Gorringe KL (2012) CONTRA: copy number analysis for targeted resequencing. Bioinformatics 28(10):1307–1313

    Article  Google Scholar 

  5. Krumm N, Sudmant PH, Ko A, O'Roak BJ, Malig M, Coe BP, Quinlan AR, Nickerson DA, Eichler EE, NHLBI Exome Sequencing Project (2012) Copy number variation detection and genotyping from exome sequence data. Genome Res 22(8):1525–1532

    Article  CAS  Google Scholar 

  6. Amarasinghe KC, Li J, Halgamuge SK (2013) CoNVEX: copy number variation estimation in exome sequencing data using HMM. BMC Bioinformatics 14(2):1–9

    Google Scholar 

  7. Johansson LF, van Dijk F, de Boer EN, van Dijk-Bos KK, Jongbloed JD, van der Hout AH, Westers H, Sinke RJ, Swertz MA, Sijmons RH, Sikkema-Raddatz B (2016) CoNVaDING: single exon variation detection in targeted NGS data. Hum Mutat 37(5):457–464

    Article  CAS  Google Scholar 

  8. Chiang T, Liu X, Wu TJ, Hu J, Sedlazeck FJ, White S, Schaid D, de Andrade M, Jarvik GP, Crosslin D, Stanaway I (2019) Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel. Genet Med 21(9):2135–2144

    Article  Google Scholar 

  9. Jiang Y, Wang R, Urrutia E, Anastopoulos IN, Nathanson KL, Zhang NR (2018) CODEX2: full-spectrum copy number variation detection by high-throughput DNA sequencing. Genome Biol 19(1):1–13

    Article  Google Scholar 

  10. Kang Y, Nam SH, Park KS, Kim Y, Kim JW, Lee E, Ko JM, Lee KA, Park I (2018) DeviCNV: detection and visualization of exon-level copy number variants in targeted next-generation sequencing data. BMC Bioinformatics 19(1):1–13

    Article  Google Scholar 

  11. Fowler A, Mahamdallie S, Ruark E, Seal S, Ramsay E, Clarke M, Uddin I, Wylie H, Strydom A, Lunter G, Rahman N (2016) Accurate clinical detection of exon copy number variants in a targeted NGS panel using DECoN. Wellcome open research 1:20

    Article  Google Scholar 

  12. Team, R.C. (2013) R: A language and environment for statistical computing

    Google Scholar 

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Correspondence to Anna Fowler .

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© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Fowler, A. (2022). DECoN: A Detection and Visualization Tool for Exonic Copy Number Variants. In: Ng, C., Piscuoglio, S. (eds) Variant Calling. Methods in Molecular Biology, vol 2493. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2293-3_6

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  • DOI: https://doi.org/10.1007/978-1-0716-2293-3_6

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2292-6

  • Online ISBN: 978-1-0716-2293-3

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