Application of Nexus Copy Number Software for CNV Detection and Analysis

Katayoon Darvishi1

1 Harvard Medical School, Boston, Massachusetts
Publication Name:  Current Protocols in Human Genetics
Unit Number:  Unit 4.14
DOI:  10.1002/0471142905.hg0414s65
Online Posting Date:  April, 2010
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Abstract

Among human structural genomic variation, copy number variants (CNVs) are the most frequently known component, comprised of gains/losses of DNA segments that are generally 1 kb in length or longer. Array‐based comparative genomic hybridization (aCGH) has emerged as a powerful tool for detecting genomic copy number variants (CNVs). With the rapid increase in the density of array technology and with the adaptation of new high‐throughput technology, a reliable and computationally scalable method for accurate mapping of recurring DNA copy number aberrations has become a main focus in research. Here we introduce Nexus Copy Number software, a platform‐independent tool, to analyze the output files of all types of commercial and custom‐made comparative genomic hybridization (CGH) and single‐nucleotide polymorphism (SNP) arrays, such as those manufactured by Affymetrix, Agilent Technologies, Illumina, and Roche NimbleGen. It also supports data generated by various array image‐analysis software tools such as GenePix, ImaGene, and BlueFuse. Curr. Protoc. Hum. Genet. 65:4.14.1‐4.14.28. © 2010 by John Wiley & Sons, Inc.

Keywords: copy number variation; microarrays; comparative genomic hybridization; single‐nucleotide polymorphism; Nexus Copy Number; BioDiscovery

     
 
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Table of Contents

  • Introduction
  • Basic Protocol 1: Software Installation, Project Creation, Data Loading, and Sample Processing
  • Basic Protocol 2: Cytogenetic Review of a Single Sample
  • Basic Protocol 3: Sharing Results with Collaborators
  • Basic Protocol 4: Identification of Regions of Common Aberration in a Population
  • Basic Protocol 5: Identification of Regions of Significant Difference Between Two Sample Populations
  • Basic Protocol 6: Identification of Regions with Predictive Power
  • Basic Protocol 7: Grouping of Samples Based on Common Aberrations
  • Basic Protocol 8: Integration of mRNA and miRNA as well as Methylation Information with Copy Number
  • Basic Protocol 9: Gene List Enrichment Analysis
  • Commentary
  • Literature Cited
  • Figures
     
 
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Materials

Basic Protocol 1: Software Installation, Project Creation, Data Loading, and Sample Processing

  Necessary Resources
  • An internet‐accessible computer with any modern Web browser [with any of the following systems: Windows (Win2k/WinXP/Vista/Windows7, 32/64 bit), Mac OS X, or Linux 32/64 bit]
  • Nexus Copy Number software

Basic Protocol 2: Cytogenetic Review of a Single Sample

  Necessary Resources
  • Processed sample (see protocol 1)
  • An internet‐accessible computer with any modern Web browser [with any of the following systems Windows (Win2k/WinXP/Vista/Windows7, 32/64 bit), Mac OS X, or Linux 32/64 bit]
  • Nexus Copy Number software
NOTE: This protocol assumes that protocol 1 has been successfully completed.

Basic Protocol 3: Sharing Results with Collaborators

  Necessary Resources
  • Processed sample (see protocol 1)
  • An internet‐accessible computer with any modern Web browser [with any of the following systems Windows (Win2k/WinXP/Vista/Windows7, 32/64 bit), Mac OS X, or Linux 32/64 bit]
  • Nexus Copy Number software
NOTE: This protocol assumes that protocol 1 has been successfully completed.

Basic Protocol 4: Identification of Regions of Common Aberration in a Population

  Necessary Resources
  • Processed sample (see protocol 1)
  • An internet‐accessible computer with any modern Web browser [with any of the following systems Windows (Win2k/WinXP/Vista/Windows7, 32/64 bit), Mac OS X, or Linux 32/64 bit]
  • Nexus Copy Number software
NOTE: This protocol assumes that protocol 1 has been successfully completed.

Basic Protocol 5: Identification of Regions of Significant Difference Between Two Sample Populations

  Necessary Resources
  • Processed sample (see protocol 1)
  • An internet‐accessible computer with any modern Web browser [with any of the following systems Windows (Win2k/WinXP/Vista/Windows7, 32/64 bit), Mac OS X, or Linux 32/64 bit]
  • Nexus Copy Number software
NOTE: This protocol assumes that protocol 1 has been successfully completed.

Basic Protocol 6: Identification of Regions with Predictive Power

  Necessary Resources
  • Processed sample (see protocol 1)
  • An internet‐accessible computer with any modern Web browser [with any of the following systems Windows (Win2k/WinXP/Vista/Windows7, 32/64 bit), Mac OS X, or Linux 32/64 bit]
  • Nexus Copy Number software
NOTE: This protocol assumes that protocol 1 has been successfully completed.

Basic Protocol 7: Grouping of Samples Based on Common Aberrations

  Necessary Resources
  • Processed sample (see protocol 1)
  • An internet‐accessible computer with any modern Web browser [with any of the following systems Windows (Win2k/WinXP/Vista/Windows7, 32/64 bit), Mac OS X, or Linux 32/64 bit]
  • Nexus Copy Number software
NOTE: This protocol assumes that protocol 1 has been successfully completed.

Basic Protocol 8: Integration of mRNA and miRNA as well as Methylation Information with Copy Number

  Necessary Resources
  • Processed sample (see protocol 1)
  • An internet‐accessible computer with any modern Web browser [with any of the following systems Windows (Win2k/WinXP/Vista/Windows7, 32/64 bit), Mac OS X, or Linux 32/64 bit]
  • Nexus Copy Number software
NOTE: This protocol assumes that protocol 1 has been successfully completed.

Basic Protocol 9: Gene List Enrichment Analysis

  Necessary Resources
  • Processed sample (see protocol 1)
  • An internet‐accessible computer with any modern Web browser [with any of the following systems Windows (Win2k/WinXP/Vista/Windows7, 32/64 bit), Mac OS X, or Linux 32/64 bit]
  • Nexus Copy Number software
NOTE: This protocol assumes that protocol 1 has been successfully completed.
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Figures

Videos

Literature Cited

   Feuk, L., Carson, A.R., and Scherer, S.W. 2006. Structural variation in the human genome. Nat. Rev. Genet. 7:85‐97.
   Fisher, R.A. 1922. On the interpretation of χ2 from contingency tables, and the calculation of P. J. R. Stat. Soc. 85:87‐94.
   Freeman, J.L., Perry, G.H., Feuk, L., Redon, R., McCarroll, S.A., Altshuler, D.M., Aburatani, H., Jones, K.W., Tyler‐Smith, C., Hurles, M.E., Carter, N.P., Scherer, S.W., and Lee, C. 2006. Copy number variation: New insights in genome diversity. Genome Res. 16:949‐961.
   Hollox, E.J., Huffmeier, U., Zeeuwen, P., Palla, R., Lascorz, J., Rodijk‐Olthuis, D., van de Kerkhof, P.C.M., Traupe, H., de Jongh, G., den Heijer, M., Reis, A., Armour, J.A.L., and Schalkwijk, J. 2008. Psoriasis is associated with increased β‐defensin genomic copy number. Nat. Genet. 40:23‐25.
   Iafrate, A.J., Feuk, L., Rivera, M.N., Listewnik, M.L., Donahoe, P.K., Qi, Y., Scherer, S.W., and Lee, C. 2004. Detection of large‐scale variation in the human genome. Nat. Genet. 36:949‐951.
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   Olshen, A.B., Venkatraman, E.S., Lucito, R., and Wigler, M. 2004. Circular binary segmentation for the analysis of array‐based DNA copy number data. Biostatistics 5:557‐572.
   Peto, R. and Peto, J. 1972. Asymptotically efficient rank invariant test procedures. J. R. Stat. Soc. 135:185‐207.
   Redon, R., Ishikawa, S., Fitch, K.R., Feuk, L., Perry, G.H., Andrews, T.D., Fiegler, H., Shapero, M.H., Carson, A.R., Chen, W., Cho, E.K., Dallaire, S., Freeman, J.L., Gonzalez, J.R., Gratacos, M., Huang, J., Kalaitzopoulos, D., Komura, D., MacDonald, J.R., Marshall, C.R., Mei, R., Montgomery, L., Nishimura, K., Okamura, K., Shen, F., Somerville, M.J., Tchinda, J., Valsesia, A., Woodwark, C., Yang, F., Zhang, J., Zerjal, T., Zhang, J., Armengol, L., Conrad, D.F., Estivill, X., Tyler‐Smith, C., Carter, N.P., Aburatani, H., Lee, C., Jones, K.W., Scherer, S.W., and Hurles, M.E. 2006. Global variation in copy number in the human genome. Nature 444:444‐454.
   Sebat, J., Lakshmi, B., Troge, J., Alexander, J., Young, J., Lundin, P., Maner, S., Massa, H., Walker, M., Chi, M., Navin, N., Lucito, R., Healy, J., Hicks, J., Ye, K., Reiner, A., Gilliam, T.C., Trask, B., Patterson, N., Zetterberg, A., and Wigler, M. 2004. Large‐scale copy number polymorphism in the human genome. Science 305:525‐528.
   Tuzun, E., Sharp, A.J., Bailey, J.A., Kaul, R., Morrison, V.A., Pertz, L.M., Haugen, E., Hayden, H., Albertson, D., Pinkel, D., Olson, M.V., and Eichler, E.E. 2005. Fine‐scale structural variation of the human genome. Nat. Genet. 37:727‐732.
   Weiss, L.A., Shen, Y., Korn, J.M., Arking, D.E., Miller, D.T., Fossdal, R., Saemundsen, E., Stefansson, H., Ferreira, M.A., Green, T., Platt, O.S., Ruderfer, D.M., Walsh, C.A., Altshuler, D., Chakravarti, A., Tanzi, R.E., Stefansson, K., Santangelo, S.L., Gusella, J.F., Sklar, P., Wu, B.L., and Daly, M.J. 2008. Association between microdeletion and microduplication at 16p11.2 and autism. N. Engl. J. Med. 358:667‐675.
Internet Resources
   http://www.biodiscovery.com/
  Biodiscovery Web site containing information about copy number and expression analysis, software trial, download, tutorial, and publications.
   http://www.biodiscovery.com/index/downloads.
  Optional BeadStudio/GenomeStudio Plugin for Illumina platform in order to import data directly from BeadStudio or GenomeStudio into Nexus.
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