BioChip Journal

, 5:265 | Cite as

CNVAS: Copy Number Variation Analysis System — The analysis tool for genomic alteration with a powerful visualization module

  • Jinho Yoo
  • In Cheol Ha
  • Gyu Tae Chang
  • Kwang Su Jung
  • Kiejung ParkEmail author
  • Yangseok KimEmail author
Original Research


Recently, Copy Number Variation (CNV) has been recognized as one of the most important genomic alterations in the study of human variation, as it can be employed as a novel marker for human disease studies. Thus, many hardware technologies have been developed to detect copy number variations, including chip-based technologies. However, owing to its complexity, relatively few analysis tools are currently available for CNV, and most public tools have only limited functions and Graphic User Interfaces (GUI). CNVAS is a powerful software package for the analysis of CNV. Two different algorithms, Smith Waterman (SW) and Circular Binary Segmentation (CBS), are implemented for the detection of CNV regions. Furthermore, in order to evaluate the relationship between phenotype and CNV, CNVAS can perform the Chi-square test and Fisher’s exact test. Result visualization is another strong merit of the CNVAS software. CNVAS can show the analysis results in the form of chromosome ideograms, and these can be exported in the form of an image file. Furthermore, CNVAS has a database system, which can manage the user’s data from different sources and under different experimental conditions. CNVAS is a web-based program, and users can freely access the CNVAS by connecting to


Copy Number Variation Phenotype-specific CNV Bioinformatics Chromosome visualization Association study 


  1. 1.
    Yoshihara, K. et al. Germline copy number variations in BRCA1-associated ovarian cancer patients. Genes Chromosomes Cancer 50, 167–177 (2011).CrossRefGoogle Scholar
  2. 2.
    Fanciulli, M., Petretto, E. & Aitman, T.J. Gene copy number variation and common human disease. Clin Genet. 77, 201–213 (2010).CrossRefGoogle Scholar
  3. 3.
    Kuiper, R.P., Ligtenberg, M.J., Hoogerbrugge, N. & Geurts van Kessel, A. Germline copy number variation and cancer risk. Curr Opin Genet Dev. 20, 282–289 (2010).CrossRefGoogle Scholar
  4. 4.
    Dear, P.H. Copy-number variation: the end of the human genome? Trends Biotechnol. 27, 448–454 (2009).CrossRefGoogle Scholar
  5. 5.
    Lee, M. & Kim, Y. CHESS (CgHExpreSS): A comprehensive analysis tool for the analysis of genomic alterations and their effects on the expression profile of the genome. BMC Bioinformatics. 10, 424 (2009).CrossRefGoogle Scholar
  6. 6.
    Kim, T., Jung, Y., Rhyu, M., Jung, M.H. & Chung, Y. GEAR: genomic enrichment analysis of regional DNA copy number changes. Bioinformatics. 24, 420–421 (2008).CrossRefGoogle Scholar
  7. 7.
    Shankar, G. et al. aCGHViewer: a generic visualization tool for aCGH data. Cancer Inform. 2, 36–43 (2006).Google Scholar
  8. 8.
    Liva, S. et al. CAPweb: a bioinformatics CGH array analysis platform. Nucleic Acids Res. 34, W477–481 (2006).CrossRefGoogle Scholar
  9. 9.
    van Wieringen, W.N., Belien, J.A.M., Vosse, S.J., Achame, E.M. & Ylstra, B. ACE-it: a tool for genomewide integration of gene dosage and RNA expression data. Bioinformatics. 22, 1919–1920 (2006).CrossRefGoogle Scholar
  10. 10.
    Conde, L. et al. ISACGH: a web-based environment for the analysis of Array CGH and gene expression which includes functional profiling. Nucleic Acids Res. 35, W81–85 (2007).CrossRefGoogle Scholar
  11. 11.
    La Rosa, P. et al. VAMP: visualization and analysis of array-CGH, transcriptome and other molecular profiles. Bioinformatics. 22, 2066–2073 (2006).CrossRefGoogle Scholar
  12. 12.
    Chari, R. et al. SIGMA2: a system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes. BMC Bioinformatics. 9, 422 (2008).CrossRefGoogle Scholar

Copyright information

© The Korean BioChip Society and Springer-Verlag Berlin Heidelberg  2011

Authors and Affiliations

  1. 1.Bioinformatics UnitISTECH Inc. No. 402Goyang-si, Gyeonggi-doKorea
  2. 2.Department of Oriental Pediatrics, College of Oriental MedicineKyung Hee UniversitySeoulKorea
  3. 3.Division of Bio-Medical Informatics, Center for Genome ScienceKorea National Institution of HealthChungcheongbuk-doKorea
  4. 4.Department of Physiology, College of Oriental MedicineKyung Hee UniversitySeoulKorea

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