Table of Contents Author Guidelines Submit a Manuscript
Journal of Biomedicine and Biotechnology
Volume 2011, Article ID 860732, 15 pages
http://dx.doi.org/10.1155/2011/860732
Research Article

A New Normalizing Algorithm for BAC CGH Arrays with Quality Control Metrics

1Department of Biostatistics, University at Buffalo, Buffalo, NY 14214, USA
2Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
3Department of Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
4Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
5Department of Biochemistry, University at Buffalo, Buffalo, NY 14214, USA

Received 1 July 2010; Revised 23 November 2010; Accepted 18 December 2010

Academic Editor: Adewale Adeyinka

Copyright © 2011 Jeffrey C. Miecznikowski et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. Schena, D. Shalon, R. W. Davis, and P. O. Brown, “Quantitative monitoring of gene expression patterns with a complementary DNA microarray,” Science, vol. 270, no. 5235, pp. 467–470, 1995. View at Google Scholar · View at Scopus
  2. A. M. Snijders, N. Nowak, R. Segraves et al., “Assembly of microarrays for genome-wide measurement of DNA copy number,” Nature Genetics, vol. 29, no. 3, pp. 263–264, 2001. View at Publisher · View at Google Scholar · View at Scopus
  3. F. Falciani, Microarray Technology Through Applications, Routledge, Routledge, UK, 2007.
  4. R. Gentleman, Bioinformatics and Computational Biology Solutions Using R and Bioconductor, Springer, New York, NY, USA, 2005.
  5. D. Lugtenberg, A. P. M. De Brouwer, T. Kleefstra et al., “Chromosomal copy number changes in patients with non-syndromic X linked mental retardation detected by array CGH,” Journal of Medical Genetics, vol. 43, no. 4, pp. 362–370, 2006. View at Publisher · View at Google Scholar · View at Scopus
  6. N. Miyake, O. Shimokawa, N. Harada et al., “BAC array CGH reveals genomic aberrations in idiopathic mental retardation,” American Journal of Medical Genetics, vol. 140, no. 3, pp. 205–211, 2006. View at Publisher · View at Google Scholar · View at Scopus
  7. P. Stankiewicz and A. L. Beaudet, “Use of array CGH in the evaluation of dysmorphology, malformations, developmental delay, and idiopathic mental retardation,” Current Opinion in Genetics and Development, vol. 17, no. 3, pp. 182–192, 2007. View at Publisher · View at Google Scholar · View at Scopus
  8. R. Ullmann, G. Turner, M. Kirchhoff et al., “Array CGH identifies reciprocal 16p13.1 duplications and deletions that predispose to autism and/or mental retardation,” Human Mutation, vol. 28, no. 7, pp. 674–682, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. D. G. Albertson, B. Ylstra, R. Segraves et al., “Quantitative mapping of amplicon structure by array CGH identifies CYP24 as a candidate oncogene,” Nature Genetics, vol. 25, no. 2, pp. 144–146, 2000. View at Publisher · View at Google Scholar · View at Scopus
  10. G. Hodgson, J. H. Hager, S. Volik et al., “Genome scanning with array CGH delineates regional alterations in mouse islet carcinomas,” Nature Genetics, vol. 29, no. 4, pp. 459–464, 2001. View at Publisher · View at Google Scholar · View at Scopus
  11. J. R. Pollack, T. Sørlie, C. M. Perou et al., “Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors,” Proceedings of the National Academy of Sciences of the United States of America, vol. 99, no. 20, pp. 12963–12968, 2002. View at Publisher · View at Google Scholar
  12. D. G. Albertson, “Profiling breast cancer by array CGH,” Breast Cancer Research and Treatment, vol. 78, no. 3, pp. 289–298, 2003. View at Publisher · View at Google Scholar · View at Scopus
  13. D. G. Albertson, C. Collins, F. McCormick, and J. W. Gray, “Chromosome aberrations in solid tumors,” Nature Genetics, vol. 34, no. 4, pp. 369–376, 2003. View at Publisher · View at Google Scholar · View at Scopus
  14. C. S. Hackett, J. G. Hodgson, M. E. Law et al., “Genome-wide array CGH analysis of murine neuroblastoma reveals distinct genomic aberrations which parallel those in human tumors,” Cancer Research, vol. 63, no. 17, pp. 5266–5273, 2003. View at Google Scholar · View at Scopus
  15. C. Garnis, B. P. Coe, L. Zhang, M. P. Rosin, and W. L. Lam, “Overexpression of LRP12, a gene contained within an 8q22 amplicon identified by high-resolution array CGH analysis of oral squamous cell carcinomas,” Oncogene, vol. 23, no. 14, pp. 2582–2586, 2004. View at Publisher · View at Google Scholar · View at Scopus
  16. J. A. Veltman, J. Fridlyand, S. Pejavar et al., “Array-based comparative genomic hybridization for genome-wide screening of DNA copy number in bladder tumors,” Cancer Research, vol. 63, no. 11, pp. 2872–2880, 2003. View at Google Scholar · View at Scopus
  17. L. W. M. Loo, D. I. Grove, E. M. Williams et al., “Array comparative genomic hybridization analysis of genomic alterations in breast cancer subtypes,” Cancer Research, vol. 64, no. 23, pp. 8541–8549, 2004. View at Publisher · View at Google Scholar · View at Scopus
  18. D. Pinkel and D. G. Albertson, “Array comparative genomic hybridization and its applications in cancer,” Nature Genetics, vol. 37, no. 6, pp. S11–S17, 2005. View at Publisher · View at Google Scholar · View at Scopus
  19. M. R. Rossi, J. Conroy, D. McQuaid, N. J. Nowak, J. T. Rutka, and J. K. Cowell, “Array CGH analysis of pediatric medulloblastomas,” Genes Chromosomes and Cancer, vol. 45, no. 3, pp. 290–303, 2006. View at Publisher · View at Google Scholar · View at Scopus
  20. A. Idbaih, Y. Marie, C. Lucchesi et al., “BAC array CGH distinguishes mutually exclusive alterations that define clinicogenetic subtypes of gliomas,” International Journal of Cancer, vol. 122, no. 8, pp. 1778–1786, 2008. View at Publisher · View at Google Scholar · View at Scopus
  21. M. E. Futschik and T. Crompton, “OLIN: optimized normalization, visualization and quality testing of two-channel microarray data,” Bioinformatics, vol. 21, no. 8, pp. 1724–1726, 2005. View at Publisher · View at Google Scholar · View at Scopus
  22. Y. Xiao, M. R. Segal, and H. Y. Yee, “Stepwise normalization of two-channel spotted microarrays,” Statistical Applications in Genetics and Molecular Biology, vol. 4, no. 1, p. 1117, 2005. View at Google Scholar · View at Scopus
  23. M. Khojasteh, W. L. Lam, R. K. Ward, and C. MacAulay, “A stepwise framework for the normalization of array CGH data,” BMC Bioinformatics, vol. 6, no. 1, article 274, 2005. View at Publisher · View at Google Scholar · View at Scopus
  24. F. Picard, S. Robin, M. Lavielle, C. Vaisse, and J. J. Daudin, “A statistical approach for array CGH data analysis,” BMC Bioinformatics, vol. 6, no. 1, article 27, 2005. View at Publisher · View at Google Scholar · View at Scopus
  25. P. Neuvial, P. Hupé, I. Brito et al., “Spatial normalization of array-CGH data,” BMC Bioinformatics, vol. 7, no. 1, article 264, 2006. View at Publisher · View at Google Scholar · View at Scopus
  26. J. Staaf, G. Jönsson, M. Ringnér, and J. Vallon-Christersson, “Normalization of array-CGH data: influence of copy number imbalances,” BMC Genomics, vol. 8, no. 1, article 382, 2007. View at Publisher · View at Google Scholar · View at Scopus
  27. H. Huang, N. Nguyen, S. Oraintara, and AN. Vo, “Array CGH data modeling and smoothing in Stationary Wavelet Packet Transform domain,” BMC Genomics, vol. 9, supplement 2, p. S17, 2008. View at Publisher · View at Google Scholar · View at Scopus
  28. J. Fridlyand and P. Dimitrov, aCGH: Classes and functions for Array Comparative Genomic Hybridization Data, 2009, R package version 1.22.0.
  29. P. Neuvial and P. Hupe, “MANOR: CGH Micro-Array NORmalization,” r package version 1.18.0., 2009, http://bioinfo.curie.fr/projects/manor/index.html.
  30. R. Ihaka and R. Gentleman, “R: a language for data analysis and graphics,” Journal of Computational and Graphical Statistics, vol. 5, no. 3, pp. 299–314, 1996. View at Google Scholar · View at Scopus
  31. D. Gaile, L. Shepherd, and J. Miecznikowski, “aCGHplus,” r package version 2.4.1, 2009, http://sphhp.buffalo.edu/biostat/research/software/acghplus/index.php.
  32. N. J. Nowak, J. Miecznikowski, S. R. Moore et al., “Challenges in array comparative genomic hybridization for the analysis of cancer samples,” Genetics in Medicine, vol. 9, no. 9, pp. 585–595, 2007. View at Publisher · View at Google Scholar · View at Scopus
  33. D. Miliaras, J. Conroy, S. Pervana, S. Meditskou, D. McQuaid, and N. Nowak, “Karyotypic changes detected by comparative genomic hybridization in a stillborn infant with chorioangioma and liver hemangioma,” Birth Defects Research Part A—Clinical and Molecular Teratology, vol. 79, no. 3, pp. 236–241, 2007. View at Publisher · View at Google Scholar · View at Scopus
  34. K. Sellers, J. Miecznikowski, and W. Eddy, “Removal of systematic variation in genetic microarray data,” Tech. Rep. 779, Carnegie Mellon University, 2004. View at Google Scholar
  35. P. Stafford, Methods in Microarray Normalization, CRC, London, UK, 2008.
  36. S. K. Watson, R. J. deLeeuw, A. S. Ishkanian, C. A. Malloff, and W. L. Lam, “Methods for high throughput validation of amplified fragment pools of BAC DNA for constructing high resolution CGH arrays,” BMC Genomics, vol. 5, no. 1, article 6, 2004. View at Publisher · View at Google Scholar · View at Scopus
  37. A. B. Olshen, E. S. Venkatraman, R. Lucito, and M. Wigler, “Circular binary segmentation for the analysis of array-based DNA copy number data,” Biostatistics, vol. 5, no. 4, pp. 557–572, 2004. View at Publisher · View at Google Scholar · View at Scopus
  38. D. Nychka, “Fields: tools for spatial data,” r package version 2.0., 2009, http://www.cgd.ucar.edu/stats/Software/Fields.
  39. J. Miecznikowski, D. Gaile, J. Conroy, and N. Nowak, “Quality control metrics for array comparative genomic hybridization data,” Tech. Rep. 0606, Department of Biostatistics, University at Buffalo, Buffalo, NY, USA, 2006. View at Google Scholar
  40. W. Cleveland, E. Grosse, and W. Shyu, “Local regression models,” in Statistical Models in S, pp. 309–376, Chapman & Hall, Boca Raton, Fla, USA, 1992. View at Google Scholar
  41. B. M. Bolstad, R. A. Irizarry, M. Åstrand, and T. P. Speed, “A comparison of normalization methods for high density oligonucleotide array data based on variance and bias,” Bioinformatics, vol. 19, no. 2, pp. 185–193, 2003. View at Publisher · View at Google Scholar · View at Scopus
  42. J. L. Hintze and R. D. Nelson, “Violin plots: a box plot-density trace synergism,” American Statistician, vol. 52, no. 2, pp. 181–184, 1998. View at Google Scholar · View at Scopus
  43. M. A. van de Wie, K. I. Kim, S. J. Vosse, W. N. van Wieringen, S. M. Wilting, and B. Ylstra, “CGHcall: calling aberrations for array CGH tumor profiles,” Bioinformatics, vol. 23, no. 7, pp. 892–894, 2007. View at Publisher · View at Google Scholar · View at Scopus
  44. K. Jong, E. Marchiori, G. Meijer, A. V. D. Vaart, and B. Ylstra, “Breakpoint identification and smoothing of array comparative genomic hybridization data,” Bioinformatics, vol. 20, no. 18, pp. 3636–3637, 2004. View at Publisher · View at Google Scholar · View at Scopus
  45. P. Wang, Y. Kim, J. Pollack, B. Narasimhan, and R. Tibshirani, “A method for calling gains and losses in array CGH data,” Biostatistics, vol. 6, no. 1, pp. 45–58, 2005. View at Publisher · View at Google Scholar · View at Scopus
  46. Y. Nannya, M. Sanada, K. Nakazaki et al., “A robust algorithm for copy number detection using high-density oligonucleotide single nucleotide polymorphism genotyping arrays,” Cancer Research, vol. 65, no. 14, pp. 6071–6079, 2005. View at Publisher · View at Google Scholar · View at Scopus
  47. D. P. Gaile, E. D. Schifano, J. C. Miecznikowski, J. J. Java, J. M. Conroy, and N. J. Nowak, “Estimating the arm-wise false discovery rate in array comparative genomic hybridization experiments,” Statistical Applications in Genetics and Molecular Biology, vol. 6, no. 1, article 32, 2007. View at Google Scholar · View at Scopus
  48. W. R. Lai, M. D. Johnson, R. Kucherlapati, and P. J. Park, “Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data,” Bioinformatics, vol. 21, no. 19, pp. 3763–3770, 2005. View at Publisher · View at Google Scholar · View at Scopus
  49. H. Willenbrock and J. Fridlyand, “A comparison study: applying segmentation to array CGH data for downstream analyses,” Bioinformatics, vol. 21, no. 22, pp. 4084–4091, 2005. View at Publisher · View at Google Scholar · View at Scopus