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Integration of Diverse Microarray Data Types

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Microarray Analysis of the Physical Genome

Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 556))

Abstract

Over the past decade, DNA microarrays have proven to be a powerful tool in biological research for the molecular surveillance of cells and tissues. The expansive utility of DNA microarrays owes its nascence to the development of a multitude of microarray platforms that enable the systematic and comprehensive exploration of diverse genomic properties and processes. Concomitant with the explosive generation of microarray data over the last several years has been an increasing interest in the integration of such diverse data types, thus spurring the development of novel statistical techniques and integrative bioinformatics tools. This chapter will outline general approaches to microarray data integration and provide an introduction to DR-Integrator, a broadly useful analysis tool for the integration of DNA copy number and gene-expression microarray data.

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References

  1. Schena, M., Shalon, D., Davis, R. W., and Brown, P. O. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467–470.

    Article  PubMed  CAS  Google Scholar 

  2. Calin, G. A., Liu, C. G., Sevignani, C., Ferracin, M., Felli, N., Dumitru, C. D., et al. (2004) MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias. Proc Natl Acad Sci USA 101, 11755–11760.

    Article  PubMed  CAS  Google Scholar 

  3. Haab, B. B., Dunham, M. J., and Brown, P. O. (2001) Protein microarrays for highly parallel detection and quantitation of specific proteins and antibodies in complex solutions. Genome Biol 2, RESEARCH0004.

    Article  PubMed  CAS  Google Scholar 

  4. Pinkel, D., Segraves, R., Sudar, D., Clark, S., Poole, I., Kowbel, D., et al. (1998) High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat Genet 20, 207–211.

    Article  PubMed  CAS  Google Scholar 

  5. Pollack, J. R., Perou, C. M., Alizadeh, A. A., Eisen, M. B., Pergamenschikov, A., Williams, C. F., et al. (1999) Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat Genet 23, 41–46.

    Article  PubMed  CAS  Google Scholar 

  6. Kennedy, G. C., Matsuzaki, H., Dong, S., Liu, W. M., Huang, J., Liu, G., et al. (2003) Large-scale genotyping of complex DNA. Nat Biotechnol 21, 1233–1237.

    Article  PubMed  CAS  Google Scholar 

  7. Yan, P. S., Chen, C. M., Shi, H., Rahmatpanah, F., Wei, S. H., Caldwell, C. W., et al. (2001) Dissecting complex epigenetic alterations in breast cancer using CpG island microarrays. Cancer Res 61, 8375–8380.

    PubMed  CAS  Google Scholar 

  8. Weinmann, A. S., Yan, P. S., Oberley, M. J., Huang, T. H., and Farnham, P. J. (2002) Isolating human transcription factor targets by coupling chromatin immunoprecipitation and CpG island microarray analysis. Genes Dev 16, 235–244.

    Article  PubMed  CAS  Google Scholar 

  9. Silva, J. M., Mizuno, H., Brady, A., Lucito, R., and Hannon, G. J. (2004) RNA interference microarrays: high-throughput loss-of-function genetics in mammalian cells. Proc Natl Acad Sci U S A 101, 6548–6552.

    Article  PubMed  CAS  Google Scholar 

  10. Segal, E., Friedman, N., Koller, D., and Regev, A. (2004) A module map showing conditional activity of expression modules in cancer. Nat Genet 36, 1090–1098.

    Article  PubMed  CAS  Google Scholar 

  11. Tan, K., Tegner, J., and Ravasi, T. (2008) Integrated approaches to uncovering transcription regulatory networks in mammalian cells. Genomics 91, 219–231.

    Article  PubMed  CAS  Google Scholar 

  12. Lee, S. I., Pe’er, D., Dudley, A. M., Church, G. M., and Koller, D. (2006) Identifying regulatory mechanisms using individual variation reveals key role for chromatin modification. Proc Natl Acad Sci USA 103, 14062–14067.

    Article  PubMed  CAS  Google Scholar 

  13. Carroll, J. S., Meyer, C. A., Song, J., Li, W., Geistlinger, T. R., Eeckhoute, J., et al. (2006) Genome-wide analysis of estrogen receptor binding sites. Nat Genet 38, 1289–1297.

    Article  PubMed  CAS  Google Scholar 

  14. Yu, J., Cao, Q., Mehra, R., Laxman, B., Tomlins, S. A., Creighton, C. J., et al. (2007) Integrative genomics analysis reveals silencing of beta-adrenergic signaling by polycomb in prostate cancer. Cancer Cell 12, 419–431.

    Article  PubMed  CAS  Google Scholar 

  15. Pollack, J. R., Sorlie, T., Perou, C. M., Rees, C. A., Jeffrey, S. S., Lonning, P. E., et al. (2002) Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc Natl Acad Sci USA 99, 12963–12968.

    Article  PubMed  CAS  Google Scholar 

  16. Garraway, L. A., Widlund, H. R., Rubin, M. A., Getz, G., Berger, A. J., Ramaswamy, S., et al. (2005) Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma. Nature 436, 117–122.

    Article  PubMed  CAS  Google Scholar 

  17. Kwei, K. A., Kim, Y. H., Girard, L., Kao, J., Pacyna-Gengelbach, M., Salari, K., et al. (2008) Genomic profiling identifies TITF1 as a lineage-specific oncogene amplified in lung cancer. Oncogene 27, 3635–3640.

    Article  PubMed  CAS  Google Scholar 

  18. Kwei, K. A., Bashyam, M. D., Kao, J., Ratheesh, R., Reddy, E. C., Kim, Y. H., et al. (2008) Genomic profiling identifies GATA6 as a candidate oncogene amplified in pancreatobiliary cancer. PLoS Genet 4, e1000081.

    Article  PubMed  Google Scholar 

  19. Zardo, G., Tiirikainen, M. I., Hong, C., Misra, A., Feuerstein, B. G., Volik, S., et al. (2002) Integrated genomic and epigenomic analyses pinpoint biallelic gene inactivation in tumors. Nat Genet 32, 453–458.

    Article  PubMed  CAS  Google Scholar 

  20. Zender, L., Spector, M. S., Xue, W., Flemming, P., Cordon-Cardo, C., Silke, J., et al. (2006) Identification and validation of oncogenes in liver cancer using an integrative oncogenomic approach. Cell 125, 1253–1267.

    Article  PubMed  CAS  Google Scholar 

  21. Kim, M., Gans, J. D., Nogueira, C., Wang, A., Paik, J. H., Feng, B., et al. (2006) Comparative oncogenomics identifies NEDD9 as a melanoma metastasis gene. Cell 125, 1269–1281.

    Article  PubMed  CAS  Google Scholar 

  22. Maser, R. S., Choudhury, B., Campbell, P. J., Feng, B., Wong, K. K., Protopopov, A., et al. (2007) Chromosomally unstable mouse tumours have genomic alterations similar to diverse human cancers. Nature 447, 966–971.

    Article  PubMed  CAS  Google Scholar 

  23. Butte, A. J. (2004) Exploring Genomic Medicine Using Integrative Biology. Massachusetts Institute of Technology: Cambridge, MA.

    Google Scholar 

  24. Liu, F., Park, P. J., Lai, W., Maher, E., Chakravarti, A., Durso, L., et al. (2006) A genome-wide screen reveals functional gene clusters in the cancer genome and identifies EphA2 as a mitogen in glioblastoma. Cancer Res 66, 10815–10823.

    Article  PubMed  CAS  Google Scholar 

  25. Weir, B. A., Woo, M. S., Getz, G., Perner, S., Ding, L., Beroukhim, R., et al. (2007) Characterizing the cancer genome in lung adenocarcinoma. Nature 450, 893–898.

    Article  PubMed  CAS  Google Scholar 

  26. Salari, K., Tibshirani, R., and Pollack, J. R. DR-Integrator: an integrative analysis tool for DNA copy number and RNA expression microarray data. Manuscript in preparation.

    Google Scholar 

  27. Tibshirani, R., and Wang, P. (2008) Spatial smoothing and hot spot detection for CGH data using the fused lasso. Biostatistics 9, 18–29.

    Article  PubMed  Google Scholar 

  28. Lai, W. R., Johnson, M. D., Kucherlapati, R., and Park, P. J. (2005) Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data. Bioinformatics 21, 3763–3770.

    Article  PubMed  CAS  Google Scholar 

  29. Willenbrock, H., and Fridlyand, J. (2005) A comparison study: applying segmentation to array CGH data for downstream analyses. Bioinformatics 21, 4084–4091.

    Article  PubMed  CAS  Google Scholar 

  30. Lai, W., Choudhary, V., and Park, P. J. (2008) CGHweb: a tool for comparing DNA copy number segmentations from multiple algorithms. Bioinformatics 24, 1014–1015.

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

The authors would like to thank Robert Tibshirani for helpful discussions in the development of DR-Integrator. K.S. is a Paul & Daisy Soros Fellow and a fellow of the Medical Scientist Training Program.

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© 2009 Humana Press, a part of Springer Science+Business Media, LLC

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Salari, K., Pollack, J.R. (2009). Integration of Diverse Microarray Data Types. In: Pollack, J. (eds) Microarray Analysis of the Physical Genome. Methods in Molecular Biology™, vol 556. Humana Press. https://doi.org/10.1007/978-1-60327-192-9_15

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  • DOI: https://doi.org/10.1007/978-1-60327-192-9_15

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  • Publisher Name: Humana Press

  • Print ISBN: 978-1-60327-191-2

  • Online ISBN: 978-1-60327-192-9

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