Springer Protocols: Abstract: Analysis of Comparative Genomic Hybridization Data on cDNA Microarrays

Analysis of Comparative Genomic Hybridization Data on cDNA Microarrays

By: Sven Bilke², Javed Khan²

Abstract

Full Text

Download PDF (137K)

We present a detailed method to analyze DNA copy number data generated on cDNA microarrays. A web interface is made available for those steps in the workflow that are not typically used in gene expression analysis so that these steps can be carried out online. The end result of the analysis is a list of p-values for the presence of genomic gains or losses for each sample individually or an average p-value, which we show is useful to identify recurrent genomic imbalances.

Affiliation(s): (2) Oncogenomics Section, Pediatric Oncology Branch, Advanced Technology Center, National Cancer Institute, Gaithersburg, MD

Book Title: Microarray Data Analysis: Methods and Applications

Series: Methods in Molecular Biology | Volume: 377 | Pub. Date: May-03-2007 | Page Range: 175-186 | DOI: 10.1007/978-1-59745-390-5_11

Subject: Genetics/Genomics

Key Words: Microarray - comparative genomic hybridization - cancer - disease diagnosis - disease prognosis

References

Download References

1.	Mittelman, A. (1962) Tumor etiology and chromosome pattern. Science 176, 1340–1341.

2.	Forozan, F., Karhu, R., Kononen, J., et al. (1997) Genome screening by comparative genomic hybridization. Trends Genet. 13, 405–409.

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

4.	Pollack, J. R., Perou, C. M., Alizadeh, A. A., et al. (1999) Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat. Gen. 23, 41–46.

5.	Pinkel, D. and Albertson, D. G. (2005) Array comparative genomic hybridization and its applications in cancer. Nat Genet. 37Suppl, S11–S17.

6.	Pollack, J. R., Sortie, T., Perou, C. M., 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, 12,963–12,968.

7.	Hyman, E., Kauraniemi, P., Hautaniemi, S., et al. (2002) Impact of DNA amplification on gene expression patterns in breast cancer. Cancer Res. 62, 6240–6245.

8.	Beheshti, B., Braude, I., Marrano, P., et al. (2003) Chromosomal localization of DNA amplifications in neuroblastoma tumors using cDNA microarray comparative genomic hybridization. Neoplasia 5, 53–62.

9.	Hupe, P., Stransky, N., Thiery, J., et al. (2004) Analysis of array CGH data: from signal ratio to gain and loss of DNA regions, Bioinformatics 20, 3413–3422.

10.	Jong, K., Marchiori, E., Meijer, G., et al. (2004) Breakpoint identification and smoothing of array comparative genomic hybridization data, Bioinformatics 20, 3636–3637.

11.	Bilke, S., Chen Q. R., Whiteford, C. C., et al. (2005) Detection of low level genomic alterations by comparative genomic hybridization based on cDNA microarrays. Bioinformatics 21, 1138–1145.

12.	Sokal, A. (1996) Monte Carlo methods in statistical mechanics: foundations and new algorithms. In: Dewitt-Morette, C., Castier, P., Folacci, A. (eds.) Lectures at the Cargèse Summer School on ‘Functional Integration: Basics and Applications.’ Proc. ASI, Cargèse, France, p. 431.

13.	Cleveland, W. S. (1979) Robust locally weighted regression and smoothing scatterplots. J. Amer. Stat. Assoc. 74, 829–836.

14.	Dudoit, S., Yang, Y. H., Callow, M. J., et al. (2002) Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments. Statist. Sinica. 12, 111–139.

15.	Yang, Y. H., Dudoit, S., Luu, P., et al. (2002) Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucl. Acids Res. 30, e15.

16.	Chen, Q. R., Bilke, S., Wei, J. S., et al. (2004) cDNA Array-CGH profiling identifies genomic alterations specific to stage and MYCN-amplification in neuroblastoma. BMC Genomics 5, 70.

17.	Bilke, S., Chen, Q. R., Westerman, F., et al. (2005) Inferring a tumor progression model for neuroblastoma from genomic data. J. Clin. Oncol. 23, 7322–7331.

Comments (Loading...)

Post comment/View all comments