Abstract
Microarray analysis results in the gathering of massive amounts of information concerning gene expression profiles of different cells and experimental conditions. Analyzing these data can often be a quagmire, with endless discussion as to what the appropriate statistical analyses for any given experiment might be. As a result many different methods of data analysis have evolved, the basics of which are outlined in this chapter.
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References
Augenlicht, L. H., Wahrman, M. Z., Halsey, H., Anderson, L., Taylor, J., and Lipkin, M. (1987) Expression of cloned sequences in biopsies of human colonic tissue and in colonic carcinoma cells induced to differentiate in vitro. Cancer Res. 47, 6017–6021.
Lander, E. S., Linton, L. M., Birren, B., et al. (2001) Initial sequencing and analysis of the human genome. Nature 409, 860–921.
Brazma, A., Hingamp, P., Quackenbush, J., et al. (2001) Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat. Genet. 29, 365–371.
Dodson, J. M., Charles, P. T., Stenger, D. A., and Pancrazio, J. J. (2002) Quantitative assessment of filter-based cDNA microarrays: gene expression profiles of human T-lymphoma cell lines. Bioinformatics 18, 953–960.
Li, Q., Fraley, C., Bumgarner, R.E., Yeung, K.Y., and Raftery, A.E. (2005) In: “Technical Report no. 473” (http://www.stat.washington.edu/www/research/reports/2005/tr473.pdf, Ed.), University of Washington, Seattle.
Jain, A. N., Tokuyasu, T. A., Snijders, A. M., Segraves, R., Albertson, D. G., and Pinkel, D. (2002) Fully automatic quantification of microarray image data. Genome Res. 12, 325–332.
Quackenbush, J. (2002) Microarray data normalization and transformation. Nat Genet 32(Suppl), 496–501.
Zien, A., Aigner, T., Zimmer, R., and Lengauer, T. (2001) Centralization: a new method for the normalization of gene expression data. Bioinformatics 17(Suppl 1), S323–S331.
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. Nucleic Acids Res. 30, e15.
Kepler, T. B., Crosby, L., and Morgan, K. T. (2002) Normalization and analysis of DNA microarray data by self-consistency and local regression. Genome Biol. 3, RESEARCH0037.
Zhao, Y., Li, M. C., and Simon, R. (2005) An adaptive method for cDNA microarray normalization. BMC Bio informatics 6, 28.
Sasik, R., Calvo, E., and Corbeil, J. (2002) Statistical analysis of high-density oligonucleotide arrays: a multiplicative noise model. Bioinformatics 18, 1633–1640.
Li, H., Wood, C. L., Getchell, T. V., Getchell, M. L., and Stromberg, A. J. (2004) Analysis of oligonucleotide array experiments with repeated measures using mixed models. BMC Bioinformatics 5, 209.
Meuwissen, T. H., and Goddard, M. E. (2004) Bootstrapping of gene-expression data improves and controls the false discovery rate of differentially expressed genes. Genet. Sel. Evol. 36, 191–205.
Reiner, A., Yekutieli, D., and Benjamini, Y. (2003) Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics 19, 368–375.
Barrett, T., Suzek, T. O., Troup, D. B., et al. (2005) NCBI GEO: mining millions of expression profiles — database and tools. Nucleic Acids Res. 33 Database Issue, D562–D566.
Sherlock, G. (2000) Analysis of large-scale gene expression data. Curr. Opin. Immunol. 12, 201–205.
Wang, J., Delabie, J., Aasheim, H., Smeland, E., and Myklebost, O. (2002) Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study. BMC Bioinformatics 3, 36.
Dharmadi, Y, and Gonzalez, R. (2004) DNA microarrays: experimental issues, data analysis, and application to bacterial systems. Biotechnol. Prog. 20, 1309–1324.
Bittner, M., Meltzer, P., Chen, Y, et al. (2000) Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature 406, 536–540.
Ramaswamy, S., Tamayo, P., Rifkin, R., et al. (2001) Multiclass cancer diagnosis using tumor gene expression signatures. Proc. Natl. Acad. Sei. USA 98, 15,149–15,154.
Cunliffe, H. E., Ringner, M., Bilke, S., et al. (2003) The gene expression response of breast cancer to growth regulators: patterns and correlation with tumor expression profiles. Cancer Res. 63, 7158–7166.
Burczynski, M. E., Oestreicher, J. L., Cahilly, M. J., et al. (2005) Clinical pharmacogenomics and transcriptional profiling in early phase oncology clinical trials. Curr. Mol. Med. 5, 83–102.
Nutt, C. L., Mani, D. R., Betensky, R. A., et al. (2003) Gene expression-based classification of malignant gliomas correlates better with survival than histological classification. Cancer Res. 63, 1602–1607.
Mendez, M. A., Hodar, C., Vulpe, C., Gonzalez, M., and Cambiazo, V. (2002) Discriminant analysis to evaluate clustering of gene expression data. FEBS Lett. 522, 24–28.
Olshen, A. B., and Jain, A. N. (2002) Deriving quantitative conclusions from microarray expression data. Bioinformatics 18, 961–970.
Brown, M. P., Grundy, W. N., Lin, D., et al. (2000) Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc. Natl. Acad. Sei. USA 97, 262–267.
Khan, J., Wei, J. S., Ringner, M., et al. (2001) Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat Med 7, 673–679.
Ringner, M., Peterson, C., and Khan, J. (2002) Analyzing array data using supervised methods. Pharmacogenomics 3, 403–415.
Zhang, H., Yu, C. Y., Singer, B., and Xiong, M. (2001) Recursive partitioning for tumor classification with gene expression microarray data. Proc. Natl. Acad. Sci. USA 98, 6730–6735.
Zeeberg, B. R., Feng, W., Wang, G., et al. (2003) GoMiner: a resource for biological interpretation of genomic and proteomic data. Genome Biol. 4, R28.
Dennis, G.,Jr., Sherman, B. T., Hosack, D. A., et al. (2003) DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol. 4, P3.
Demir, E., Babur, O., Dogrusoz, U., et al. (2002) PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways. Bioinformatics 18, 996–1003.
Raponi, M., Belly, R. T., Karp, J. E., Lancet, J. E., Atkins, D., and Wang, Y (2004) Microarray analysis reveals genetic pathways modulated by tipifarnib in acute myeloid leukemia. BMC Cancer 4, 56.
Jenson, S. D., Robetorye, R. S., Bohling, S. D., et al. (2003) Validation of cDNA microarray gene expression data obtained from linearly amplified RNA. Mol. Pathol. 56, 307–312.
Winer, J., Jung, C. K., Shackel, I., and Williams, P. M. (1999) Development and validation of real-time quantitative reverse transcriptase-polymerase chain reaction for monitoring gene expression in cardiac myocytes in vitro. Anal. Biochem. 270, 41–49.
Kononen, J., Bubendorf, L., Kallioniemi, A., et al. (1998) Tissue microarrays for high-throughput molecular profiling of tumor specimens. Nat. Med. 4, 844–847.
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Weeraratna, A.T., Taub, D.D. (2007). Microarray Data Analysis. In: Korenberg, M.J. (eds) Microarray Data Analysis. Methods in Molecular Biology™, vol 377. Humana Press. https://doi.org/10.1007/978-1-59745-390-5_1
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DOI: https://doi.org/10.1007/978-1-59745-390-5_1
Publisher Name: Humana Press
Print ISBN: 978-1-58829-540-8
Online ISBN: 978-1-59745-390-5
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