Gene Expression Profiling pp 41-53 | Cite as
Software and Tools for Microarray Data Analysis
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Abstract
A typical microarray experiment results in series of images, depending on the experimental design and number of samples. Software analyses the images to obtain the intensity at each spot and quantify the expression for each transcript. This is followed by normalization, and then various data analysis techniques are applied on the data. The whole analysis pipeline requires a large number of software to accurately handle the massive amount of data. Fortunately, there are large number of freely available and commercial software to churn the massive amount of data to manageable sets of differentially expressed genes, functions, and pathways. This chapter describes the software and tools which can be used to analyze the gene expression data right from the image analysis to gene list, ontology, and pathways.
Key words
Microarray Gene expression Normalization Clustering Classification Gene ontology PathwaysReferences
- 1.Rubenstein, K. (2003) Commercial aspects of microarray technology. BioTechniques. Suppl: 52–4.Google Scholar
- 2.Bolstad, B.M., Irizarry, R.A., Astrand, M., Speed, T.P. (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 19 185–93.Google Scholar
- 3.Irizarry, R.A., Bolstad, B.M., Collin, F., Cope, L.M., Hobbs, B., Speed, T.P. (2003) Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 31 e15.PubMedCrossRefGoogle Scholar
- 4.Li, C., Hung, Wong. W. (2001) Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application. Genome Biol. 2, RESEARCH0032.Google Scholar
- 5.Saeed, A.I., Sharov, V., White, J., et al. (2003) TM4: a free, open-source system for microarray data management and analysis. BioTechniques. 34 374–8.Google Scholar
- 6.Colantuoni, C., Henry, G., Zeger, S., Pevsner, J. (2002) SNOMAD (Standardization and NOrmalization of MicroArray Data): web-accessible gene expression data analysis. Bioinformatics. 18 1540–1.PubMedCrossRefGoogle Scholar
- 7.Tusher, V.G., Tibshirani, R., Chu, G. (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA. 98 5116–21.PubMedCrossRefGoogle Scholar
- 8.Efron, B., Tibshirani, R. (2002) Empirical bayes methods and false discovery rates for microarrays. Genet Epidemiol. 23 70–86.Google Scholar
- 9.Sturn, A., Quackenbush, J., Trajanoski, Z. (2002) Genesis: cluster analysis of microarray data. Bioinformatics. 18 207–8.PubMedCrossRefGoogle Scholar
- 10.Statnikov, A., Aliferis, C.F., Tsamardinos, I., Hardin, D., Levy, S. (2005) A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis. Bioinformatics. 21 631–43.PubMedCrossRefGoogle Scholar
- 11.Dahlquist, K.D., Salomonis, N., Vranizan, K., Lawlor, S.C., Conklin, B.R. (2002) GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways. Nat Genet. 31 19–20.PubMedCrossRefGoogle Scholar
- 12.Doniger, S.W., Salomonis, N., Dahlquist, K.D., Vranizan, K., Lawlor, S.C., Conklin, B.R. (2003) MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data. Genome Biol. 4 R7.PubMedCrossRefGoogle Scholar
- 13.Draghici, S., Khatri, P., Bhavsar, P., Shah, A., Krawetz, S.A., Tainsky, M.A. (2003) Onto-Tools, the toolkit of the modern biologist: Onto-Express, Onto-Compare, Onto-Design and Onto-Translate. Nucleic Acids Res. 31 3775–81.Google Scholar
- 14.Khatri, P., Draghici, S. (2005) Ontological analysis of gene expression data: current tools, limitations, and open problems. Bioinformatics. 21 3587–95.PubMedCrossRefGoogle Scholar
- 15.Khatri, P., Sellamuthu, S., Malhotra, P., Amin, K., Done, A., Draghici, S. (2005) Recent additions and improvements to the Onto-Tools. Nucleic Acids Res. 33 W762–5.PubMedCrossRefGoogle Scholar
- 16.Khatri, P., Voichita, C., Kattan, K., et al. (2007) Onto-Tools: new additions and improvements in 2006. Nucleic Acids Res. 35 W206–11.PubMedCrossRefGoogle Scholar
- 17.Dennis, G., Jr, Sherman, B.T., Hosack, D.A., et al. (2003) DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol. 4 P3.PubMedCrossRefGoogle Scholar
- 18.Hosack, D.A., Dennis, G., Jr, Sherman, B.T., Lane, H.C., Lempicki, R.A. (2003) Identifying biological themes within lists of genes with EASE. Genome Biol. 4 R70.PubMedCrossRefGoogle Scholar