Pre-processing of microarray data and analysis of differential expression.

作者: Steffen Durinck

DOI: 10.1007/978-1-60327-159-2_4

关键词: GeneMicroarray databasesDNA microarrayMicroarray analysis techniquesBioconductorComputer scienceExpression (computer science)Northern blotGene expressionComputational biologyRegulation of gene expression

摘要: Microarrays have become a widely used technology in molecular biology research. One of their main uses is to measure gene expression. Compared older expression measuring assays such as Northern blotting, analyzing data from microarrays inherently more complex due the massive amounts they produce. The analysis microarray requires biologists collaborate with bioinformaticians or learn basics statistics and programming. Many software tools for are available. Currently one most popular freely available Bioconductor. This chapter Bioconductor preprocess data, detect differentially expressed genes, annotate lists interest.

参考文章(22)
Christopher Workman, Lars Jensen, Hanne Jarmer, Randy Berka, Laurent Gautier, Henrik Nielser, Hans-Henrik Saxild, Claus Nielsen, Søren Brunak, Steen Knudsen, A new non-linear normalization method for reducing variability in DNA microarray experiments Genome Biology. ,vol. 3, pp. 1- 16 ,(2002) , 10.1186/GB-2002-3-9-RESEARCH0048
Robert Gentleman, Vincent J Carey, Wolfgang Huber, Rafael A Irizarry, Sandrine Dudoit, Bioinformatics and Computational Biology Solutions Using R and Bioconductor ,(2006)
Stanislav O Zakharkin, Kyoungmi Kim, Tapan Mehta, Lang Chen, Stephen Barnes, Katherine E Scheirer, Rudolph S Parrish, David B Allison, Grier P Page, Sources of variation in Affymetrix microarray experiments BMC Bioinformatics. ,vol. 6, pp. 214- 214 ,(2005) , 10.1186/1471-2105-6-214
Kerby Shedden, Wei Chen, Rork Kuick, Debashis Ghosh, James Macdonald, Kathleen R Cho, Thomas J Giordano, Stephen B Gruber, Eric R Fearon, Jeremy MG Taylor, Samir Hanash, Comparison of seven methods for producing Affymetrix expression scores based on False Discovery Rates in disease profiling data BMC Bioinformatics. ,vol. 6, pp. 26- 26 ,(2005) , 10.1186/1471-2105-6-26
Zhijin Wu, Rafael A Irizarry, Robert Gentleman, Francisco Martinez-Murillo, Forrest Spencer, A Model-Based Background Adjustment for Oligonucleotide Expression Arrays Journal of the American Statistical Association. ,vol. 99, pp. 909- 917 ,(2004) , 10.1198/016214504000000683
LUKE W. HUNT, RECENT OBSERVATIONS IN SERUM DISEASE JAMA. ,vol. 99, pp. 909- 912 ,(1932) , 10.1001/JAMA.1932.02740630035009
C. Li, W. H. Wong, Model-based analysis of oligonucleotide arrays: Expression index computation and outlier detection Proceedings of the National Academy of Sciences of the United States of America. ,vol. 98, pp. 31- 36 ,(2001) , 10.1073/PNAS.98.1.31
Gordon K Smyth, Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments Statistical Applications in Genetics and Molecular Biology. ,vol. 3, pp. 1- 25 ,(2004) , 10.2202/1544-6115.1027
M. Kathleen Kerr, Mitchell Martin, Gary A. Churchill, Analysis of Variance for Gene Expression Microarray Data Journal of Computational Biology. ,vol. 7, pp. 819- 837 ,(2000) , 10.1089/10665270050514954
R Radha, S Jayalakshmi, SP Rajagopalan, AA Alizadeh, MB Eisen, RE Davis, C Ma, IS Lossos, T Ando, M Katayama, DG Beer, LRK Sharon, CC Huang, TJ Giordano, AM Levin, SM Chen, YC Chen, DR Cox, U Fayyad, K Irani, M LeBlanc, H Liu, J Li, L Wong, M Lunn, DR McNeil, B Maurice, R Panneerselvam, PJ Park, L Tian, S Kohane, A Rosenwald, MA Shipp, MJ Van de Vijver, YD He, LJ van't Veer, H Dai, AA Hart, YH Yang, S Dudoit, P Luu, DM Lin, V Peng, J Ngai, TP Speed, Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation Nucleic Acids Research. ,vol. 30, ,(2002) , 10.1093/NAR/30.4.E15