Fundamentals of cDNA microarray data analysis

Trends in Genetics - Tập 19 - Trang 649-659 - 2003
Yuk Fai Leung1, Duccio Cavalieri1
1Bauer Center For Genomics Research, Harvard University, 7 Divinity Avenue, Cambridge, MA 02138, USA

Tài liệu tham khảo

Leung, 2002, Microarray software review Box, 1978 Churchill, 2002, Fundamentals of experimental design for cDNA microarrays, Nat. Genet., 32, 490, 10.1038/ng1031 Yang, 2002, Design issues for cDNA microarray experiments, Nat. Rev. Genet., 3, 579, 10.1038/nrg863 Simon, 2003, Experimental design of DNA microarray experiments, Biotechniques, S16, 10.2144/mar03simon Perou, 2001, Show me the data!, Nat. Genet., 29, 373, 10.1038/ng1201-373 Brazma, 2001, Minimum information about a microarray experiment (MIAME)-toward standards for microarray data, Nat. Genet., 29, 365, 10.1038/ng1201-365 2002, Microarray standards at last, Nature, 419, 323, 10.1038/419323a Yang, 2001, Analysis of cDNA microarray images, Brief. Bioinform., 2, 341, 10.1093/bib/2.4.341 Jain, 2002, Fully automatic quantification of microarray image data, Genome Res., 12, 325, 10.1101/gr.210902 Quackenbush, 2002, Microarray data normalization and transformation, Nat. Genet., 32, 496, 10.1038/ng1032 Lee, 2002, Control genes and variability: absence of ubiquitous reference transcripts in diverse mammalian expression studies, Genome Res., 12, 292, 10.1101/gr.217802 Novak, 2002, Characterization of variability in large-scale gene expression data: implications for study design, Genomics, 79, 104, 10.1006/geno.2001.6675 Pritchard, 2001, Project normal: defining normal variance in mouse gene expression, Proc. Natl. Acad. Sci. U. S. A., 98, 13266, 10.1073/pnas.221465998 Nadon, 2002, Statistical issues with microarrays: processing and analysis, Trends Genet., 18, 265, 10.1016/S0168-9525(02)02665-3 Lee, 2000, Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations, Proc. Natl. Acad. Sci. U. S. A., 97, 9834, 10.1073/pnas.97.18.9834 Lönnstedt, 2002, Replicated Microarray Data, Stat. Sinica, 12, 31 Storey, 2003, SAM thresholding and false discovery rates for detecting differential gene expression in DNA microarrays Kerr, 2000, Analysis of variance for gene expression microarray data, J. Comput. Biol., 7, 819, 10.1089/10665270050514954 Long, 2001, Improved statistical inference from DNA microarray data using analysis of variance and a Bayesian statistical framework. Analysis of global gene expression in Escherichia coli K12, J. Biol. Chem., 276, 19937, 10.1074/jbc.M010192200 Baldi, 2001, A Bayesian framework for the analysis of microarray expression data: regularized t test and statistical inferences of gene changes, Bioinformatics, 17, 509, 10.1093/bioinformatics/17.6.509 Wu, 2001, Analysing gene expression data from DNA microarrays to identify candidate genes, J. Pathol., 195, 53, 10.1002/1096-9896(200109)195:1<53::AID-PATH891>3.0.CO;2-H Dudoit, 2002, Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments, Stat. Sinica, 12, 111 Chuaqui, 2002, Post-analysis follow-up and validation of microarray experiments, Nat. Genet., 32, 509, 10.1038/ng1034 Reiner, 2003, Identifying differentially expressed genes using false discovery rate controlling procedures, Bioinformatics, 19, 368, 10.1093/bioinformatics/btf877 Raychaudhuri, 2000, Principal components analysis to summarize microarray experiments: application to sporulation time series, Pac. Symp. Biocomput., 455 Alter, 2000, Singular value decomposition for genome-wide expression data processing and modeling, Proc. Natl. Acad. Sci. U. S. A., 97, 10101, 10.1073/pnas.97.18.10101 Eisen, 1998, Cluster analysis and display of genome-wide expression patterns, Proc. Natl. Acad. Sci. U. S. A., 95, 14863, 10.1073/pnas.95.25.14863 Tavazoie, 1999, Systematic determination of genetic network architecture, Nat. Genet., 22, 281, 10.1038/10343 Tamayo, 1999, Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation, Proc. Natl. Acad. Sci. U. S. A., 96, 2907, 10.1073/pnas.96.6.2907 Quackenbush, 2001, Computational analysis of microarray data, Nat. Rev. Genet., 2, 418, 10.1038/35076576 Sherlock, 2001, Analysis of large-scale gene expression data, Brief. Bioinform., 2, 350, 10.1093/bib/2.4.350 Valafar, 2002, Pattern recognition techniques in microarray data analysis: a survey, Ann. N. Y. Acad. Sci., 980, 41, 10.1111/j.1749-6632.2002.tb04888.x Pomeroy, 2002, Prediction of central nervous system embryonal tumour outcome based on gene expression, Nature, 415, 436, 10.1038/415436a Shipp, 2002, Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning, Nat. Med., 8, 68, 10.1038/nm0102-68 Khan, 2001, Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks, Nat. Med., 7, 673, 10.1038/89044 Brown, 2000, Knowledge-based analysis of microarray gene expression data by using support vector machines, Proc. Natl. Acad. Sci. U. S. A., 97, 262, 10.1073/pnas.97.1.262 Vohradsky, 2001, Neural network model of gene expression, FASEB J., 15, 846, 10.1096/fj.00-0361com Theilhaber, 2002, Finding genes in the C2C12 osteogenic pathway by k-nearest-neighbor classification of expression data, Genome Res., 12, 165, 10.1101/gr.182601 Ben-Dor, 2000, Tissue classification with gene expression profiles, J. Comput. Biol., 7, 559, 10.1089/106652700750050943 Pilpel, 2001, Identifying regulatory networks by combinatorial analysis of promoter elements, Nat. Genet., 29, 153, 10.1038/ng724 Hughes, 2000, Functional discovery via a compendium of expression profiles, Cell, 102, 109, 10.1016/S0092-8674(00)00015-5 Tavazoie, 1999, Systematic determination of genetic network architecture, Nat. Genet., 22, 281, 10.1038/10343 Liang, 1998, Reveal, a general reverse engineering algorithm for inference of genetic network architectures, Pac. Symp. Biocomput., 18 Akutsu, 2000, Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function, J. Comput. Biol., 7, 331, 10.1089/106652700750050817 Maki, 2001, Development of a system for the inference of large scale genetic networks, Pac. Symp. Biocomput., 446 Friedman, 2000, Using Bayesian networks to analyze expression data, J. Comput. Biol., 7, 601, 10.1089/106652700750050961 Hartemink, 2001, Using graphical models and genomic expression data to statistically validate models of genetic regulatory networks, Pac. Symp. Biocomput., 422 de Jong, 2002, Modeling and simulation of genetic regulatory systems: a literature review, J. Comput. Biol., 9, 67, 10.1089/10665270252833208 D'haeseleer, 2000, Genetic network inference: from co-expression clustering to reverse engineering, Bioinformatics, 16, 707, 10.1093/bioinformatics/16.8.707 Grosu, 2002, Pathway Processor: a tool for integrating whole-genome expression results into metabolic networks, Genome Res., 12, 1121, 10.1101/gr.226602 Schena, 1995, Quantitative monitoring of gene expression patterns with a complementary DNA microarray, Science, 270, 467, 10.1126/science.270.5235.467 Lipshutz, 1999, High density synthetic oligonucleotide arrays, Nat. Genet., 21, 20, 10.1038/4447 Zhou, 2003, Algorithms for high-density oligonucleotide array, Curr. Opin. Drug Discov. Devel., 6, 339 Schadt, 2001, Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data, J. Cell. Biochem., 37, 120, 10.1002/jcb.10073 Schadt, 2000, Analyzing high-density oligonucleotide gene expression array data, J. Cell. Biochem., 80, 192, 10.1002/1097-4644(20010201)80:2<192::AID-JCB50>3.0.CO;2-W Sasik, 2002, Statistical analysis of high-density oligonucleotide arrays: a multiplicative noise model, Bioinformatics, 18, 1633, 10.1093/bioinformatics/18.12.1633 Li, 2001, Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection, Proc. Natl. Acad. Sci. U. S. A., 98, 31, 10.1073/pnas.011404098