E-learning in analysis of genomic and proteomic data 2. Data analysis 2.2. Analysis of high-density genomic data 2.2.1. DNA microarrays Meta-analysis of microarray experiments


Cahan, P., Rovegno, F., Mooney, D., Newman, J. C., St. Laurent, G. III, a McCaffrey, T. A. 2007, ‘Meta-analysis of microarray results: challenges, opportunities, and recommendations for standardization‘, Gene, vol. 401, issuses 1-2, pp. 12-18

Choi, H., Shen, R., Chinnaiyan, A. M. a Ghosh, D. 2007, ‘A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments‘, BMC Bioinformatics 2007, vol. 8:364

Choi, J.K., Choi, J.Y., Kim, D.G, Choi, D.W., Kim, B.Y., Lee, K. H., Yeom, J.I., Yoo, H. S., Yoo, O.J. a Kim, S. 2004, ‘Integrative analysis of multiple gene expression profiles applied to liver cancer study‘, FEBS Letters , vol. 565, pp.93–100

Choi, J.K., Yu, U., Kim, S. and Yoo, O.J. 2003, ‘Combining multiple microarray studies and modeling interstudy variation’, Bioinformatics, Vol. 19, Suppl. 1, 2003, pp. i84-i90

Conlon, E. M. 2007, ‘A Bayesian mixture model for meta analysis of microarray studies‘, Funct Integr Genomics, vol. 8, pp. 43-53

Conlon, E. M., Song, J. J. a Liu, J. S. 2006, ‘Bayesian models for pooling microarray studies with multiple sources of replications‘, BMC Bioinformatics 2006, vol. 7:247

Conlon, E. M., Song, J.J., Liu, A. 2007, ‘Bayesian meta-analysis models for microarray data: a comparative study‘, BMC Bioinformatics 2007, vol. 8:80

Conway, A.R. 2003, „GeneSpring (version 6.1)“, Silicon Genetics, Redwood City, CA

Geman, D., d'Avignon, Ch., Naiman, D. Q. a Winslow, R.L. 2004, ‘Classifying Gene Expression Profiles from Pairwise mRNA Comparisons‘, Stat Appl Genet Mol Biol. 2004 ; vol. 3: Article19

Ghosh, D., Barette, T. R., Rhodes, D. a Chinanaiyan A. M. 2003, ‘Statistical issues and methods for meta-analysis of microarray data: a case study in prostate cancer‘, Funct Integr Genomics, vol. 3, pp. 180–188

Hastie, T., Tibshirani, R., Eisen, M.B., Alizadeh, A., Levy, R., Staudt, L., Chan, W.C., Bootstein, D. and Brown, P. 2000, ‘’Gene shaving’ as a method for identifying distinct sets of genes with similar expression patterns’, Genome Biology 2000, 1(2):research 0003.1-0003.21

Hedges, L.V. and Olkin, I. 1985, ‘Statistical Methods for Metaanalysis‘, Academic Press, Orlando

Jarvinen, A.K., Hautaniemi, S., Edgren, H., Auvinen, P., Saarela, J., Kallioniemi, O.P., Monni, O. 2004, ‘Are data from different gene expression microarray platform comparable’, Genomics 2004, vol. 83, pp. 1164-1168

Jiang, H., Deng, Y., Chen, H-S., Tao, L., Sha, Q., Chen, J., Tsai, Ch-J. a Zhang, S. 2004, ‘Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes‘, BMC Bioinformatics, vol. 5:81

Jong, K., Marchiori, E., Meijer, G., Vaart, A.V. a Ylstra, B. 2004, ‘Breakpoint identification and smoothing of array comparative genomic hybridization data‘, Bioinformatics, vol. 20, pp. 3636–3637

Kuo, W.P., Jensen, T-K., Butte, A.J., Ohno-Machado, L. and Kohane I.S. 2002, ‘Analysis of matched mRNA measurements from two different microarray technologies’, Bioinformatics, vol. 18, pp. 405-412

Lunn, D.J., Thomas, A., Best, N., a Spiegelhalter, D. 2000, ‘WinBUGS -- a Bayesian modelling framework: concepts, structure, and extensibility‘, Statistics and Computing, vol. 10, pp. 325-337

Park, T., Yi, S.G., Shin, Y. K. a Lee, S. Y. 2006, ‘Combining multiple microarrays in the presence of controlling variables‘, Bioinformatics, vol. 22 no. 14 2006, pp. 1682–1689

R Development Core Team 2007, ‘R: A language and environment for statistical computing‘ R Foundation for Statistical Computing, Vienna, Austria

Rhodes, D. R., Yu, J., Shanker, K., Deshpande, N., Varambally, R., Ghosh, D., Barrette, T., Pandey, A. a Chinnaiyan, A. M. 2004, ‘Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression’, PNAS, vol. 101, no. 25, pp. 9309-9314

Rhodes, D.R., Barrette, T.R., Rubin, M. A., Ghosh, D. a Chinnaiyan, A. M. 2002, ‘Meta-Analysis of Microarrays: Interstudy Validation of Gene Expression Profiles Reveals Pathway Dysregulation in Prostate Cancer‘, CANCER RESEARCH 62, pp: 4427-4433

Smid, M., Dorssers, L. C. J. a Jenster, G. 2003, ‘Venn Mapping: clustering of heterologous microarray data based on the number of co-occurring differentially expressed genes‘, Bioinformatics, vol. 19 no. 16 2003, pp. 2065–2071

Stevens, J.R. and Doerge, R.W. 2005, ‘Combining Affymetrix microarray results’, BMC Bioinformatics, vol. 6:57

Tibshirani R. 1996, ‘Regression shrinkage and selection via the lasso‘, J. Royal. Statist. Soc B., vol. 58, no. 1, pp. 267-288

Wang, J., Coombes, K. R., Highsmith, W. E., Keating, M. J. a Abruzzo, L. V. 2004, ‘Differences in gene expression between B-cell chronic lymphocytic leukemia and normal B cells: a meta-analysis of three microarray studies‘, Bioinformatics, vol. 20, no. 17 2004, pp. 3166-3178

Yang, X., Bentink, S. a Spang, R. 2005, ‘Detecting Common Gene Expression Patterns in Multiple Cancer Outcome Entities‘, Biomedical Microdevices, vol.7:3, pp. 247–251

Yang, X., Bentink, S., Scheid, S. a Spang, R. 2006, ‘Similarities of ordered gene lists‘, Journal of Bioinformatics and Computational Biology, vol. 4, issue 3, pp. 693-708

Zhang, Z. a Fenstermacher D. 2005, ‘An Introduction to MAMA (Meta-Analysis of MicroArray data) System‘, 27th Annual International Conference of the Engineering in Medicine and Biology Society, pp. 7730 - 7733