DigOut: viewing differential expression genes as outliers.
作者： HUI YU , KANG TU , LU XIE , YUAN-YUAN LI
DOI: 10.1142/S0219720010005208
关键词:
摘要: With regards to well-replicated two-conditional microarray datasets, the selection of differentially expressed (DE) genes is a well-studied computational topic, but for multi-conditional datasets with limited or no replication, same task not properly addressed by previous studies. This paper adopts multivariate outlier analysis analyze replication-lacking finding that it performs significantly better than widely used limit fold change (LFC) model in simulated comparative experiment. Compared LFC model, also demonstrates improved stability against sample variations series manipulated real expression datasets. The reanalysis non-replicated dataset leads satisfactory results. In conclusion, algorithm, like DigOut, particularly useful selecting DE from gene dataset.
researchgate.net 
sci-hub.se 参考文章(44)
E. Pennisi, DNA Chips Give New View of Classic Test Science. ,vol. 283, pp. 17- 18 ,(1999) , 10.1126/SCIENCE.283.5398.17
K. H. Rubins, L. E. Hensley, P. B. Jahrling, A. R. Whitney, T. W. Geisbert, J. W. Huggins, A. Owen, J. W. LeDuc, P. O. Brown, D. A. Relman, The host response to smallpox: Analysis of the gene expression program in peripheral blood cells in a nonhuman primate model Proceedings of the National Academy of Sciences of the United States of America. ,vol. 101, pp. 15190- 15195 ,(2004) , 10.1073/PNAS.0405759101
Victor E Velculescu, Stephen L Madden, Lin Zhang, Alex E Lash, Jian Yu, Carlo Rago, Anita Lal, Clarence J Wang, Gary A Beaudry, Kristin M Ciriello, Brian P Cook, Michael R Dufault, Anne T Ferguson, Yuhong Gao, Tong-Chuan He, Heiko Hermeking, Siewleng K Hiraldo, Paul M Hwang, Marissa A Lopez, Hilary F Luderer, Brynna Mathews, Joseph M Petroziello, Kornelia Polyak, Leigh Zawel, Wen Zhang, Xiaoming Zhang, Wei Zhou, Frank G Haluska, Jin Jen, Saraswati Sukumar, Gregory M Landes, Gregory J Riggins, Bert Vogelstein, Kenneth W Kinzler, Analysis of human transcriptomes Nature Genetics. ,vol. 23, pp. 387- 388 ,(1999) , 10.1038/70487
J. Bruce German, Matthew-Alan Roberts, Steven M. Watkins, Genomics and Metabolomics as Markers for the Interaction of Diet and Health: Lessons from Lipids Journal of Nutrition. ,vol. 133, pp. 2078- 2083 ,(2003) , 10.1093/JN/133.6.2078S
Patrick O. Brown, David Botstein, Exploring the new world of the genome with DNA microarrays Nature Genetics. ,vol. 21, pp. 33- 37 ,(1999) , 10.1038/4462
Katrien Van Driessen, Peter J. Rousseeuw, A fast algorithm for the minimum covariance determinant estimator Technometrics. ,vol. 41, pp. 212- 223 ,(1999) , 10.2307/1270566
Douglas T Ross, Uwe Scherf, Michael B Eisen, Charles M Perou, Christian Rees, Paul Spellman, Vishwanath Iyer, Stefanie S Jeffrey, Matt Van de Rijn, Mark Waltham, Alexander Pergamenschikov, JC Lee, Deval Lashkari, Dari Shalon, Timothy G Myers, John N Weinstein, David Botstein, Patrick O Brown, None, Systematic variation in gene expression patterns in human cancer cell lines. Nature Genetics. ,vol. 24, pp. 227- 235 ,(2000) , 10.1038/73432
Ju-Seog Lee, In-Sun Chu, Arsen Mikaelyan, Diego F Calvisi, Jeonghoon Heo, Janardan K Reddy, Snorri S Thorgeirsson, Application of comparative functional genomics to identify best-fit mouse models to study human cancer. Nature Genetics. ,vol. 36, pp. 1306- 1311 ,(2004) , 10.1038/NG1481
F. Bertucci, F. Eisinger, R. Tagett, H. Sobol, D. Birnbaum, Re: Gene Expression Profiles of BRCA1-Linked, BRCA2-Linked, and Sporadic Ovarian Cancers Journal of the National Cancer Institute. ,vol. 94, pp. 1506- 1507 ,(2002) , 10.1093/JNCI/94.19.1506
Trey Ideker, Vesteinn Thorsson, Andrew F. Siegel, Leroy E. Hood, Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data. Journal of Computational Biology. ,vol. 7, pp. 805- 817 ,(2000) , 10.1089/10665270050514945