SvdPPCS: An effective singular value decomposition-based method for conserved and divergent co-expression gene module identification

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  Zhang, Wensheng ^a   Edwards, Andrea ^a   Fan, Wei ^b   Zhu, Dongxiao ^c   Zhang, Kun ^a  

^a XAVIER UNIVERSITY OF LOUISIANA   (United States)

^b IBM T J WATSON RESEARCH CENTER   (United States)

^c USA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL SIGNIFICANCE; EFFECTIVE SINGULAR VALUES; EXPERIMENTAL CONDITIONS; GENE EXPRESSION PROFILING; MICROARRAY EXPERIMENTS; MODULE IDENTIFICATIONS; TIME SERIES MICROARRAYS; TRANSCRIPTIONAL PROFILING;

COMPUTATIONAL METHODS; HISTOLOGY; REGRESSION ANALYSIS; SINGULAR VALUE DECOMPOSITION; TIME SERIES; TISSUE;

GENE EXPRESSION;

ALGORITHM; ANIMAL; ANTIBODY SPECIFICITY; ARTICLE; BIOLOGY; DNA MICROARRAY; DROSOPHILA MELANOGASTER; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORK; GENETICS; HISTOLOGY; METHODOLOGY;

ALGORITHMS; ANIMALS; COMPUTATIONAL BIOLOGY; DROSOPHILA MELANOGASTER; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; ORGAN SPECIFICITY;

EID: 77953677922     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-338     Document Type: Article

References (38)

1. Su AI, Cooke MP, Ching KA, Hakak Y, Walker JR, Wiltshire T, Orth AP, Vega RG, Sapinoso LM, Moqrich A, Patapoutian A, Hampton GM, Schultz PG, Hogenesch JB. Large-scale analysis of the human and mouse transcriptomes. PNAS 2002, 99:4465-70. 10.1073/pnas.012025199, 123671, 11904358.
2. Stuart JM, Segal E, Koller D, Kim SK. A gene-coexpression network for global discovery of conserved genetic modules. Science 2003, 302:249-55. 10.1126/science.1087447, 12934013.
3. Alter O, Brown PO, Botstein D. Generalized singular value decomposition for comparative analysis of genome-scale expression data sets of two different organisms. PNAS 2003, 100:3351-3356. 10.1073/pnas.0530258100, 152296, 12631705.
4. McCarroll SA, Murphy CT, Zou S, Pletcher SD, Chin CS, Jan YN, Kenyon C, Bargmann CI, Li H. Comparing genomic expression patterns across species identifies shared transcriptional profile in aging. Nat Genet 2004, 36:197-204. 10.1038/ng1291, 14730301.
5. Ihmels J, Bergmann S, Berman J, Barkai N. Comparative gene expression analysis by differential clustering approach: application to the Candida albicans transcription program. PLoS Genet 2005, 1(3):e39. 10.1371/journal.pgen.0010039, 1239936, 16470937.
6. Ihmels J, Bergmann S, Barkai N. Defining transcription modules using large-scale gene expression data. Bioinformatics 2004, 20:1993-2003. 10.1093/bioinformatics/bth166, 15044247.
7. Li H, Sun Y, Zhan M. The discovery of transcriptional modules by a two-stage matrix decomposition approach. Bioinformatics 2007, 23:473-439. 10.1093/bioinformatics/btl640, 17189296.
8. Wang X, Dalkic E, Wu M, Chan C. Gene module level analysis: identification to networks and dynamics. Curr Opin Biotechnol 2008, 19:482-491. 10.1016/j.copbio.2008.07.011, 2615490, 18725293.
9. Mao L, Van Hemert JL, Dash S, Dickerson JA. Arabidopsis gene co-expression network and its functional modules. BMC Bioinformatics 2009, 10:e346.
10. Loor JJ, Dann HM, Everts RE, Oliveira R, Green CA, Guretzky NA, Rodriguez-Zas SL, Lewin HA, Drackley JK. Temporal gene expression profiling of liver from periparturient dairy cows reveals complex adaptive mechanisms in hepatic function. Physiol Genomics 2005, 23:217-26. 10.1152/physiolgenomics.00132.2005, 16091418.
11. Alter O, Brown PO, Botstein D. Singular value decomposition for genome-wide expression data processing and modeling. PNAS 2000, 97:10101-06. 10.1073/pnas.97.18.10101, 27718, 10963673.
12. Holter NS, Mitra M, Maritan A, Cieplak M, Banavar JR, Fedoroff NV. Fundamental patterns underlying gene expression profiles: simplicity from complexity. PNAS 2000, 97:8409-14. 10.1073/pnas.150242097, 26961, 10890920.
13. Hastie T, Tibshirani R, Eisen MB, Alizadeh A, Levy R, Staudt L, Chan WC, Botstein D, Brown P. 'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns. Genome Biol 2000, 1(2):RESEARCH0003. 10.1186/gb-2000-1-2-research0003, 15015, 11178228.
14. Wall ME, Dyck PA, Brettin TS. SVDMAN--singular value decomposition analysis of microarray data. Bioinformatics 2001, 17:566-568. 10.1093/bioinformatics/17.6.566, 11395437.
15. Zhu D. Semi-supervised gene shaving method for predicting low variation biological pathways from genome-wide data. BMC Bioinformatics 2009, 10(Suppl 1):S54. 10.1186/1471-2105-10-S1-S54, 2648790, 19208157.
16. Zhang W, Rekaya R, Bertrand K. A method for predicting disease subtypes in presence of misclassification among training samples using gene expression: application to human breast cancer. Bioinformatics 2006, 22:317-325. 10.1093/bioinformatics/bti738, 16267079.
17. Liu L, Hawkins DM, Ghosh S, Young SS. Robust singular value decomposition analysis of microarray data. PNAS 2003, 100:13167-72. 10.1073/pnas.1733249100, 263735, 14581611.
18. Wall ME, Rechtsteiner A, Rocha LA. Singular value decomposition and principal component analysis. A Practical Approach to Microarray Data Analysis 2003, 91-109. Kluwer, Norwell, MA, Berrar DP, Dubitzky W, Granzow M.
19. Zhang L, Marron JS, Shen H, Zhu Z. Singular value decomposition and its visualization. Journal of Computational and Graphical Statistics 2007, 16(4):833-854.
20. Householder AS, Young G. Matrix Approximations and Latent Roots. American mathematical Monthly 1938, 45:165-171.
21. Troyanskaya O, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D, Altman RB. Missing value estimation methods for DNA microarrays. Bioinformatics 2001, 17:520-525. 10.1093/bioinformatics/17.6.520, 11395428.
22. Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, Speed TP. Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res 2002, 30(4):e15. 10.1093/nar/30.4.e15, 100354, 11842121.
23. Bolstad BM, Irizarry RA, Astrand M, Speed TP. A Comparison of Normalization Methods for High Density Oligonucleotide Array Data Based on Bias and Variance. Bioinformatics 2003, 19:185-193. 10.1093/bioinformatics/19.2.185, 12538238.
24. Zahn JM, Sonu R, Vogel H, Crane E, Mazan-Mamczarz K, Rabkin R, Davis RW, Becker KG, Owen AB, Kim SK. Transcriptional profiling of aging in human muscle reveals a common aging signature. PLoS Genet 2006, 2(7):e115. 10.1371/journal.pgen.0020115, 1513263,1513263, 16789832.
25. Zhang W, Zou S, Song J. Term-tissue specific models for prediction of gene ontology biological processes using transcriptional profiles of aging in drosophila melanogaster. BMC Bioinformatics 2008, 9:e129.
26. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nature Protoc 2009, 4:44-57.
27. Miquel J, Economos AC, Fleming J, Johnson JE. Mitochondrial role in cell aging. Exp Gerontol 1980, 15:575-591. 10.1016/0531-5565(80)90010-8, 7009178.
28. Ozawa T. Genetic and functional changes in mitochondria associated with aging. Physiol Rev 1997, 77:425-464.
29. Genova ML, Bianchi C, Lenaz G. Structural organization of the mitochondrial respiratory chain. Ital J Biochem 2003, 52:58-61.
30. Rea SL, Ventura N, Johnson TE. Relationship between mitochondrial electron transport chain dysfunction, development, and life extension in Caenorhabditis elegans. PLoS Biol 2007, 5(10):e259. 10.1371/journal.pbio.0050259, 1994989,1994989, 17914900.
31. Storey JD, Xiao W, Leek JT, Tompkins RG, Davis RW. Significance analysis of time course microarray experiments. PNAS 2005, 102(36):12837-42. 10.1073/pnas.0504609102, 1201697, 16141318.
32. Kaufman L, Rousseeuw P. Finding Groups in Data: An Introduction to Cluster Analysis. 1990, Wiley, New York.
33. Rousseeuw PJ. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics 1987, 20:53-65.
34. Sun Y, Li H, Liu Y, Mattson MP, Rao MS, Zhan M. Evolutionarily conserved transcriptional co-expression guiding embryonic stem cell differentiation. PLoS One 2008, 3(10):e3406. 10.1371/journal.pone.0003406, 2566604, 18923680.
35. Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. PNAS 1998, 95(25):14863-68. 10.1073/pnas.95.25.14863, 24541, 9843981.
36. Ramaswamy S, Tamayo P, Rifkin R, Mukherjee S, Yeang CH, Angelo M, Ladd C, Reich M, Latulippe E, Mesirov JP, Poggio T, Gerald W, Loda M, Lander ES, Golub TR. Multiclass cancer diagnosis using tumor gene expression signatures. PNAS 2001, 98:15149-54. 10.1073/pnas.211566398, 64998, 11742071.
37. Keerthikumar S, Bhadra S, Kandasamy K, Raju R, Ramachandra YL, Bhattacharyya C, Imai K, Ohara O, Mohan S, Pandey A. Prediction of candidate primary immunodeficiency disease genes using a support vector machine learning approach. DNA Res 2009, 16:345-51. 10.1093/dnares/dsp019, 2780952, 19801557.
38. Zhang W, Robbins K, Wang Y, Bertrand K, Rekaya R. A jackknife-like method for classification and uncertainty assessment of multi-category tumor samples using gene expression information. BMC Genomics 2010, 11:273. 10.1186/1471-2164-11-273, 2876124, 20429942.