Comparisons and validation of statistical clustering techniques for microarray gene expression data

Bioinformatics

Volumn 19, Issue 4, 2003, Pages 459-466

  Datta, Susmita ^a   Datta, Somnath ^b  

^a GEORGIA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF GEORGIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FUNGAL DNA;

ANALYTIC METHOD; ARTICLE; BUDDING; CLUSTER ANALYSIS; CONTROLLED STUDY; CORRELATION ANALYSIS; DATA ANALYSIS; DNA MICROARRAY; GENE EXPRESSION; GENETIC ALGORITHM; INTERMETHOD COMPARISON; NONHUMAN; PERFORMANCE; PRIORITY JOURNAL; SIMULATION; SPOROGENESIS; STATISTICAL ANALYSIS; STATISTICAL MODEL; VALIDATION PROCESS; YEAST;

SACCHAROMYCETALES;

EID: 0037342510     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btg025     Document Type: Article

References (21)

1. Banfield,J.D. and Raftery,A.E. (1993) Model-based Gaussian and non-Gaussian clustering. Biometrics, 49, 803-822.
2. Brown,P.J. (1993) Measurement, Regression, and Calibration. Oxford University Press, New York.
3. Chen,G. et al., (2002) Evaluation and comparison of clustering algorithms in analyzing ES cell gene expression data. Statistica Sinica, 12, 241-262.
4. Cho,R.J. et al., (1998) A genome-wide transcriptional analysis of the mitotic cell cycle. Mol. Cell., 2, 65-73.
5. Chu,S., DeRisi,J. et al., (1998) The transcriptional program of sporulation in budding yeast. Science, 282, 699-705.
6. Datta,S. (2001) Exploring relationships in gene expressions: a partial least squares approach. Gene Expression, 9, 257-264.
7. DeRisi,J.L.. Iyer,V.R. and Brown,P.O. (1997) Exploring the metabolic and genetic control of gene expression on a genomic scale. Science, 278, 680-686.
8. Eisen,M.B., Spellman,P.T., Brown,P.O. and Botstein,D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA, 95, 14863-14868.
9. Hartigan,J.A. (1975) Clustering Algorithms. Wiley, New York.
10. Hartigan,J.A. and Wong,M.A. (1979) A k-means clustering algorithm. Applied Statistics, 28, 100-108.
11. Kaufman,L. and Rousseeuw,P.J. (1990) Fitting Groups in Data. An Introduction to Cluster Analysis. Wiley, New York.
12. Kerr,M.K. and Churchill,G.A. (2001) Bootstrapping cluster analysis: assessing the reliability of conclusions from microarray experiments. Proc. Natl Acad. Sci. USA, 98, 8961-8965.
13. Kohonen,T. (1997) Self-Organizing Maps, 2nd edn, Springer, Berlin.
14. McLachlan,G.J., Bean,R.W. and Peel,D. (2002) A mixture model-based approach to the clustering of microarray expression data. Bioinformatics, 18, 1-10.
15. Quackenbush,J. (2001) Computational analysis of microarray data. Nat. Rev. Genet., 2, 418-427.
16. Roth,F.P., Hughes,J.D., Estep,P.W. and Church,G.M. (1998) Finding DNA regulatory motifs within unaligned non-coding sequences clustered by whole-genome mRNA quantitation. Nat. Biotechnol., 16, 939-945.
17. Spellman,P.T. et al., (1998) Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol. Biol. Cell., 12, 3273-3297.
18. Stone,M. and Brooks,R.J. (1990) Continuum regression: cross-validated sequentially constructed prediction embracing ordinary least squares, partial least squares and principal component regression. J. Roy. Statist. Soc. B, 52, 237-269, Corrigendum (1992), 54, 906-907.
19. Venables,W.N. and Ripley,B.D. (1998) Modern Applied Statistics with S-Plus, (3rd corrected printing), 2nd edn, Springer, New York.
20. Waddell,P. and Kishino,H. (2000) Cluster inference methods and graphical models evaluated on NC160 microarray gene expression data. Genome Informatics, 11, 129-140.
21. Yeung,K., Haynor,D.R. and Ruzzo,W.L. (2001) Validating clustering for gene expression data. Bioinformatics, 17, 309-318.