Inferential, robust non-negative matrix factorization analysis of microarray data

Bioinformatics

Volumn 23, Issue 1, 2007, Pages 44-49

  Fogel, Paul ^a   Young, S Stanley ^b   Hawkins, Douglas M ^c   Ledirac, Nathalie ^d  

^a National Institute of Statistical Sciences ^*  (France)

^b NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES   (United States)

^c UNIVERSITY OF MINNESOTA   (United States)

^d CEMAGREF   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ACUTE GRANULOCYTIC LEUKEMIA; ACUTE LYMPHOBLASTIC LEUKEMIA; ALGORITHM; ANALYSIS OF VARIANCE; ARTICLE; BIOINFORMATICS; CLINICAL ARTICLE; COMPUTER ANALYSIS; CORRELATION ANALYSIS; DOWN REGULATION; GENE CLUSTER; GENE EXPRESSION; GENE EXPRESSION REGULATION; HUMAN; INFERENTIAL STATISTICS; MICROARRAY ANALYSIS; POISSON DISTRIBUTION; PREDICTION; PRIORITY JOURNAL; SIMULATION; STATISTICAL ANALYSIS; UPREGULATION;

EID: 33845903308     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btl550     Document Type: Article

References (25)

1. Bogni,A. et al. (2006) Genome-wide approach to identify risk factors for therapy-related myeloid leukemia. Leukemia, 20, 239-246.
2. Benjamini,Y. and Hochberg,Y. (1995) Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Statist. Soc. B, 57, 289-300.
3. Benjamini,Y. and Hochberg,Y. (2000) On the adaptive control of the false discovery rate in multiple testing with independent statistics. J. Behav. Educ. Statist., 25, 60-83.
4. Brunet,J.P. et al. (2004) Metagenes and molecular pattern discovery using matrix factorization. Proc. Natl Acad. Sci. USA, 101, 4164-4169.
5. Donoho,D. and Stodden,V. (2004) When does non-negative matrix factorization give a correct decomposition into parts? In Thrun,S., Saul,L. and Scholkopf,B. (eds), Advances in Neural Information Processing Systems 16. MIT Press, Cambridge, MA.
6. Durbin,B.P. et al. (2002) A variance-stabilizing transformation for gene-expression microarray data. Bioinformatics, 18(Suppl. 1), S105-S110.
7. Fisher,R.A. (1925) Statistical Methods for Research Workers. Hafner, New York.
8. Gabriel,K.R. and Zamir,S. (1979) Lower rank approximation of matrices by least squares with any choice of weights. Technometrics, 21, 489-498.
9. Gao,Y. and Church,G. (2005) Improving molecular cancer class discovery through sparse non-negative matrix factorization. Bioinformatics, 21, 3970-3975.
10. Golub,T.R. et al. (1999) Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science, 286, 531-537.
11. Good,I.J. (1969) Some applications of the singular decomposition of a matrix. Technometrics, 11, 823-831.
12. Hoyer,P.O. (2004) Non-negative matrix factorization with sparseness constraints. J. Mach. Learn. Res., 5, 1457-1469.
13. Ioannidis,J.P.A. (2005) Contradicted and initially stronger effects in highly cited clinical research. JAMA, 294, 218-228.
14. Kim,P.M. and Tidor,B. (2003) Subsystem identification through dimensionality reduction of large-scale gene expression data. Genome Res., 13, 1706-1718.
15. Kropf,S. and Lauter,J. (2002) Multiple tests for different sets of variables using a data-driven ordering of hypotheses, with an application to gene expression data. Biometric. J., 44, 789-800.
16. Kumatori,A. et al. (1990) Abnormally high expression of proteasomes in human leukemic cells. Proc. Natl Acad. Sci. USA, 87, 7071-7075.
17. Lee,D.D. and Seung,H.S. (1999) Learning the parts of objects by non-negative matrix factorization. Nature, 401, 788-791.
18. Liu,L. et al. (2003) Robust singular value decomposition analysis of microarray data. Proc. Natl Acad. Sci. USA, 100, 13167-13172.
19. Rothman,K.J. (1990) No adjustments are needed for multiple comparisons. Epidemiology, 1, 43-46.
20. Schabath,H. et al. (2006) CD24 affects CXCR4 function in pre-B lymphocytes and breast carcinoma cells. J. Cell Sci., 119, 314-325.
21. Spano,J.P. et al. (2005) Proteasome inhibition: A new approach for the treatment of malignancies. Bull Cancer, 92, 945-952.
22. Storey,J.D. (2002) A direct approach to false discovery rates. J. R. Statist. Soc. B, 64, 479-498.
23. Westfall,P.H. and Young,S.S. (1993) Resampling-based Multiple Testing. Wiley, New York.
24. Zhang,B., Kirov,S. and Snoddy,J. (2005) WebGestalt: An integrated system for exploring gene sets in various biological contexts. Nucleic Acids Res., 33(Web Server issue), W741-W748.
25. Zhu,M. and Ghodsi,A. (2006) Automatic dimensionality selection from the scree plot via the use of profile likelihood. Comput. Stat. Data Anal., 51, 918-930.