Matrix correlations for high-dimensional data: The modified RV-coefficient

Bioinformatics

Volumn 25, Issue 3, 2009, Pages 401-405

  Smilde, A K ^a   Kiers, H A L ^b   Bijlsma, S ^c   Rubingh, C M ^c   Van Erk, M J ^c  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b UNIVERSITY OF GRONINGEN   (Netherlands)

^c TNO   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BIOINFORMATICS; CONTROLLED STUDY; CORRELATION COEFFICIENT; DATA ANALYSIS; FUNCTIONAL GENOMICS; MATRIX CORRELATION; METABOLOMICS; NONHUMAN; PRIORITY JOURNAL; RV COEFFICIENT; SIMULATION; STATISTICAL ANALYSIS; THEORY; TRANSCRIPTOMICS;

EID: 59549100948     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btn634     Document Type: Article

References (13)

1. Alter,O. et al. (2003) Generalized singular value decomposition for comparative analysis of genome-scale expression data sets of two different organisms. Proc. Natl Acad. Sci. USA, 100, 3351-3356.
2. Bro,R. and Smilde,A. (2003) Centering and scaling in component analysis. J. Chemometr., 17, 16-33.
3. Kazi-Aoual,F. et al. (1995) Refined approximations to permutation tests for multivariate inference. Comput. Statist. Data Anal., 20, 643-656.
4. Kleeman,R. et al. (2007) Increased dietary cholesterol-induced atherosclerosis is associated with liver inflammation: Identification of novel regulatory pathways and transcriptional regulators involved in switch from metabolic adaptation to inflammatory state. Gen. Biol. 8, R200.
5. Lorenzo-Seva,U. and Ten Berge,J.M.F. (2006) Tucker's congruence coefficient as a meaningful index of factor similarity. Methodology 2, 57-64.
6. Mood,A.M. et al. (1974) Introduction to the Theory of Statistics. McGraw-Hill Kogakusha Ltd, Tokyo.
7. Ramsay,J.O. et al. (1984) Matrix correlation. Psychometrika, 49, 403-423.
8. Robert,P. and Escoufier,Y. (1976) A unifying tool for linear multivariate statistical methods: The rv-coefficient. Appl. Stat., 25, 257-265.
9. Smilde,A.K. et al. (2003) A framework for sequential multiblock component methods. J. Chemometr., 17, 323-337.
10. Smilde,A.K. et al. (2005a) Anova-simultaneous component analysis (asca): A new tool for analyzing designed metabolomics data. Bioinformatics, 21, 3043-3048.
11. Smilde,A.K. et al. (2005b) Fusion of mass-spectrometry based metabolomics data. Anal. Chem., 77, 6729-6736.
12. van den Berg,R. et al. (2006) Centering, scaling, and transformations: Improving the biological information content of metabolomics data. BMC Genomics, 7, 142.
13. Yanai,H. (1974) Unification of various techniques of multivariate analysis by means of generalized coefficient of determination (ged). J. Behaviormetr., 1, 45-54.