Two-way analysis of high-dimensional collinear data

Data Mining and Knowledge Discovery

Volumn 19, Issue 2, 2009, Pages 261-276

  Huopaniemi, Ilkka ^a   Suvitaival, Tommi ^a   Nikkilä, Janne ^a,b   Orešič, Matej ^c   Kaski, Samuel ^a  

^a AALTO UNIVERSITY   (Finland)

^b UNIVERSITY OF HELSINKI   (Finland)

^c VTT TECHNICAL RESEARCH CENTRE OF FINLAND   (Finland)

Author keywords

ANOVA; Factor analysis; Hierarchical model; Metabolomics; Multi way analysis; Small sample size

Indexed keywords

ANOVA; FACTOR ANALYSIS; HIERARCHICAL MODEL; METABOLOMICS; MULTI-WAY ANALYSIS; SMALL SAMPLE-SIZE;

BAYESIAN NETWORKS; HIERARCHICAL SYSTEMS;

ANALYSIS OF VARIANCE (ANOVA);

EID: 68749092565     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-009-0142-5     Document Type: Article

References (23)

1. Archambeau C, Bach F (2009) Sparse probabilistic projections. In: Koller D, Schuurmans D, Bengio Y, Bottou L (eds) Advances in neural information processing systems, vol 21. MIT Press, Cambridge, pp 73-80
2. Beal M, Krishnamurthy P (2006) Gene expression time course clustering with countably infinite hidden markov models. In: Proceedings of the 22nd annual conference on uncertainty in artificial intelligence (UAI-06), Arlington, Virginia. AUAI Press
3. Y Benjamini Y Hochberg 1995 Controlling the false discovery rate: a practical and powerful approach to multiple testing J R Stat Soc Ser B (Methodological) 57 1 289 300
4. Bishop CM (1999) Bayesian PCA. In: Proceedings of the 1998 conference on advances in neural information processing systems II. MIT Press, Cambridge, pp 382-388
5. Cao G, Bouman CA (2009) Covariance estimation for high dimensional data vectors using the sparse matrix transform. In: Koller D, Schuurmans D, Bengio Y, Bottou L (eds) Advances in neural information processing systems, vol 21. MIT Press, Cambridge, pp 225-232
6. G Celeux O Martin C Lavergne 2005 Mixture of linear mixed models for clustering gene expression profiles from repeated microarray experiments Stat Model 5 3 243 267
7. Gelman A, Carlin JB, Stern HS, Rubin DB (2003) Bayesian data analysis, 2nd edn. Chapman & Hall/CRC, London
8. Ghahramani Z, Beal MJ (2000) Variational inference for Bayesian mixtures of factor analysers. In: Advances in neural information processing systems, vol 12. MIT Press, Cambridge, pp 449-455
9. O Langsrud 2002 50-50 multivariate analysis of variance for collinear responses J R Stat Soc Ser D-the Statistician 51 305 317
10. SK Ng GJ McLachlan K Wang L Ben-Tovim Jones SW Ng 2006 A mixture model with random-effects components for clustering correlated gene-expression profiles Bioinformatics 22 14 1745 1752
11. Nikkila J, Sysi-Aho M, Ermolov A, Seppnen-Laakso T, Simell O, Kaski S, Oresic M (2008) Gender-dependent progression of systemic metabolic states in early childhood. Mol Syst Biol 4(197). doi: 10.1038/msb.2008.34 (Pubitemid 351787185)
12. M Oresic S Simell M Sysi-Aho K Nanto-Salonen T Seppanen-Laakso V Parikka M Katajamaa A Hekkala I Mattila P Keskinen L Yetukuri A Reinikainen J Lahde T Suortti J Hakalax T Simell H Hyoty R Veijola J Ilonen R Lahesmaa M Knip O Simell 2008 Dysregulation of lipid and amino acid metabolism precedes islet autoimmunity in children who later progress to type 1 diabetes J Exp Med 205 13 2975 2984
13. Rowe DB (2000) On estimating the mean in Bayesian factor analysis. In: Social science working paper 1096, division of humanities and social sciences, Caltech, Pasadena, CA 91125
14. S Roweis Z Ghahramani 1999 A unifying review of linear Gaussian models Neural Comput 11 2 305 345
15. G Sanguinetti J Noirel PC Wright 2008 MMG: a probabilistic tool to identify submodules of metabolic pathways Bioinformatics 24 8 1078 1084
16. DM Seo PJ Goldschmidt-Clermont M West 2007 Of mice and men: sparse statistical modelling in cardiovascular genomics Ann Appl Stat 1 1 152 178
17. AK Smilde JJ Jansen HCJ Hoefsloot RJAN Lamers J van der Greef ME Timmerman 2005 ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data Bioinformatics 21 13 3043 3048
18. R Steuer 2006 Review: On the analysis and interpretation of correlations in metabolomic data Brief Bioinform 7 2 151 158
19. F Tai W Pan 2007 Incorporating prior knowledge of gene functional groups into regularized discriminant analysis of microarray data Bioinformatics 23 23 3170 3177
20. D Vis J Westerhuis A Smilde J van der Greef 2007 Statistical validation of megavariate effects in ASCA BMC Bioinform 8 1 322
21. L Wang B Zhang RD Wolfinger X Chen 2008 An integrated approach for the analysis of biological pathways using mixed models PLoS Genet 4 7 e1000115
22. M West 2003 Bayesian factor regression models in the large p, small n paradigm Bayesian Stat 7 723 732
23. J Westerhuis H Hoefsloot S Smit D Vis A Smilde E van Velzen J van Duijnhoven F van Dorsten 2008 Assessment of plsda cross validation Metabolomics 4 1 81 89