ANOVA–principal component analysis and ANOVA–simultaneous component analysis: A comparison

Journal of Chemometrics

Volumn 25, Issue 10, 2011, Pages 561-567

  Zwanenburg, Gooitzen ^a   Hoefsloot, Huub C J ^a   Westerhuis, Johan A ^a   Jansen, Jeroen J ^a   Smilde, Age K ^a  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

ANOVA PCA; ASCA; Metabolomics; Multivariate data analysis; Permutation tests; Proteomics

Indexed keywords

ANALYSIS OF VARIANCE (ANOVA); MOLECULAR BIOLOGY; MULTIVARIANT ANALYSIS;

ANOVA–PRINCIPAL COMPONENT ANALYSE; ANOVA–SIMULTANEOUS COMPONENT ANALYSE; COMPONENT ANALYSIS; METABOLOMICS; MULTIVARIATE DATA; MULTIVARIATE DATA ANALYSIS; PERMUTATION TESTS; PRINCIPAL COMPONENTS; PRINCIPAL-COMPONENT ANALYSIS; PROTEOMICS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84861579218     PISSN: 08869383     EISSN: 1099128X     Source Type: Journal    
DOI: 10.1002/cem.1400     Document Type: Article

References (17)

1. Sokal RR, Rohlf FJ. Biometry, The Principles and Practice of Statistics in Biological Research (3rd edn). W.H. Freeman and company: New York, 1995.
2. Ståhle L, Svante W. Analysis of variance (ANOVA). Chemom. Intell. Lab. Syst. 1989; 6: 259–272.
3. Ståhle L, Wold S. Multivariate analysis of variance (MANOVA). Chemom. Intell. Lab. Syst. 1990; 9: 127–141.
4. Smilde AK, Jansen JJ, Hoefsloot HCJ, Lamers R‐JAN, van der Greef J, Timmerman ME. ANOVA–simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data. Bioinformatics 2005; 21: 3043–3048.
5. Jansen JJ, Hoefsloot HCJ, van der Greef J, Timmerman ME, Westerhuis JA, Smilde AK. ASCA: analysis of multivariate data obtained from an experimental design. J. Chemom. 2005; 19: 469–481.
6. Harrington P de B, Vieira NE, Espinoza J, Nien JK, Romero R, Yergey AL. Analysis of variance–principal component analysis: a soft tool for proteomic discovery. Anal. Chim. Acta 2005; 544: 118–127.
7. Harrington P de B, Vieira NE, Chen P, Espinoza J, Nien JK, Romero R, Yergey AL. Proteomic analysis of amniotic fluids using analysis of variance–principal component analysis and fuzzy rule‐building expert systems applied to matrix‐assisted laser desorption/ ionization mass spectrometry. Chemom. Intell. Lab. Syst. 2006; 82: 283–293.
8. Vis DJ, Westerhuis JA, Smilde AK, van der Greef J. Statistical validation of megavariate effects in ASCA. BMC Bioinformatics 2007; 8: 322.
9. Langsrud Ø. 50–50 Multivariate analysis of variance for collinear responses. The Statistician 2002; 51(3): 305–317.
10. Anderson MJ, ter Braak CJF. Permutation tests for multi‐factorial analysis of variance. J. Stat. Comput. Simul. 2003; 73(2): 85–113.
11. Climaco-Pinto R, Barros AS, Locquet N, Schmidtke L, Rutledge DN. Improving the detection of significant factors using ANOVA–PCA by selective reduction of residual variability. Anal. Chim. Acta 2009; 653: 131–142.
12. Westerhuis JA, Hoefsloot HCJ, Smit S, Vis DJ, Smilde AK, van Velzen EJJ, van Duijnhoven JPM, van Dorsten FA. Assessment of PLSDA cross validation. Metabolomics 2008; 4: 81–89.
13. Verouden MPH, Westerhuis JA, van der Werf MJ, Smilde AK. Exploring the analysis of structured metabolomic data. Chemom. Intell. Lab. Syst. 2009; 98: 88–96.
14. Climaco-Pinto R, Bosc V, Noçairi H, Barros AS, Rutledge DN. Using ANOVA–PCA for discriminant analysis: application to the study of mid‐infrared spectra of carraghenan gels as a function of concentration and temperature. Anal. Chim. Acta 2008; 629: 47–55.
15. Jansen JJ, van Dam NM, Hoefsloot HCJ, Smilde AK. Crossfit analysis: a novel method to characterize the dynamics of induced plant responses. BMC Bioinformatics 2009; 10: 425.
16. de Haan JR, Wehrens R, Bauerschmidt S, Piek E, van Schaik RC, Buydens LMC. Interpretation of ANOVA models for microarray data using PCA. Bioinformatics 2006; 23: 184–190.
17. Gower J, Lubbe S, le Roux N. Understanding Biplots. John Wiley & Sons Ltd., Chichester UK, 2011.