Multi- and Megavariate Data Analysis: Finding and Using Regularities in Metabonomics Data

Metabonomics in Toxicity Assessment

Volumn , Issue , 2005, Pages 263-336

  Eriksson, Lennart ^a   Johansson, Erik ^a   Antti, Henrik ^b   Holmes, Elaine ^b  

^a Umetrics AB   (Sweden)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85091393223     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1201/b14117-11     Document Type: Chapter

References (56)

1. Nicholson JK, Connelly J, Lindon JC, Holmes E. Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev 2002; 1: 153-161.
2. Freeman R, Goodacre R, Sisson PR, Magee JG, Ward AC, Lightfoot NF. Rapid identification of species within the Mycobacterium tuberculosis complex by artificial neural network analysis of pyrolysis mass spectra. J Med Microbiol 1994; 40: 170-173.
3. Halket JM, Przyborowska A, Stein SE, Mallard WG, Down S, Chalmers RA. Deconvolution of gas chromatography=mass spectrometry of urinary organic acids-potential for pattern recognition and automated identification of metabolic disorders. Rapid Commun Mass Spectrom 1999; 13: 279-284.
4. Ramos LS. Characterisation of Mycobacteria species by HPLC and pattern recognition. J Chromatogr Sci 1994; 32: 219-227.
5. Jackson JE. A User’s Guide to Principal Components. New York: John Wiley, 1991 (ISBN 0-471-62267-2).
6. Wold S, Sjöström M, Eriksson L. PLS-regression: a basic tool of chemometrics. Chemometrics Intell Lab Systems 2001; 58: 109-130.
7. Wold S, Albano C, Dunn WJ, Edlund U, Esbensen K, Geladi P, Hellberg S, Johansson E, Lindberg W, Sjöström M. Multivariate data analysis in chemistry. In: Kowalski BR, ed. Chemometrics: Mathematics and Statistics in Chemistry. Dordrecht, Holland: D. Reidel Publishing Company, 1984.
8. Eriksson L, Johansson E, Kettaneh-Wold N, Wold S. Multiand Megavariate Data Analysis-Principles and Applications. Umetrics AB, 2001, ISBN 91-973730-1-X.
9. Wold S, Johansson E, Cocchi M. PLS. In: Kubinyi H, ed. 3DQSAR in Drug Design, Theory, Methods, and Applications. Ledien: ESCOM Science, 1993: 523-550.
10. Höskuldsson A. A combined theory for PCA and PLS. J Chemometrics 1995; 9: 91-123.
11. Wold S, Esbensen K, Geladi P. Principal component analysis. Chemometrics Intell Lab Systems 1987; 2: 37-52.
12. Wold S. Cross-validatory estimation of the number of components in factor and principal components models. Technometrics 1978; 20: 397-405.
13. Wikström C, Albano C, Eriksson L, Fridén H, Johansson E, Nordahl Å, Rännar S, Sandberg M, Kettaneh-Wold N, Wold S. Multivariate process and quality monitoring applied to an electrolysis process-Part I. Process supervision with multivariate control charts. Chemometrics Intell Lab Systems 1998; 42: 221-231.
14. Höskuldsson A. Prediction Methods in Science and Technology. Copenhagen, Denmark: Thor Publishing, 1996.
15. Wold S, Sjöström M, Eriksson L., PLS in chemistry. In: Schleyer PVR, Allinger NL, Clark T, Gasteiger J, Kollman PA, Schaefer III, HF, Schreiner PR, eds. The Encyclopedia of Computational Chemistry. Chichester: John Wiley and Sons, 1999: 2006-2020.
16. Wold S, Josefson M. (2000) In: Wold et al., eds. Multivariate Calibration of Analytical Data, Encyclopedia of Analytical Chemistry. Wiley, 1999: 1-27.
17. Wakeling IN, Morris JJ. A test of significance for partial least squares regression. J Chemometrics 1993; 7: 291-304.
18. Denham MC. Prediction intervals in partial least squares. J Chemometrics 1997; 11: 39-52.
19. Martens H, Hoy M, Westad F, Folkenberg D, Martens M. Analysis of designed experiments by stabilised PLS-regression and jack-knifing. Chemometrics Intell Lab Systems 2001; 58: 151-170.
20. Burnham AJ, Viveros R, MacGregor JF. Frameworks for latent variable multivariate regression. J Chemometrics 1996; 10: 31-45.
21. Burnham AJ, MacGregor JF, Viveros R. A statistical framework for multivariate latent variable regression methods based on maximum likelihood. J Chemometrics 1999; 13: 49-65.
22. Burnham AJ, MacGregor J, Viveros R. Interpretation of regression coefficients under a latent variable regression model. J Chemometrics 2001; 15: 265-284.
23. Efron B, Gong G. A leisurely look at the bootstrap, the Jackknife, and cross-validation. Am Statisti 1983; 37: 36-48.
24. Wold H. Soft modelling. The basic design and some extensions. In: Jöreskog KG, Wold H, eds. Systems Under Indirect Observation, Vols. I and II Amsterdam, The Netherlands: North-Holland, 1982.
25. Martens H, Martens M. Modified Jack-knife estimation of parameter uncertainty in bilinear modeling (PLSR). Food Quality Preference 2000; 11: 5-16.
26. Espina JR, Shockcor JP, Herron WJ, Car BD, Contel NR, Ciaccio PJ, Lindon JC, Holmes E, Nicholson JK. Detection of in vivo biomarkers of phospholipidosis using NMR-based metabonomic approaches. Magn Reson Chem 2001; 295(39): 559-565.
27. Smallcombe SH, Platt SL, Kaifer PA. J Magn Reson A 1995; 117: 2953.
28. Sjöström M, Wold S, Söderström B. PLS discriminant plots. Proceedings of PARC in Practice, Amsterdam, June 19-21, 1985. North-Holland: Elsevier Science Publishers B.V., 1986.
29. Ståhle L, Wold S. Partial least squares analysis with crossvalidation for the two-class problem: a Monte Carlo study. J Chemometrics 1987; 1: 185-196.
30. Coomans D, Broeckaert I, Derde MP, Tassin A, Massart DL, Wold S. Use of a microcomputer for the definition of multivariate confidence regions in medical diagnosis based on clinical laboratory profiles. Comp Biomed Res 1984; 17: 1-14.
31. Shockcor JP, Holmes E. Metabonomic applications in toxicity and disease diagnosis. Curr Topics Med Chem 2002; 2: 35-51.
32. Wold S, Kettaneh N, Fridén H, Holmberg, A. Modelling and diagnostics of batch processes and analogous kinetic experiments. Chemometrics Intell Lab Systems 1998; 44: 331-340.
33. Antti H, Bollard ME, Ebbels T, Keun H, Lindon JC, Nicholson JK, Holmes EB. Batch statistical processing of 1H NMR-derived urinary spectral data. J Chemometrics 2002; 16: 461-468.
34. Wold S, Trygg J, Berglund A, Antti H. Some recent developments in PLS modeling. Chemometrics Intell Lab Systems 2001; 58: 131-150.
35. Naes T, Isaksson T, Fearn T, Davies T. A User-friendly Guide to Multivariate Calibration and Classification. Chichester, UK: NIR Publications, 2002 (ISBN: 0-95286662-5).
36. Geladi P, MacDougall D, Martens H. Linearization and scatter-correction for near-infrared reflectance spectra of meat. Appl Spectrosc 1985; 3: 491-500.
37. Barnes RJ, Dhanoa MS, Lister SJ. Standard normal variate transformation and de-trending of near-infrared diffuse reflectance spectra. Appl Spectrosc 1989; 43: 772-777.
38. Wold S, Antti H, Lindgren F, Öhman J. Orthogonal signal correction of near-infrared spectra. Chemometrics Intell Lab Systems 1998; 44: 175-185.
39. Alsberg BK, Woodward AM, Kell DB. An introduction to wavelet transforms for chemometricians: a time-frequency approach. Chemometrics Intell Lab Systems 1997; 37: 215-239.
40. Trygg, J, Wold S. PLS regression on wavelet compressed NIR spectra. Chemometrics Intell Lab Systems 1998; 42: 209-220.
41. Savitzky A, Golay MJE. Smoothing and differentiation by simplified least squares procedures. Anal Chem 1964; 36: 1627-1632.
42. Trygg J, Wold S. Orthogonal projections to latent structures, OPLS. J Chemometrics 2002; 16: 119-128.
43. Trygg J. O2-PLS for qualitative and quantitative analysis in multivariate calibration. J Chemometrics 2002; 16: 283-293.
44. Westerhuis JA, de Jong S, Smilde AK. Direct orthogonal signal correction. Chemometrics Intell Lab Systems 2001; 56: 13-25.
45. Beckwith-Hall BM, Brindle JT, Barton R, Coen M, Holmes E, Nicholson JK, Antti H. Application of orthogonal signal correction to minimise the effects of physical and biological variation in high resolution 1H NMR spectra of biofluids. Analyst 2002; 1283-1288.
46. Eriksson L, Trygg J, Johansson E, Bro R, Wold S. Orthogonal signal correction, wavelet analysis, and multivariate calibration of complicated process fluorescence data. Anal Chim Acta Anal 2000; 420: 181-195.
47. Davis OL, Goldsmith PL. Statistical Methods in Research and Production. New York: Longman, 1986.
48. Massart DL, Vandeginste BGM, Deming SN, Michotte Y, Kaufman L. Chemometrics: A Textbook. Elsevier, 1988.
49. Wold S, Kettaneh-Wold N, Skagerberg B. Nonlinear PLS Modelling. Chemometrics Intell Lab Systems 1989; 7: 53-65.
50. Berglund A, Wold S. INLR, implicit non-linear latent variable regression. J Chemometrics 1997; 11: 141-156.
51. Eriksson L, Johansson E, Lindgren F, Wold S. GIFI-PLS: modelling of non-linearities and discontinuities in QSAR. Quantitat Struct-Activity Relationships 2000; 19: 345-355.
52. Wold S, Kettaneh-Wold N, Tjessem K. Hierarchical multiblock PLS and PC models for easier model interpretation and as an alternative to variable selection. J Chemometrics 1996; 10: 463-482.
53. Eriksson L, Johansson E, Lindgren F, Sjöström M, Wold S. Megavariate analysis of hierarchical QSAR data. J Computer-Aided Molec design. 2002; 16: 711-726.
54. Frank IE, Friedman JH. A statistical view of some chemometrics regression tools. Technometrics 1993; 35: 109-135.
55. Holmes E, Nicholson JK, Tranter G. Metabonomic characterization of genetic variations in toxicological and metabolic responses using probabilistic neural networks. Chem Res Toxicol 2001; 14(2): 182-191.
56. Parzen E. On estimation of a probability density function and mode. Ann Math Statist 1962; 33: 1065-1076.