Analysis of -omics data: Graphical interpretation- and validation tools in multi-block methods

Chemometrics and Intelligent Laboratory Systems

Volumn 104, Issue 1, 2010, Pages 140-153

  Hassani, Sahar ^a,b   Martens, Harald ^a,b   Qannari, El Mostafa ^c   Hanafi, Mohamed ^c   Borge, Grethe Iren ^a   Kohler, Achim ^a  

^a NOFIMA   (Norway)

^b NORWEGIAN UNIVERSITY OF LIFE SCIENCES   (Norway)

^c LUNAM UNIVERSITÉ   (France)

Author keywords

Multi block methods; Omics data; Validation tools

Indexed keywords

ACCURACY; ANALYTIC METHOD; ARTICLE; BIOMICS; CONSENSUS; DATA ANALYSIS; HIGH THROUGHPUT SCREENING; MATHEMATICAL COMPUTING; MATHEMATICAL PARAMETERS; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SCORING SYSTEM; STATISTICAL ANALYSIS; STATISTICAL PARAMETERS; STUDENT T TEST; VALIDATION PROCESS;

EID: 78650178785     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chemolab.2010.08.008     Document Type: Article

References (57)

1. Emilien G., Ponchon M., Caldas C., Isacson O., Maloteaux J.M. Impact of genomics on drug discovery and clinical medicine. QJM 2000, 93(7):391-423.
2. Rothschild M.F., Plastow G.S. Impact of genomics on animal agriculture and opportunities for animal health. Trends in Biotechnology 2008, 26(1):21-25.
3. Georges M. Recent progress in livestock genomics and potential impact on breeding programs. Theriogenology 2001, 55(1):15-21.
4. Salmeron J., Herrera-Estrella L.R. Plant biotechnology: fast-forward genomics for improved crop production. Current Opinion in Plant Biology 2006, 9(2):177-179.
5. Cunningham M.J. Genomics and proteomics: The new millennium of drug discovery and development. Journal of Pharmacological and Toxicological Methods 2000, 44(1):291-300.
6. Sinha A., Singh C., Parmar D., Singh M.P. Proteomics in clinical interventions: achievements and limitations in biomarker development. Life Sciences 2007, 80(15):1345-1354.
7. Colantonio D.A., Chan D.W. The clinical application of proteomics. Clinica Chimica Acta 2005, 357(2):151-158.
8. Anderson N.L., Matheson A.D., Steiner S. Proteomics: applications in basic and applied biology. Current Opinion in Biotechnology 2000, 11(4):408-412.
9. Nicholson J.K., Lindon J.C. Systems biology: metabonomics. Nature 2008, 455(7216):1054-1056.
10. Kell D.B. Systems biology, metabolic modelling and metabolomics in drug discovery and development. Drug Discovery Today 2006, 11(23-24):1085-1092.
11. Stenlund H., Madsen R., Vivi A., Calderisi M., Lundstedt T., Tassini M., Carmellini M., Trygg J. Monitoring kidney-transplant patients using metabolomics and dynamic modeling. Chemometrics and Intelligent Laboratory Systems 2009, 98(1):45-50.
12. Lewis G.D., Asnani A., Gerszten R.E. Application of metabolomics to cardiovascular biomarker and pathway discovery. Journal of the American College of Cardiology 2008, 52(2):117-123.
13. Naylor S., Culbertson A.W., Valentine S.J. Towards a systems level analysis of health and nutrition. Current Opinion in Biotechnology 2008, 19(2):100-109.
14. Kim H., Page G.P., Barnes S. Proteomics and mass spectrometry in nutrition research. Nutrition 2004, 20(1):155-165.
15. Rezzi S., Ramadan Z., Fay L.B., Kochhar S. Nutritional metabonomics: applications and perspectives. Journal of Proteome Research 2007, 6(2):513-525.
16. Wishart D.S. Metabolomics: applications to food science and nutrition research. Trends in Food Science and Technology 2008, 19(9):482-493.
17. Vos P., Hogers R., Bleeker M., Reijans M., Lee T.V.D., Hornes M., Friters A., Pot J., Paleman J., Kuiper M., Zabeau M. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Research 1995, 23(21):4407-4414.
18. Owens J. Ian Humphery-Smith on current challenges in proteomics. Targets 2003, 2(1):10-13.
19. Jamesdaniel S., Salvi R., Coling D. Auditory proteomics: methods, accomplishments and challenges. Brain Research 2009, 1277:24-36.
20. Wu H., Southam A.D., Hines A., Viant M.R. High-throughput tissue extraction protocol for NMR- and MS-based metabolomics. Analytical Biochemistry 2008, 372(2):204-212.
21. Werner E., Heilier J.-F., Ducruix C., Ezan E., Junot C., Tabet J.-C. Mass spectrometry for the identification of the discriminating signals from metabolomics: current status and future trends. Journal of Chromatography B 2008, 871(2):143-163.
22. Wishart D.S. Quantitative metabolomics using NMR. TrAC, Trends in Analytical Chemistry 2008, 27(3):228-237.
23. Kumar C., Mann M. Bioinformatics analysis of mass spectrometry-based proteomics data sets. FEBS Letters 2009, 583(11):1703-1712.
24. Harrigan G.G., LaPlante R.H., Cosma G.N., Cockerell G., Goodacre R., Maddox J.F., Luyendyk J.P., Ganey P.E., Roth R.A. Application of high-throughput Fourier-transform infrared spectroscopy in toxicology studies: contribution to a study on the development of an animal model for idiosyncratic toxicity. Toxicology Letters 2004, 146:197-205.
25. Lay J.J.O., Liyanage R., Borgmann S., Wilkins C.L. Problems with the "omics". TrAC, Trends in Analytical Chemistry 2006, 25(11):1046-1056.
26. Rocke D.M. Design and analysis of experiments with high throughput biological assay data. Seminars in Cell & Developmental Biology 2004, 15(6):703-713.
27. Hoefsloot H.C.J., Vis D.J., Westerhuis J.A., Smilde A.K., Jansen J.J. Multiset data analysis: ANOVA simultaneous component analysis and related methods. Comprehensive Chemometrics 2009, 453-472. Elsevier, Oxford. S. Brown, R. Tauler, R. Walczak (Eds.).
28. Sarembaud J., Pinto R., Rutledge D.N., Feinberg M. Application of the ANOVA-PCA method to stability studies of reference materials. Analytica Chimica Acta 2007, 603(2):147-154.
29. Climaco Pinto R., Bosc V., Noçairi H., Barros A.S., Rutledge D.N. Using ANOVA-PCA for discriminant analysis: application to the study of mid-infrared spectra of carraghenan gels as a function of concentration and temperature. Analytica Chimica Acta 2008, 629(1-2):47-55.
30. Fostel J.M. Towards standards for data exchange and integration and their impact on a public database such as CEBS (Chemical Effects in Biological Systems). Toxicology and Applied Pharmacology 2008, 233(1):54-62.
31. Aderem A. Systems biology: its practice and challenges. Cell 2005, 121(4):511-513.
32. Færgestad E.M., Langsrud Ø., Høy M., Hollung K., Sæbø S., Liland K.H., Kohler A., Gidskehaug L., Almergren J., Anderssen E., Martens H. Analysis of megavariate data in functional genomics. Comprehensive Chemometrics 2009, 221-278. Elsevier, Oxford. S. Brown, R. Tauler, R. Walczak (Eds.).
33. Millar C.D., Huynen L., Subramanian S., Mohandesan E., Lambert D.M. New developments in ancient genomics. Trends in Ecology & Evolution 2008, 23(7):386-393.
34. Smilde A.K., van der Werf M.T.J., Bijlsma S., van der Werff-van der Vat B.J.C., Jellema R.H. Fusion of mass spectrometry-based metabolomics data. Analytical Chemistry 2005, 77(20):6729-6736.
35. Lindon J.C., Holmes E., Nicholson J.K. Global systems biology through integration of "omics" results. The Handbook of Metabonomics and Metabolomics 2007, 533-555. Elsevier Science B.V., Amsterdam. J.C. Lindon, J.K. Nicholson, E. Holmes (Eds.).
36. Meyer K., Suter-Dick L., Amberg A., Gautier J.-C., Wendt M., Riefke B., Sutter A., Raschke M., Gmuender H. S08: The challenge of integrating different "omics" technologies. Experimental and Toxicologic Pathology 2009, 61(3):260.
37. Orei M., Clish C.B., Davidov E.J., Verheij E., Vogels J., Havekes L.M., Neumann E., Adourian A., Naylor S., Jan van der G., Plasterer T. Phenotype characterisation using integrated gene transcript, protein and metabolite profiling. Applied Bioinformatics 2004, 3:205-217.
38. Martens H., Næs T. Multivariate calibration. I. Concepts and distinctions. TrAC, Trends in Analytical Chemistry 1984, 3(8):204-210.
39. Martens H., Næs T. Multivariate calibration 1989, Wiley & Sons, Chichester.
40. Martens H., Martens M. Multivariate analysis of quality: an introduction 2001, Wiley, Chichester, UK.
41. Tyssø V., Esbensen K., Martens H. UNSCRAMBLER, an interactive program for multivariate calibration and prediction. Chemometrics and Intelligent Laboratory Systems 1987, 2(1-3):239-243.
42. Höskuldsson A., Svinning K. Modelling of multi-block data. Journal of Chemometrics 2006, 20(8-10):376-385.
43. Geladi P. Analysis of multi-way (multi-mode) data. Chemometrics and Intelligent Laboratory Systems 1989, 7(1-2):11-30.
44. van Velzen E.J.J., Westerhuis J.A., van Duynhoven J.P.M., van Dorsten F.A., Hoefsloot H.C.J., Jacobs D.M., Smit S., Draijer R., Kroner C.I., Smilde A.K. Multilevel data analysis of a crossover designed human nutritional intervention study. Journal of Proteome Research 2008, 7(10):4483-4491.
45. Westerhuis J.A., Kourti T., MacGregor J.F. Analysis of multiblock and hierarchical PCA and PLS models. Journal of Chemometrics 1998, 12(5):301-321.
46. Bougeard P., Hanafi M., Qannari E.M. Multiblock latent root regression. Application to epidemiological data. Computational Statistics 2007, 22(2):209-222.
47. Kohler A., Hanafi M., Bertrand D., Oust Janbu A., Møretrø T., Naderstad K., Qannari M., Martens H. Interpreting several types of measurements in bioscience. Modern concepts in biomedical vibrational spectroscopy 2008, John Wiley & Sons, USA. P. Lasch, J. Kneipp (Eds.).
48. Wold S., Hellberg S., Lundstedt Y., Sjostrom M., Wold H. Proc. Symp. on PLS Model Building: Theory and Application, Frankfurt am Main 1987.
49. Wold H. Estimation of principal components and related models by iterative least squares. Multivariate Analysis 1966, 391-420. Academic Press, New York. P.R. Krishnaiah (Ed.).
50. Miyashita Y., Itozawa T., Katsumi H., Sasaki S.-I. Comments on the NIPALS algorithm. Journal of Chemometrics 1990, 4(1).
51. Stone M. Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society: Series B: Methodological 1974, 36(2):111-147.
52. Westad H.M.F. Variable selection in near infrared spectroscopy based on significance testing in partial least squares regression. Journal of Near Infrared Spectroscopy 2000, 8(2):117-124.
53. Oust A., Moretro T., Naterstad K., Sockalingum G.D., Adt I., Manfait M., Kohler A. Fourier transform infrared and Raman spectroscopy for characterization of Listeria monocytogenes strains. Applied and Environmental Microbiology 2006, 72(1):228-232.
54. Winder C.L., Gordon S.V., Dale J., Hewinson R.G., Goodacre R. Metabolic fingerprints of Mycobacterium bovis cluster with molecular type: implications for genotype-phenotype links. Microbiology 2006, 152(9):2757-2765.
55. Kohler A., Kirschner C., Oust A., Martens H. Extended multiplicative signal correction as a tool for separation and characterization of physical and chemical information in Fourier transform infrared microscopy images of cryo-sections of beef loin. Applied Spectroscopy 2005, 59(6):707-716.
56. Kohler A., Zimonja M., Segtnan V., Martens H. Data preprocessing: SNV, MSC and EMSC pre-processing in biospectroscopy. Comprehensive Chemometrics 2009, 139-162. Elsevier, Oxford. S. Brown, R. Tauler, R. Walczak (Eds.).
57. Lafleur M. Phase behaviour of model stratum corneum lipid mixtures: an infrared spectroscopy investigation. Canadian Journal of Chemistry 1998, 76:1501-1511.