Introduction of a new critical p value correction method for statistical significance analysis of metabonomics data

Analytical and Bioanalytical Chemistry

Volumn 405, Issue 26, 2013, Pages 8419-8429

  Wang, Bo ^a   Shi, Zhanquan ^b   Weber, Georg F ^b   Kennedy, Michael A ^a  

^a MIAMI UNIVERSITY   (United States)

^b UNIVERSITY OF CINCINNATI ACADEMIC HEALTH CENTER   (United States)

Author keywords

Bioanalytical methods; Bioassays; Biological samples; Chemometrics statistics; NMR ESR

Indexed keywords

BIOANALYTICAL METHODS; BIOLOGICAL SAMPLES; BONFERRONI CORRECTION; CHEMOMETRICS/STATISTICS; MULTIPLE TESTING PROBLEMS; NUCLEAR MAGNETIC RESONANCE(NMR); STATISTICAL SIGNIFICANCE; VARIABLE DEPENDENCIES;

BIOASSAY; CELL CULTURE; ERROR ANALYSIS; ETHYLENE; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PROPYLENE;

STATISTICAL TESTS;

ARTICLE; BREAST; BREAST TUMOR; FEMALE; HUMAN; LABORATORY DIAGNOSIS; METABOLISM; METABOLOMICS; METHODOLOGY; PRINCIPAL COMPONENT ANALYSIS; PROBABILITY; REGRESSION ANALYSIS; STATISTICAL MODEL; TUMOR CELL LINE;

BREAST; BREAST NEOPLASMS; CELL LINE, TUMOR; FALSE POSITIVE REACTIONS; FEMALE; HUMANS; LEAST-SQUARES ANALYSIS; METABOLOMICS; MODELS, STATISTICAL; PRINCIPAL COMPONENT ANALYSIS; PROBABILITY;

EID: 84885426102     PISSN: 16182642     EISSN: 16182650     Source Type: Journal    
DOI: 10.1007/s00216-013-7284-4     Document Type: Article

References (41)

1. Lindon J, Nicholson J, Holmes E, Everett J (2000) Metabonomics: metabolic processes studied by NMR spectroscopy of biofluids. Concepts Magn Reson 12(5):289-320. doi: 10.1002/1099-0534(2000)12:5<289::AID-CMR3>3.0.CO;2-W
2. Lindon JC, Nicholson JK, Holmes E (2007) The handbook of metabonomics and metabolomics. Elsevier, Amsterdam
3. Beckonert O, Keun H, Ebbels T, Bundy J, Holmes E, Lindon J, Nicholson J (2007) Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nat Protoc 2(11):2692-2703. doi: 10.1038/nprot.2007.376
4. Halouska S, Powers R (2006) Negative impact of noise on the principal component analysis of NMR data. J Magn Reson 178(1):88-95. doi: 10.1016/j.jmr.2005.08.016
5. Choi Y, Kim H, Hazekamp A, Erkelens C, Lefeber A, Verpoorte R (2004) Metabolomic differentiation of cannabis sativa cultivars using H-1 NMR spectroscopy and principal component analysis. J Nat Prod 67(6):953-957. doi: 10.1021/np049919c
6. Romick-Rosendale L, Goodpaster A, Hanwright P, Patel N, Wheeler E, Chona D, Kennedy M (2009) NMR-based metabonomics analysis of mouse urine and fecal extracts following oral treatment with the broad-spectrum antibiotic enrofloxacin (Baytril). Magn Reson Chem 47:S36-S46. doi: 10.1002/mrc.2511
7. Wishart D (2008) Quantitative metabolomics using NMR. Trac Trends Anal Chem 27(3):228-237. doi: 10.1016/j.trac.2007.12.001
8. Gu H, Pan Z, Xi B, Asiago V, Musselman B, Raftery D (2011) Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: application to the detection of breast cancer. Anal Chim Acta 686(1-2):57-63. doi: 10.1016/j.aca.2010.11.040
9. Fonville J, Richards S, Barton R, Boulange C, Ebbels T, Nicholson J, Holmes E, Dumas M (2010) The evolution of partial least squares models and related chemometric approaches in metabonomics and metabolic phenotyping. J Chemometr 24(11-12):636-649. doi: 10.1002/cem.1359
10. Trygg J, Holmes E, Lundstedt T (2007) Chemometrics in metabonomics. J Proteome Res 6(2):469-479. doi: 10.1021/pr060594q
11. Van Den Berg R, Hoefsloot H, Westerhuis J, Smilde A, Van Der Werf M (2006) Centering, scaling, and transformations: improving the biological information content of metabolomics data. Bmc Genomics 7. doi: 10.1186/1471-2164-7-142
12. Cloarec O, Dumas M, Craig A, Barton R, Trygg J, Hudson J, Blancher C, Gauguier D, Lindon J, Holmes E, Nicholson J (2005) Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic H-1 NMR data sets. Anal Chem 77(5):1282-1289. doi: 10.1021/ac048630x
13. Wei S, Zhang J, Liu L, Ye T, Gowda G, Tayyari F, Raftery D (2011) Ratio analysis nuclear magnetic resonance spectroscopy for selective metabolite identification in complex samples. Anal Chem 83(20):7616-7623. doi: 10.1021/ac201625f
14. Cloarec O, Dumas M, Trygg J, Craig A, Barton R, Lindon J, Nicholson J, Holmes E (2005) Evaluation of the orthogonal projection on latent structure model limitations caused by chemical shift variability and improved visualization of biomarker changes in H-1 NMR spectroscopic metabonomic studies. Anal Chem 77(2):517-526. doi: 10.1021/ac048803i
15. Claus S, Tsang T, Wang Y, Cloarec O, Skordi E, Martin F, Rezzi S, Ross A, Kochhar S, Holmes E, Nicholson J (2008) Systemic multicompartmental effects of the gut microbiome on mouse metabolic phenotypes. Molecular Systems Biology 4. doi: 10.1038/msb.2008.56
16. Wang B, Goodpaster AM, Kennedy MA (2013) Investigating the coefficient of variation, signal-to-noise ratio, and effects of normalization to aid in validation of biomarkers in NMR-based metabonomic studies. Chemometr Intell Lab Syst (in press)
17. Broadhurst DI, Kell DB (2006) Statistical strategies for avoiding false discoveries in metabolomics and related experiments. Metabolomics 2(4):171-196. doi: 10.1007/s11306-006-0037-z
18. Reiner A, Yekutieli D, Benjamini Y (2003) Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics 19(3):368-375. doi: 10.1093/bioinformatics/btf877
19. Narum S (2006) Beyond Bonferroni: less conservative analyses for conservation genetics. Conserv Genet 7(5):783-787. doi: 10.1007/s10592-005-9056- y
20. Perneger T (1998) What's wrong with Bonferroni adjustments. Br Med J 316(7139):1236-1238
21. Nakagawa S (2004) A farewell to Bonferroni: the problems of low statistical power and publication bias. Behav Ecol 15(6):1044-1045. doi: 10.1093/beheco/arh107
22. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate - a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol 57(1):289-300
23. Benjamini Y, Yekutieli D (2001) The control of the false discovery rate in multiple testing under dependency. Annal Stat 29(4):1165-1188
24. Eriksson L, Johansson E, Kettaneh-Wold N, Trygg J, Wikström C, Wold S (2006) Multi- and megavariate data analysis: part II: advanced applications and method extensions. Umetrics Inc. http://urn.kb.se/resolve?urn=urn:nbn:se: umu:diva-12897
25. He B, Mirza M, Weber G (2006) An osteopontin splice variant induces anchorage independence in human breast cancer cells. Oncogene 25(15):2192-2202. doi: 10.1038/sj.onc.1209248
26. Gottschalk M, Ivanova G, Collins D, Eustace A, O'connor R, Brougham D (2008) Metabolomic studies of human lung carcinoma cell lines using in vitro H-1 NMR of whole cells and cellular extracts. NMR Biomed 21(8):809-819. doi: 10.1002/nbm.1258
27. Watanabe M, Sheriff S, Ramelot T, Kadeer N, Cho J, Lewis K, Balasubramaniam A, Kennedy M (2011) NMR based metabonomics study of dag treatment in a c2c12 mouse skeletal muscle cell line myotube model of burn-injury. Int J Pept Res Ther 17(4):281-299. doi: 10.1007/s10989-011-9264-x
28. Zhang S, Zheng C, Lanza I, Nair K, Raftery D, Vitek O (2009) Interdependence of signal processing and analysis of urine H-1 NMR spectra for metabolic profiling. Anal Chem 81(15):6080-6088. doi: 10.1021/ac900424c
29. Lindon JC, Nicholson JK, Holmes E (2007) The handbook of metabonomics. NMR spectroscopy techniques for application to metabonomics. Elsevier, Amsterdam
30. Goodpaster A, Romick-Rosendale L, Kennedy M (2010) Statistical significance analysis of nuclear magnetic resonance-based metabonomics data. Anal Biochem 401(1):134-143. doi: 10.1016/j.ab.2010.02.005
31. Eriksson L, Umetrics A (2006) Multi- and megavariate data analysis. P. 1, basic principles and applications. Umetrics Academy, Umeå
32. Nichols T, Hayasaka S (2003) Controlling the familywise error rate in functional neuroimaging: a comparative review. Stat Methods Med Res 12(5):419-446. doi: 10.1191/0962280203sm341ra
33. Holm S (1979) A simple sequentially rejective multiple test procedure. Scand J Stat 6(2):65-70
34. Hochberg Y (1988) A sharper bonferroni procedure for multiple tests of significance. Biometrika 75(4):800-802. doi: 10.1093/biomet/75.4.800
35. Beger R, Schnackenberg L, Holland R, Li D, Dragan Y (2006) Metabonomic models of human pancreatic cancer using 1d proton NMR spectra of lipids in plasma. Metabolomics 2(3):125-134. doi: 10.1007/s11306-006-0026-2
36. Simes R (1986) An improved bonferroni procedure for multiple tests of significance. Biometrika 73(3):751-754. doi: 10.1093/biomet/73.3.751
37. Holland B, Copenhaver M (1988) Improved Bonferroni-type multiple testing procedures. Psychol Bull 104(1):145-149. doi: 10.1037//0033-2909.104.1.145
38. Ruxton G (2006) The unequal variance t-test is an underused alternative to Student's t-test and the Mann-Whitney u test. Behav Ecol 17(4):688-690. doi: 10.1093/beheco/ark016
39. Goodpaster A, Kennedy M (2011) Quantification and statistical significance analysis of group separation in NMR-based metabonomics studies. Chemometr Intell Lab Syst 109(2):162-170. doi: 10.1016/j.chemolab.2011.08.009
40. Shapiro S, Wilk M (1965) An analysis of variance test for normality (complete samples). Biometrika 52:591. doi: 10.2307/2333709
41. Blaise B, Shintu L, Elena B, Emsley L, Dumas M, Toulhoat P (2009) Statistical recoupling prior to significance testing in nuclear magnetic resonance based metabonomics. Anal Chem 81(15):6242-6251. doi: 10.1021/ac9007754