A statistical framework for protein quantitation in bottom-up MS-based proteomics

Bioinformatics

Volumn 25, Issue 16, 2009, Pages 2028-2034

  Karpievitch, Yuliya ^a   Stanley, Jeff ^b   Taverner, Thomas ^b   Huang, Jianhua ^a   Adkins, Joshua N ^b   Ansong, Charles ^b   Heffron, Fred ^c   Metz, Thomas O ^b   Qian, Wei Jun ^b   Yoon, Hyunjin ^c   Smith, Richard D ^b   Dabney, Alan R ^a  

^a TEXAS A AND M UNIVERSITY   (United States)

^b PACIFIC NORTHWEST NATIONAL LABORATORY   (United States)

^c OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; AUTOMATION; BACTERIAL VIRULENCE; BIOINFORMATICS; CLINICAL ARTICLE; COMPUTER PROGRAM; COMPUTER SIMULATION; CONTROLLED STUDY; HUMAN; INSULIN DEPENDENT DIABETES MELLITUS; LIQUID CHROMATOGRAPHY; MASS SPECTROMETRY; NONHUMAN; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEOMICS; QUANTITATIVE ANALYSIS; SALMONELLA TYPHIMURIUM; STATISTICAL MODEL;

DATABASES, PROTEIN; MASS SPECTROMETRY; MODELS, STATISTICAL; PROTEINS; PROTEOME; PROTEOMICS;

EID: 68549137863     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btp362     Document Type: Article

References (25)

1. Aebersold,R. and Mann,M. (2003) Mass spectrometry-based proteomics. Nature, 422, 198-207.
2. Benjamini,Y. and Hochbergv,Y. (1995) Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. B, 57, 289-300.
3. Dabney,A.R. and Storey,J.D. (2006) A reanalysis of a published affymetrix genechip control dataset. Genome Biol., 7, 401.
4. Ferguson,T.S. (1996) A Course in Large Sample Theory. Chapman and Hall, London.
5. Gygi,S.P. et al. (1999) Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nat. Biotechnol., 17, 994-999.
6. Hill,E.G. et al. (2008) A statistical model for iTRAQ data analysis. J. Proteome Res., 7, 3091-3101.
7. Keller,A. et al. (2002) Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal. Chem., 74, 5383-5392.
8. Kiebel,G. et al. (2006) PRISM: A data management system for high-throughput proteomics. Proteomics, 6, 1783-1790.
9. Lehmann,E.L. (1997) Testing Statistical Hypotheses. Springer, New York, NY.
10. Lehmann,E.L. and Casella,G. (2003) Theory of Point Estimation. Springer, New York, NY.
11. Lehti,T.M. et al. (2006) Effects of streptozotocin-induced diabetes and physical training on gene expression of extracellular matrix proteins in mouse skeletal muscle. Am. J. Physiol. Endocrinol. Metab., 290, E900-E907.
12. Little,R.J.A. and Rubin,D.B. (2002) Statistical Analysis with Missing Data. Wiley-Interscience, Hoboken, New Jersey.
13. Metz,T.O. et al. (2008) Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset. J. Proteome Res., 7, 698-707.
14. Nesvizhskii,A.I. et al. (2007) Analysis and validation of proteomic data generated by tandem mass spectrometry. Nat. Methods 4, 787-797.
15. Oberg,A.L. et al. (2008) Statistical analysis of relative labeled mass spectrometry data from complex samples using ANOVA. J. Proteome Res., 7, 225-233.
16. Old,W.M. et al. (2005) Comparison of label-free methods for quantifying human proteins by shotgun proteomics. Mol. Cell. Proteomics, 4, 1487-1502.
17. Pasa-Tolic,L. et al. (2004) Proteomic analyses using an accurate mass and time tag strategy. BioTechniques, 37, 621-636.
18. Polpitiya,A.D. et al. (2008) DAnTE: A statistical tool for quantitative analysis of -omics data. Bioinformatics, 24, 1556-1558.
19. Storey,J.D. (2002) A direct approach to false discovery rates. J. R. Stat. Soc. B, 64, 479-498.
20. Storey,J.D. and Tibshirani,R. (2003) Statistical significance for genomewide studies. Proc. Natl Acad. Sci. USA, 100, 9440-9445.
21. Tang,K. et al. (2004) Charge competition and the linear dynamic range of detection in electrospray ionization mass spectrometry. J. Am. Soc. Mass Spectrom., 15, 1416-1423.
22. Troyanskaya,O. et al. (2001) Missing value estimation methods for DNA microarrays. Bioinformatics, 17, 520-525.
23. Wang,P. et al. (2006) Normalization regarding non-random missing values in high-throughput mass spectrometry data. In Pacific Symposium Biocomputing, pp. 315-326.
24. Wang,W. et al. (2003) Quantification of proteins and metabolites by mass spectrometry without isotopic labeling or spiked standards. Anal. Chem., 75, 4818-4826.
25. Zimmer,J.S. et al. (2006) Advances in proteomics data analysis and display using an accurate mass and time tag approach. Mass Spectrom. Rev., 23, 450-482.