Challenges related to analysis of protein spot volumes from two-dimensional gel electrophoresis as revealed by replicate gels

Journal of Proteome Research

Volumn 5, Issue 12, 2006, Pages 3399-3410

  Grove, Harald ^a,b   Hollung, Kristin ^a   Uhlen, Anne Kjersti ^b   Martens, Harald ^a,b   Færgestad, Ellen Mosleth ^a  

^a NORWEGIAN FOOD RESEARCH INSTITUTE   (Norway)

^b NORWEGIAN UNIVERSITY OF LIFE SCIENCES   (Norway)

Author keywords

2 DE; Missing data; Multivariate data analysis; Statistical properties

Indexed keywords

ARTICLE; DATA ANALYSIS; GEL; MULTIVARIATE ANALYSIS; PRIORITY JOURNAL; PROTEIN ANALYSIS; STATISTICAL ANALYSIS; TWO DIMENSIONAL GEL ELECTROPHORESIS;

DATA INTERPRETATION, STATISTICAL; ELECTROPHORESIS, GEL, TWO-DIMENSIONAL; MULTIVARIATE ANALYSIS; PROTEINS; PROTEOMICS; TRITICUM;

EID: 33845446814     PISSN: 15353893     EISSN: None     Source Type: Journal    
DOI: 10.1021/pr0603250     Document Type: Article

References (22)

1. Gorg, A.; Weiss, W.; Dunn, M. J. Current two-dimensional electrophoresis technology for proteomics. Proteomics 2004, 4 (12), 3665-3685.
2. Voss, T.; Haberl, P. Observations on the reproducibility and matching efficiency of two-dimensional electrophoresis gels: Consequences for comprehensive data analysis. Electrophoresis 2000, 21 (16), 3345-3350.
3. Zhou, H. L.; Ranish, J. A.; Watts, J. D.; Aebersold, R. Quantitative proteome analysis by solid-phase isotope tagging and mass spectrometry. Nat. Biotechnol. 2002, 20 (5), 512-515.
4. Everley, P. A.; Krijgsveld, J.; Zetter, B. R.; Gygi, S. P. Quantitative cancer proteomics: Stable isotope labeling with amino acids in cell culture (SILAC) as a tool for prostate cancer research. Mol. Cell. Proteomics 2004, 3 (7), 729-735.
5. Hu, Y.; Wang, G.; Chen, G. Y. J.; Fu, X.; Yao, S. Q. Proteome analysis of Saccharomyces cerevisiae under metal stress by two-dimensional differential gel electrophoresis. Electrophoresis 2003, 24 (9), 1458-1470.
6. Karp, N. A.; Spencer, M.; Lindsay, H.; O'Dell, K.; Lilley, K. S. Impact of replicate types on proteomic expression analysis. J. Proteome Res. 2005, 4 (5), 1867-1871.
7. Hunt, S. M. N.; Thomas, M. R.; Sebastian, L. T.; Pedersen, S. K.; Harcourt, R. L.; Sloane, A. J.; Wilkins, M. R. Optimal replication and the importance of experimental design for gel-based quantitative proteomics. J. Proteome Res. 2005, 4 (3), 809-819.
8. Langsrud, O. Rotation tests. Stat. Comput. 2005, 15 (1), 53-60.
9. Jessen, F.; Lametsch, R.; Bendixen, E.; Kjaersgard, I. V. H.; Jorgensen, B. M. Extracting information from two-dimensional electrophoresis gels by partial least squares regression. Proteomics 2002, 2 (1), 32-35.
10. Gottlieb, D. M.; Schultz, J.; Bruun, S. W.; Jacobsen, S.; Sondergaard, I. Multivariate approaches in plant science. Phytochemistry 2004, 65 (11), 1531-1548.
11. Kleno, T. G.; Leonardsen, L. R.; Kjeldal, H. O.; Laursen, S. M.; Jensen, O. N.; Baunsgaard, D. Mechanisms of hydrazine toxicity in rat liver investigated by Proteomics and multivariate data analysis. Proteomics 2004, 4 (3), 868-880.
12. Gustafsson, J. S.; Ceasar, R.; Glasbey, C. A.; Blomberg, A.; Rudemo, M. Statistical exploration of variation in quantitative two-dimensional gel electrophoresis data. Proteomics 2004, 4 (12), 3791-9.
13. Meunier, B.; Bouley, J.; Piec, I.; Bernard, C.; Picard, B.; Hocquette, J. F. Data analysis methods for detection of differential protein expression in two-dimensional gel electrophoresis. Anal. Biochem. 2005, 340 (2), 226-230.
14. Almeida, J. S.; Stanislaus, R.; Krug, E.; Arthur, J. M. Normalization and analysis of residual variation in two-dimensional gel electrophoresis for quantitative differential proteomics. Proteomics 2005, 5 (5), 1242-1249.
15. Grung, B.; Manne, R. Missing values in principal component analysis. Chemom. Intell. Lab. Syst. 1998, 42 (1-2), 125-139.
16. Wood, J.; White, I. R.; Cutler, P. A likelihood-based approach to defining statistical significance in proteomic analysis where missing data cannot be disregarded. Signal Process. 2004, 84 (10), 1777-1788.
17. Troyanskaya, O.; Cantor, M.; Sherlock, G.; Brown, P.; Hastie, T.; Tibshirani, R.; Botstein, D.; Altman, R. B. Missing value estimation methods for DNA microarrays. Bioinformatics 2001, 17 (6), 520-525.
18. Bo, T. H.; Dysvik, B.; Jonassen, I. LSimpute: accurate estimation of missing values in microarray data with least squares methods. Nucleic Acids Res. 2004, 32 (3), e34.
19. Chang, J. S.; Van Remmen, H.; Ward, W. F.; Regnier, F. E.; Richardson, A.; Cornell, J. Processing of data generated by 2-dimensional gel electrophoresis for statistical analysis: Missing data, normalization, and statistics. J. Proteome Res. 2004, 3 (6), 1210-1218.
20. Flaete, N. E. S.; Hollung, K.; Ruud, L.; Sogn, T.; Faergestad, E. M.; Skarpeid, H. J.; Magnus, E. M.; Uhlen, A. K. Combined nitrogen and sulphur fertilisation and its effect on wheat quality and protein composition measured by SE-FPLC and proteomics. J. Cereal Sci. 2005, 41 (3), 357-369.
21. Blum, H.; Beier, H.; Gross, H. J., Improved Silver Staining of Plant-Proteins, Rna and DNA in Polyacrylamide Gels. Electrophoresis 1987, 8 (2), 93-99.
22. Mosleth, E.; Uhlen, A. K. Identification of quality-related gliadins and prediction of bread-making quality of wheat from the electrophoretic pattern of gliadins and high molecular weight subunits of glutenin. Norw. J. Agric. Sci. 1990, 4, 27-45.