Improving 2D-DIGE protein expression analysis by two-stage linear mixed models: Assessing experimental effects in a melanoma cell study

Bioinformatics

Volumn 24, Issue 23, 2008, Pages 2706-2712

  Fernández, Elmer A ^a,b   Girotti, María R ^b,c   del Olmo, Juan A López ^d   Llera, Andrea S ^b,c   Podhajcer, Osvaldo L ^b,e   Cantet, Rodolfo J C ^b,e   Balzarini, Mónica ^b,f  

^a UNIVERSIDAD CATÓLICA DE CÓRDOBA   (Argentina)

^b Facultad de Ciencias Naturales e Instituto M Lillo   (Argentina)

^c FUNDACIÓN INSTITUTO LELOIR   (Argentina)

^d CENTRO NACIONAL DE INVESTIGACIONES CARDIOVASCULARES CNIC   (Spain)

^e UNIVERSIDAD DE BUENOS AIRES   (Argentina)

^f UNIVERSIDAD NACIONAL DE CÓRDOBA   (Argentina)

Author keywords

[No Author keywords available]

Indexed keywords

CYANINE DYE;

ARTICLE; CONTROLLED STUDY; DIFFERENCE IN GEL ELECTROPHORESIS; EXPERIMENTAL STUDY; HUMAN; HUMAN CELL; IMAGE ANALYSIS; MELANOMA CELL; MOLECULAR DYNAMICS; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN EXPRESSION; STATISTICAL ANALYSIS; STATISTICAL MODEL; TREATMENT RESPONSE; TWO DIMENSIONAL GEL ELECTROPHORESIS; VALIDATION PROCESS;

CARBOCYANINES; CELL LINE, TUMOR; COMPUTATIONAL BIOLOGY; ELECTROPHORESIS, GEL, TWO-DIMENSIONAL; FLUORESCENT DYES; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LINEAR MODELS; MELANOMA; PROTEOME; PROTEOMICS;

EID: 56649123519     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btn508     Document Type: Article

References (26)

1. Alban,B.A. et al. (2003) A novel experimental design for comparative two-dimensional gel analysis: Two-dimensional difference gel electrophoresis incorporating a pooled internal standard. Proteomics 3, 36-44.
2. Amersham (2003) eCyder Differential Analysis Sotware User manual, version 5.0. Amersham Biosciences. Available at http://www1.gelifesciences.com/aptrix/upp00919.nsf/Content/ 0BCBBE1D95989227C12571BF00811C16/$file/28401006AB.pdf
3. Bos,T.J. et al. (2004) International Hermelin brain tumor symposium on matricellular proteins in normal and cancer cell-matrix interactions. Matrix Biol., 23, 63-69.
4. Cochran,W.G. and Cox,G.M. (1957) Experimental Designs. 2nd edn.Wiley & Sons Inc, Canada.
5. Demidenko,E. (2005) Mixed Models: Theory and Applications. Wiley-IEEE Hoboken, New Jersey, USA.
6. Draghici,S. et al. (2003) Noise sampling method: An ANOVA approach allowing robust selection of differentially regulated genes measured by DNA microarrays. Bioinformatics, 19, 1348-1359.
7. Fodor,I.K. et al. (2005) Statistical challenges in the analysis of two-dimensional difference gel electrophoresis experiments using eCyder. Bioinformatics, 21, 3733-3740.
8. Harville,D.A. (1977) Maximum likelihood approaches to variance component estimation and to related problems. J. Am. Stat. Assoc., 72, 320-340.
9. Karp,N.A. and Lilley,K.S. (2005) Maximizing sensitivity for detecting changes in protein expression: Experimental design using minimal CyDyes. Proteomics, 5, 3105-3115.
10. Karp,N.A. et al. (2007) Experimental and statistical considerations to avoid false conclusions in proteomic studies using differential in-gel electrophoresis. Mol. Cell. Proteomics, 6 1354-1364.
11. Kreil,P.D. et al. (2004) DNA microarray normalization methods can remove bias from differential protein expression analysis of 2D difference gel electrophoresis results. Bioinformatics, 20, 2026-2034.
12. Krogh,M. et al. (2007) Analysis of DIGE data using a linear mixed model allowing for protein-specific CyDye effects. Proteomics, 7, 4235-4244.
13. Kultima,K. et al. (2006) Normalization and expression changes in predefined sets of proteins using 2D gel electrophoresis: A proteomic study of L-DOPA induced dyskinesia in an animal model of Parkinson's disease using DIGE. BMC Bioinformatics, 7, 475.
14. Ledda,M.F. et al. (1997) Suppression of SPARC expression by antisense RNA abrogates the tumorigenicity of human melanoma cells. Nat. Med., 3, 171-175.
15. Littell,R.C. et al. (2006) SAS for Mixed Models. SAS Institute, NC, USA.
16. Marouga,R. et al. (2005) The development of the DIGE system: 2D fluorescence difference gel analysis technology. Anal. Bioanal. Chem. 382, 669-678.
17. Meleth,S. et al. (2005) The case for well-conducted experiments to validate statistical protocols for 2D gels: Different pre-processing = different list of significant proteins. BMC Biotechnology, 5 7.
18. Mujumdar,R.B. et al. (1993) Cyanine dye labeling reagents: sulfoindocyanine succinimidyl esters. Bioconjug. Chem., 2, 105-111.
19. Qian,H.R. and Huang,S. (2005) Comparison of false discovery rate methods in identifying genes with differential expression. Genomics, 86 495-503.
20. Patterson,H.D. and Thompson,R. (1971) Recovery of inter-block information when block sizes are unequal. Biometrika, 58, 545-554.
21. Rempel,S.A. et al. (1999) SPARC: A potential diagnostic marker of invasive meningiomas. Clin. Cancer Res., 5, 237-241.
22. Sosa,M.S. et al. (2007) Proteomics analysis identified N-Cadherin, clusterin and HSP27 as mediators of SPARC activity in melanoma cells. Proteomics, 7, 4123-4134.
23. Storey,J.D. and Tibshirani,R. (2003) Statistical significance for genome-wide studies. Proc. Natl Acad. Sci. USA, 100, 9449-9445.
24. Ünlü,M. et al. (1997) Difference gel electrophoresis: A single gel method for detecting changes in protein extracts. Electrophoresis, 18, 2071-2077.
25. Wolfinger,R.D. et al. (2001) Assessing gene significance from cDNA microarray expresión data via mixed models. J. Comp. Biol., 8, 625-637.
26. Yang, Y.H. and Speed,T. (2002) Design issues for cDNA microarray experiments. Nat. Rev. Genet., 3, 579-588.