Multiple Testing and Pattern Recognition in 2-DE Proteomics
After separation through two-dimensional gel electrophoresis (2-DE), several hundreds of individual protein abundances can be quantified in a cell population or sample tissue. However, gel-based proteomics has the reputation of being a slow and cumbersome art. But art is not dead! While 2-DE may no longer be the tool of choice in high-throughput differential proteomics, it is still very effective to identify and quantify protein species caused by genetic variations, alternative splicing, and/or PTMs. This chapter reviews some typical statistical exploratory and confirmatory tools available and suggests case-specific guidelines for (1) the discovery of potentially interesting protein spots, and (2) the further characterization of protein families and their possible PTMs.
Key words2-DE Multivariate statistics Protein correlations Clustering Protein isoforms
The author would like to thank Annick De Troyer and Anne-Catherine Vanhove for technical assistance. Prof. Etienne Waelkens and his group (Laboratory of Protein Phosphorylation and Proteomics, KU Leuven), are gratefully acknowledged for the MALDI-TOF/TOF measurements. Financial support from “CIALCA” and the Bioversity International project “ITC characterization” (research projects financed by the Belgian Directorate-General for Development Cooperation (DGDC)) is gratefully acknowledged.
- 7.Benjamin Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Stat Soc B 57:289–300Google Scholar
- 8.Carpentier S, Panis B, Swennen R, Lammertyn J (2008) Finding the significant markers: statistical analysis of proteomic data. In: Vlahou A (ed) Methods in molecular biology, vol 428. Humana Press Inc., Totowa, NJ, pp 327–347Google Scholar
- 10.Sharma S (1996) Applied multivariate techniques. Wiley, New York ISBN 0-471-31064-6Google Scholar
- 11.Jackson JE (2003) A user’s guide to principal components. Wiley, New YorkGoogle Scholar
- 16.Wold S (1985) Partial least squares. Encyc Stat Sci 6:581–591Google Scholar
- 18.Vanhove A (2014) The quest for osmotic stress markers in Musa: from protein to gene and back in a non-model crop. Dissertation presented for the degree of Doctor in Bioscience Engineering KUleuven, LeuvenGoogle Scholar