title: Statistics for proteomics: experimental design and 2-DE differential analysis.
abstract: Proteomics relies on the separation of complex protein mixtures using bidimensional electrophoresis. This approach is largely used to detect the expression variations of proteins prepared from two or more samples. Recently, attention was drawn on the reliability of the results published in literature. Among the critical points identified were experimental design, differential analysis and the problem of missing data, all problems where statistics can be of help. Using examples and terms understandable by biologists, we describe how a collaboration between biologists and statisticians can improve reliability of results and confidence in conclusions.
authors.affiliation: INRA, Biologie Physico-Chimique des Prions, VIM 78352 Jouy-en-Josas Cedex, France. chich@jouy.inra.fr
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Chich
authors.forename: Olivier
authors.initials: O
authors.lastname: David
authors.forename: Fanny
authors.initials: F
authors.lastname: Villers
authors.forename: Brigitte
authors.initials: B
authors.lastname: Schaeffer
authors.forename: Didier
authors.initials: D
authors.lastname: Lutomski
authors.forename: Sylvie
authors.initials: S
authors.lastname: Huet
mesh_terms: D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods*; D015233:Models, Statistical; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D012107:Research Design