title: Using a cross-model loadings plot to identify protein spots causing 2-DE gels to become outliers in PCA.
abstract: The multivariate method PCA is an exploratory tool often used to get an overview of multivariate data, such as the quantified spot volumes of digitized 2-DE gels. PCA can reveal hidden structures present in the data, and thus enables identification of potential outliers and clustering. Based on PCA, we here present an approach for identification of protein spots causing 2-DE gels to become outliers. The approach can potentially obviate analytical exclusion of entire 2-DE gels.
authors.affiliation: Enzyme and Protein Chemistry Group, Department of Systems Biology, Technical University of Denmark, Kgs. Lyngby, Denmark. lck@bio.dtu.dk
authors.forename: Luise Cederkvist
authors.initials: LC
authors.lastname: Kristiansen
authors.forename: Susanne
authors.initials: S
authors.lastname: Jacobsen
authors.forename: Flemming
authors.initials: F
authors.lastname: Jessen
authors.forename: Bo M
authors.initials: BM
authors.lastname: Jørgensen
mesh_terms: D000818:Animals; D033364:Decapoda; D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods*; D015999:Multivariate Analysis; D018482:Muscle, Skeletal / Q000737:chemistry; D011506:Proteins / Q000032:analysis*
chemical_list: D011506:Proteins