Using a cross-model loadings plot to identify protein spots causing 2-DE gels to become outliers in PCA.
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.
Kristiansen
Luise Cederkvist
LC
Enzyme and Protein Chemistry Group, Department of Systems Biology, Technical University of Denmark, Kgs. Lyngby, Denmark. lck@bio.dtu.dk
Jacobsen
Susanne
S
Jessen
Flemming
F
Jørgensen
Bo M
BM
D000818:Animals; D033364:Decapoda; D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods*; D015999:Multivariate Analysis; D018482:Muscle, Skeletal / Q000737:chemistry; D011506:Proteins / Q000032:analysis*
D011506:Proteins