Figure 4

Principle component analysis of samples grouped according to breed. To lessen the effects of differences due to disease stage the 27 samples of the merged set consist of the eight terminal samples of the known set and all the samples of the unknown set. When grouped according to breed 122 proteins were present on 80% of the gels and showed significant differential abundance (ANOVA p ≤ 0.01). The 122 proteins were analyzed using the FS and RDA algorithms to identify those proteins best able to discriminate between the two breeds of cattle. RDA was used to generate a classifier out of the 12 selected proteins that was able to correctly classify the samples with 82.5 ± 12.6% accuracy. The misclassified samples are identified by arrows and the sample number to which they correspond. (K = known set, U = unknown set, PC1 = 70.2, PC2 = 12.3).