Figure 1.
Decision tree for bovine classification.
The decision tree for individual assignment to a particular breed (or group of breeds). For each diamond-shaped node we propose (small) panels of AIMs that may be used to assign an individual to one of its children nodes. The rows of square-shaped nodes indicate breed (or groups of breeds) of origin that we can separate. For example, using the panel that we proposed at the World node, we can assign a sample to either B. indicus, or B. taurus, or hybrid breeds.
Figure 2.
PCA plots at various levels of the decision tree of Figure 1. (A) Top left: PCA plot at the World node. Top right: PCA plot at the B. indicus node. Bottom left: PCA plot at the B. taurus node. Bottom right: PCA plot at the Hybrids node. (B) Top left: PCA plot at the European Taurine node. Top right: PCA plot at the seven-taurine node. Bottom left: PCA plot at the Angus-Red Angus node.
Table 1.
Significant PCs and panel sizes.
Table 2.
Classifying Angus samples.
Figure 3.
Classification accuracy of our complete leave-one-out cross-validation experiment at all nodes of our decision tree. Five different panel sizes are evaluated, with 30K corresponding to all available markers, 2K corresponding to the top 2,000 PCAIMs, and P1, P2, and P3 corresponding to the panel sizes depicted in Table 1. These smaller panels emerged by removing redundant markers from the top 2,000 AIMs. Notice that the top 2,000 markers were selected using only the individuals in the training set of the crossvalidation experiment. (A) Classification accuracy results (out of 100%). (B) Average number of correctly predicted nearest neighbors (out of five).