Fig. 5

Principal component analysis. Plots provide essential information from a large dataset and transform it into a few principal components, which convey the most variation in the dataset. 4a Loading plot. PC1 is shown horizontally, and PC2 is shown vertically. The values of the vectors on each PC show how much weight they have on that PC. Angles between the vectors express how characteristics correlate with one another, and grouping together suggests a strong positive correlation between variables. 4b PC clustering with marked strain, source, capsule or location. The dots do not represent each isolate; rather, they represent variation and account for the varied influences of the original characteristics