Figure 4. Spatial principal components analysis (sPCA), performed in 2 dimensions (d = 2) comparing malarial parasite population structures based on monogenomic single-nucleotide polymorphism barcodes from Haiti (n = 42), Colombia (n = 7), Panama (n = 37), and Venezuela (n = 31). The x-axis represents the eigenvector associated with the first principal component, which differentiates between populations; the y axis represents the second principal component, which differentiates between samples within the same populations. Inset graph depicts the amount of variability described by the principal components: x-axis indicates individual principal components, y-axis their individual contribution to the observed variance. Black bars, displayed eigenvectors; gray bars, retained principal components; white bars, nonretained principal components.