Fig. 3

Using distance-based measures and entropy as indicators of clonal outgrowth of lymphoma. a Dynamic Time Warping was used to cluster clonality profiles of all samples and identifies two major groups; early-stage samples (blue) and samples undergoing clonal outgrowth (red). Near identical clusters were obtained using the Kolgomorov–Smirnov statistic (Supplementary Data 1). b Samples are plotted comparing entropy score by rank and individual samples are colored by cluster branch, indicating both entropy scores and clustering give a similar bifurcation of samples. c Distribution of entropy scores between the two clusters indicates an entropy value of 3.5 effectively separates the groups. The mean (horizontal line), ±1 s.d. (box), and ±2 s.d. (vertical line) are indicated. d Distribution of entropy scores between different time points indicates a progressive increase in the frequency of clonal outgrowth (mean (horizontal line), ±1 s.d. (box), and ±2 s.d. (vertical line)). Superimposing the clonality profiles of all samples within each cluster indicates consistent shape within the low entropy group (e) and within the high entropy group (f). A normalized clonality value of 0.1 is used to differentiate clonal and subclonal mutations within the late-stage clonal outgrowth samples