Fig 3. A schematic of our clustering procedure in Algorithm 1.

Each point is a TCR portrayed in an abstract 2-D space, where the distance between points is determined by TCRdist. Our procedure starts by identifying the maximally lonely TCR t_max according to Eq (10). In each iteration, we step out s units of TCRdist, and compute the mean loneliness of all TCRs within the annulus defined by the current and previous radii (or ball in the first step). By construction of Eq (10), we expect the loneliness values to steadily decrease as we move away from t_max, until we arrive at a radius where the loneliness values have stabilized. This “breakpoint radius” thus defines the radius of our cluster.