The Dedenser algorithm is formulated to first cluster a chemical point cloud with HDBSCAN and then apply Poisson disk downsampling to clusters based on their relative hull volumes or weighted densities. The goal of downsampling is to achieve a targeted percentage of retained compounds from the initial chemical point cloud. To calculate the number of molecules each cluster is to be downsampled to a remaining target (T*) is calculated as the difference between the initial target (T) and the number of chemical singletons (S), or 'noise' (eq 2.). The hull volume for each cluster (vi) is then calculated, and used to determine the relative volume of each cluster which is then used to calculate the target number of molecules for each cluster (𝑇𝑇 𝑖𝑖 * ) (eq 3.). Alternatively, Dedenser allows for cluster targets to be calculated from proportional weightings (Wi) of clusters (eq. 4), derived from exponential functions parameterized by a weighting term (w) to allow for greater differentiation between cluster properties (pi, either cluster density or volume) (eq. 5). Additionally, by assigning negative weights, sparser/smaller clusters will be assigned greater relative target sizes compared to denser/larger clusters.