Fig. 4 ∣. Determinants of cluster coherence in the shape mode distributions.

a, Schematic illustrating the concept of inertia in K-means clustering. The inertia is measured by total squared distances of all data points to the centroids of their corresponding subtype. A lower inertia value indicates better segregation of clusters indicating more intercluster coherence. b, The inertia in principle decays with an increasing number of clusters. The corresponding cluster number at the elbow point where the inertia decay rate starts to drop is the suggested cluster number to use in VAMPIRE for K-means clustering. The example inertia profile is calculated based on 17,093 MEF cells. The inertia value is calculated on ten separate runs of VAMPIRE analysis at each cluster number parameter value. In each run, the K-means clustering is by default repeated five times with different centroid seeds to find the initial seed that results in the lowest inertia value. The coefficient of variation of inertia between ten separate runs of VAMPIRE is less than 0.05% for this inertia profile, thus an error bar is not shown.