Fig. 4: Critical point analysis and network analysis of two trajectories.

a Clustering of all cells into four time point-defined subpopulations. The left panel is FLOW-MAP with cells color-coded by drug exposure time. The right panel is FLOW-MAP with cell color-coded as one of the 14 subpopulations defined from clustering analysis. b Critical point transition analysis for the upper path. Critical point index SNAI is calculated within each subpopulation associated with the upper path and color-coded onto the FLOW-MAP. Red indicates a higher SNAI value, while blue represents a lower SNAI value. Cluster 7, shown where labeled, shows the highest SNAI value in the upper path. c Critical point transition analysis for the lower path. Critical point index SNAI is calculated within each subpopulation associated with the lower path and color-coded onto the FLOW-MAP. Red indicates higher SNAI value, whereas blue represents lower SNAI value. Cluster 9, shown where labeled, shows the highest SNAI value in the lower path. d Marker–marker correlation networks, extracted from SCBC data within cluster 7 cells. The correlation strengths are reflected in the color of each edge (orange indicates positive correlation and blue indicates negative correlation). e Marker–marker correlation networks, extracted from SCBC data within cluster 9 cells. The correlation strengths are reflected in the color of each edge (orange indicates positive correlation and blue indicates negative correlation). f Importance score of each node within each network, as defined by node degree (a quantification of connectivity of a node within a network). Colors indicate the node-degree value of each node within cluster 7 or cluster 9 networks. Nodes with high scores were hypothesized to be important and some of them labeled with stars were further tested with drug perturbation.