Inferring pattern-driving intercellular flows from single-cell transcriptomics of young human cortical organoids

Intercellular communication drives directed flows of information that are mediated by intracellular gene modules, in turn triggering outflows of other signals. Methodologies to describe such intercellular flows are severely lacking. We present FlowSig, a method that infers communication-driven intercellular flows from scRNA-seq using graphical causal modeling and conditional independence. We used human cortical organoid samples collected at D18 and D35 to demonstrate the functions of FlowSig. Organoids were self-assembled using 9,000 stem cells per organoid and cultured in brain cortical region-inducing media. 160 cortical organoids were pooled for a D18 sample, and 25 cortical organoids were pooled for a D35 sample. There were two biological repeats per time point. The samples were subjected to scRNA-seq to identify key signaling pathways from D18 to D35 using FlowSig.