Fig. 2: scBONITA pipeline to infer Boolean rules and perform pathway analysis using single-cell expression measurements.
From: Executable models of immune signaling pathways in HIV-associated atherosclerosis
A Input: a binarized single-cell RNA-seq dataset as a text file, and a prior knowledge network (PKN) describing the activating or inhibitory relationships between genes. B Rule determination: inference of logic rules that describe the regulatory relationships between nodes in the PKN by a global search followed by node-level rule refinement. C Pathway analysis: scBONITA calculates a gene importance score calculated by simulating network perturbations with inferred rules and combines these scores with fold-changes from scRNA-seq to identify differentially regulated pathways in a specified contrast. D Steady-state analysis: scBONITA simulates networks using learned rules to identify steady states which correspond to observed cellular states.
