scACCorDiON: A clustering approach for explainable patient level cell cell communication graph analysis

Abstract

Motivation The combination of single-cell sequencing with ligand-receptor analysis paves the way for the characterization of cell communication events in complex tissues. In particular, directed weighted graphs stand out as a natural representation of cell-cell communication events. However, current computational methods cannot analyze sample-specific cell-cell communication events, as measured in single-cell data produced in large patient cohorts. Cohort-based cell-cell communication analysis presents many challenges, such as the non-linear nature of cell-cell communication and the high variability presented by the patient-specific single-cell RNAseq datasets.