Dissection of intercellular communication using the transcriptome-based framework ICELLNET

Abstract Cell-to-cell communication can be inferred from ligand–receptor expression in cell transcriptomic datasets. However, important challenges remain: global integration of cell-to-cell communication; biological interpretation; and application to individual population profiles. We develop ICELLNET, a transcriptomic-based framework integrating: 1) an original expert-curated database interactions accounting for multiple subunits expression; 2) quantification scores; 3) the possibility connect interest with 31 reference human types; 4) three visualization modes facilitate interpretation. apply ICELLNET datasets generated through RNA-seq, single-cell microarray. reveals autocrine IL-10 control dendritic up 12 types. Four them (T cells, keratinocytes, neutrophils, pDC) are further tested experimentally validated. In summary, is global, versatile, biologically validated, easy-to-use dissect or cell-based