Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.07.24.218537v1?rss=1 Authors: Cherry, C., Cahan, P., Garmire, L. X., Elisseeff, J. H. Abstract: Intercellular communication is crucial for function of cells but current methods for reconstruction of intercellular signaling from single cell data can be challenging to connect with biological outcomes. Here, we present Domino (github.com/chris-cherry/domino), a computational tool which reconstructs intercellular signaling coupled with transcription factor activation. Matching signaling with transcription factor activation allows for immediate connection of results to known biological phenotypes. We first apply Domino to model biomaterial environments in a muscle wound where different chemical compositions produce distinct tissue microenvironments. While traditional single cell RNA sequencing analyses captured few differences between conditions, Domino identified previously unknown signaling pathways distinct to conditions. We then demonstrate Domino on a previously published human Alzheimers data set to discover new signaling pathways associated with health and disease. Copy rights belong to original authors. Visit the link for more info