@article {1632012,
	title = {FlyPhoneDB: an integrated web-based resource for cell-cell communication prediction in Drosophila},
	journal = {Genetics},
	year = {2021},
	month = {2021 Dec 31},
	abstract = {Multicellular organisms rely on cell-cell communication to exchange information necessary for developmental processes and metabolic homeostasis. Cell-cell communication pathways can be inferred from transcriptomic datasets based on ligand-receptor expression. Recently, data generated from single-cell RNA sequencing have enabled ligand-receptor interaction predictions at an unprecedented resolution. While computational methods are available to infer cell-cell communication in vertebrates such a tool does not yet exist for Drosophila. Here, we generated a high-confidence list of ligand-receptor pairs for the major fly signaling pathways and developed FlyPhoneDB, a quantification algorithm that calculates interaction scores to predict ligand-receptor interactions between cells. At the FlyPhoneDB user interface, results are presented in a variety of tabular and graphical formats to facilitate biological interpretation. To illustrate that FlyPhoneDB can effectively identify active ligands and receptors to uncover cell-cell communication events, we applied FlyPhoneDB to Drosophila single-cell RNA sequencing data sets from adult midgut, abdomen, and blood, and demonstrate that FlyPhoneDB can readily identify previously characterized cell-cell communication pathways. Altogether, FlyPhoneDB is an easy-to-use framework that can be used to predict cell-cell communication between cell types from single-cell RNA sequencing data in Drosophila.},
	issn = {1943-2631},
	doi = {10.1093/genetics/iyab235},
	author = {Liu, Yifang and Li, Joshua Shing Shun and Rodiger, Jonathan and Comjean, Aram and Attrill, Helen and Antonazzo, Giulia and Brown, Nicholas H and Hu, Yanhui and Perrimon, Norbert}
}
