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FlyPhoneDB: an integrated web-based resource for cell-cell communication prediction in Drosophila.


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.

SUBMITTER: Liu Y 

PROVIDER: S-EPMC9176295 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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FlyPhoneDB: an integrated web-based resource for cell-cell communication prediction in Drosophila.

Liu Yifang Y   Li Joshua Shing Shun JSS   Rodiger Jonathan J   Comjean Aram A   Attrill Helen H   Antonazzo Giulia G   Brown Nicholas H NH   Hu Yanhui Y   Perrimon Norbert N  

Genetics 20220301 3


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 t  ...[more]

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