FlyPhoneDB

FlyPhoneDB predicts cell–cell communication in Drosophila from single-cell RNA sequencing (scRNA-seq) data using a curated ligand–receptor (L-R) database and quantitative interaction scoring.

Key Features:

• High-Confidence Ligand–Receptor Pair Database: A manually curated list of ligand–receptor (L-R) pairs covering major Drosophila signaling pathways provides the knowledgebase for inference.
• Quantification Algorithm: An algorithm computes interaction scores between L-R pairs across cells to quantify the likelihood of interactions and predict active ligands and receptors.
• Application Across Multiple Tissues: Method has been applied to scRNA-seq datasets from adult midgut, abdomen, and blood to identify known cell–cell communication pathways.

Scientific Applications:

• Developmental Biology: Enables high-resolution prediction of L-R interactions at the single-cell level to study signaling networks during development in Drosophila.
• Metabolic Homeostasis: Facilitates investigation of intercellular signaling pathways that contribute to metabolic homeostasis and physiological regulation.

Methodology:

Using single-cell RNA sequencing (scRNA-seq) expression data, FlyPhoneDB maps ligand and receptor expression to infer cell–cell communications and applies an algorithm that quantifies interaction scores or likelihoods for L-R pairs.