exFINDER: identify external communication signals using single-cell transcriptomics data.

Area of Science:

• Cell Biology
• Computational Biology
• Genomics

Background:

• Cells communicate via signals, crucial for decision-making.
• Single-cell transcriptomics (scRNA-seq) infers cell-cell communication but misses external signals.
• Existing computational tools analyze only cell-intrinsic signals, lacking external input inference.

Approach:

• Introduced exFINDER, a computational method for identifying external signals received by cells in scRNA-seq data.
• Utilizes prior knowledge of signaling pathways to infer external signals activating target genes.
• Develops the external signal-target signaling network (exSigNet) for quantitative analysis.

Key Points:

• exFINDER accurately identifies external signals and their target genes.
• Reveals critical transition-related signaling activities in various species.
• Enables quantitative analysis and clustering of signal-target paths.
• Applications demonstrate robustness in identifying external signals and biological events.

Conclusions:

• exFINDER enhances scRNA-seq analysis by uncovering external signal-associated cellular activities.
• Facilitates the discovery of novel cells responsible for sending external signals.
• Provides a robust framework for understanding cell-environment interactions through signaling pathways.