cellcellcommunication

To infer cell-cell communication networks from scRNA-seq data, you provide a Seurat or AnnData object to run the LIANA+ workflow, which identifies ligand-receptor interactions between cell types based on gene expression patterns.

Yes, you can compare communication patterns between healthy and diseased tissues to identify key mediators of cellular crosstalk by applying the inference workflow to scRNA-seq datasets across different conditions.

Yes, cell-cell communication inference works with both Seurat and AnnData inputs, allowing you to compute ligand-receptor interactions and output network results directly from your single-cell RNA-seq data objects.

You can tune ligand-receptor interaction analysis by configuring parameters such as method, groupby, species, expr_prop, min_cells, n_perms, seed, and ncores to optimize network inference for your specific dataset.

The best way to identify signaling events between cell types is using the LIANA+ framework, which assesses signaling between cell types based on curated ligand-receptor interaction databases and gene expression patterns.

Yes, you need to specify a species when running cell-cell communication analysis, as the LIANA+ framework relies on curated ligand-receptor interaction databases that are species-specific for accurate network inference.