Infer ligand-receptor interactions from single-cell and spatial omics data with LIANA+.
npx skills add https://github.com/Ketomihine/my_skills --skill liana-py-complete
Please help me install this Agent Skill. Skill: liana-py-complete Source: https://github.com/Ketomihine/my_skills/tree/main/liana-py-complete Command: npx skills add https://github.com/Ketomihine/my_skills --skill liana-py-complete
LIANA+ provides an all-in-one framework to infer, analyze, and visualize cell-cell communication from single-cell, spatially resolved, and multimodal omics data, consolidating multiple methods and resources into a unified workflow.
High-intent search queries and answers about installing and using this skill.
Cell-cell communication networks are inferred by applying LIANA+ to RNA, spatial coordinates, and multimodal omics data using multiple methods and resources to identify ligand-receptor interactions.
Yes, multimodal omics data such as CITE-seq can be analyzed for ligand-receptor interactions using tensor and Misty-based analyses that integrate multiple data modalities.
Multi-sample cell-cell communication analysis compares interactions across conditions by applying rank aggregation to unify results from multiple methods like CellPhoneDB, NATMI, and CellChat.
Yes, spatial cell-cell communication analysis requires AnnData or MuData input formats, with analysis results stored directly in the adata.uns field for downstream access.
Ligand-receptor interaction analysis requires a Python environment with LIANA+ and dependencies including scanpy, omnipath, decoupler, and the muon/mudata frameworks.
Downstream analyses after inferring cell-cell communication interactions include integration with Tensor-cell2cell or MOFA, building ligand-receptor gene sets, and creating multi-view representations.
CHENyiru3Organize annotated single-cell data matrices using the AnnData structure.
chenyhvvvvIdentify significant ligand-receptor interactions in human single-cell datasets using CellPhoneDB.
tony-zhelonkinInfer transcription factor and pathway activities from bulk RNA-seq results with DecoupleR.
omicverseAnalyze single-cell ligand-receptor communication from annotated AnnData objects.
