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single-cell

ToolUniverse workflow — Single Cell

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---
name: tooluniverse-single-cell
description: Production-ready single-cell and expression matrix analysis using scanpy, anndata, and scipy. Performs scRNA-seq QC, normalization, PCA, UMAP, Leiden/Louvain clustering, differential expression (Wilcoxon, t-test, DESeq2), cell type annotation, per-cell-type statistical analysis, gene-expression correlation, batch correction (Harmony), trajectory inference, and cell-cell communication analysis. NEW: Analyzes ligand-receptor interactions between cell types using OmniPath (CellPhoneDB, CellChatDB), scores communication strength, identifies signaling cascades, and handles multi-subunit receptor complexes. Integrates with ToolUniverse gene annotation tools (HPA, Ensembl, MyGene, UniProt) and enrichment tools (gseapy, PANTHER, STRING). Supports h5ad, 10X, CSV/TSV count matrices, and pre-annotated datasets. Use when analyzing single-cell RNA-seq data, studying cell-cell interactions, performing cell type differential expression, computing gene-expression correlations by cell type, analyzing tumor-immune communication, or answering questions about scRNA-seq datasets.
---

# Single-Cell Genomics and Expression Matrix Analysis

Comprehensive single-cell RNA-seq analysis and expression matrix processing using scanpy, anndata, scipy, and ToolUniverse. Designed for both full scRNA-seq workflows (raw counts to annotated cell types) and targeted expression-level analyses (per-cell-type DE, correlation, ANOVA, clustering).

**IMPORTANT**: This skill handles complex multi-workflow analysis. Most implementation details have been moved to `references/` for progressive disclosure. This document focuses on high-level decision-making and workflow orchestration.

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## When to Use This Skill