Single-cell downstream analysis

What problem does it solves? After initial preprocessing and clustering, single-cell data requires diverse downstream analyses—from pathway scoring and differential expression to drug response prediction and gene regulatory network inference—each with its own complexities. This Skill provides a comprehensive guide to these advanced analyses, streamlining your research.

Core Features & Use Cases

• Pathway Activity Scoring: Score pathway activity using AUCell and identify cluster-enriched pathways.
• Differential Expression Analysis: Perform DEG on single cells or metacells (bulk-style, cell-type specific, compositional).
• Drug Response & GRN Inference: Predict drug responses with scDrug and infer gene regulatory networks with SCENIC.
• Gene Program Discovery: Discover gene programs with cNMF and overlapping communities with NOCD.
• Use Case: Analyze a single-cell dataset to score pathway activity with AUCell, identify differentially expressed genes between specific cell types using memento-de, infer gene regulatory networks with SCENIC, and generate a comprehensive HTML report summarizing all findings.

Quick Start

Score GO pathways with AUCell on my single-cell data, then run memento-de for differential expression between 'T cells' and 'B cells', and generate an HTML report.