肺腺癌单细胞数据集GSE189357复现系列之九:SCENIC转录调控网络

TL;DR - A practical SCENIC workflow reproduces transcriptional regulatory-network analysis for malignant epithelial cells in the GSE189357 lung adenocarcinoma single-cell dataset. It enables identification of subtype-specific transcription-factor programs beyond differential gene expression.

• SCENIC combines GENIE3 co-expression inference, RcisTarget motif enrichment, and AUCell regulon-activity scoring.
• The tutorial analyzes four malignant cell subtypes, using balanced downsampling for network inference to reduce computational cost.
• Regulon activity is then scored across all tumor cells and visualized by subtype.
• Regulon specificity scores (RSS) rank candidate subtype-specific transcription factors, but no biological findings are reported.