scrnametaboliclandscape

What problem does it solve?

Comprehensive, end-to-end metabolic landscape analysis for scRNA-seq data, coordinating imputation, pathway activity scoring, heterogeneity assessment, and feature enrichment in a single workflow to save time and reduce manual setup.

Core Features & Use Cases

• All-in-one pipeline: runs coordinated steps (expression imputation, pathway activity calculation, heterogeneity analysis, and gene-set enrichment) for complete metabolic profiling.
• Flexible configuration: supports GMT-based pathway sets, group_by and subset_by metadata, and optional mutaters/arbitrary transformations.
• Use Case: researchers analyzing metabolic heterogeneity across cell clusters or treatment conditions can compare pathway activity and enrichment results in a streamlined manner.

Quick Start

Run the ScrnaMetabolicLandscape pipeline using a Seurat clustering result to perform the complete metabolic landscape analysis.