metabolicexpimputation

What problem does it solve?

Imputes missing/dropout values in scRNA-seq expression data to improve metabolic pathway analysis and feature selection by filling zero values with principled imputation methods.

Core Features & Use Cases

• Imputes zeros using ALRA, scImpute, or MAGIC to recover latent expression signals.
• Integrates with ScrnaMetabolicLandscape, enabling auto-activation or skipping via noimpute, and scheduling after MetabolicInput and before MetabolicPathwayActivity and MetabolicFeatures.
• Use Case: when analyzing sparsely expressed metabolic genes to obtain reliable pathway scores and gene-set results in downstream analyses.

Quick Start

Configure ScrnaMetabolicLandscape.MetabolicExprImputation to select an imputation method (alra, scimpute, or rmagic) and run the ScrnaMetabolicLandscape pipeline on a Seurat object.