scFlowReport: A Reproducible Workflow for Comparative Downstream Biological Analysis of Single-Cell RNA-seq Data

Abstract

Single-cell RNA sequencing (scRNA-seq) studies are frequently organized around comparisons—disease versus control, treatment response, or genetic perturbation—yet biological interpretation still depends on integrating multiple independent downstream analyses for differential expression, functional enrichment, regulatory network inference, and cell–cell communication analysis. Applying these tools consistently across comparisons typically requires substantial custom scripting, and their heterogeneous outputs must be manually harmonized before the results can be compared or reported together. We present scFlowReport, a lightweight, configuration-driven workflow that propagates a single user-defined comparison across cell-level and sample-aware pseudobulk differential expression, over-representation and ranked functional enrichment, transcription-factor regulon export for SCENIC, and group-resolved LIANA cell–cell communication analysis, starting from an already annotated Seurat object. The workflow automatically compiles complementary downstream results into standardized figures, summary tables, and a self-contained static HTML report that can be readily inspected and shared without requiring a persistent server. Application of scFlowReport to a publicly available Atopic Dermatitis scRNA-seq dataset demonstrated its utility by enabling researchers to obtain complementary biological evidence from multiple established downstream analyses. By coordinating complementary downstream analyses under a shared comparison framework, scFlowReport provides a practical and reproducible workflow for systematic interpretation of comparative single-cell transcriptomic data.