Systematic single-cell pathway analysis to characterize early T cell activation

Pathway analysis is a key analytical stage in the interpretation of omics data, providing a powerful method for detecting alterations in cellular processes. We recently developed a sensitive and distribution-free statistical framework for multisample distribution testing, which we implement here in the open-source R package single-cell pathway analysis (SCPA). We demonstrate the effectiveness of SCPA over commonly used methods, generate a scRNA-seq T cell dataset, and characterize pathway activity over early cellular activation. This reveals regulatory pathways in T cells, including an intrinsic type I interferon system regulating T cell survival and a reliance on arachidonic acid metabolism throughout T cell activation. A systems-level characterization of pathway activity in T cells across multiple tissues also identifies alpha-defensin expression as a hallmark of bone-marrow-derived T cells. Overall, this work provides a widely applicable tool for single-cell pathway analysis and highlights regulatory mechanisms of T cells.

Automated summary

This study developed a statistical framework for single-cell pathway analysis, demonstrated its effectiveness compared to commonly used methods, and identified regulatory mechanisms and pathway activity in T cells.