scSketch: Interactive Sketch-based Trajectory Exploration and Pathway-Aware Analysis of Single-Cell Data

Interactively exploring gene expression gradients across low-dimensional cell embeddings is central to single-cell RNA sequencing analysis, yet there arent tools that allow users to sketch trajectories and interactively compute pathway-level interpretation. We present scSketch, a tool that enables users to iteratively explore and test trajectory hypotheses in single-cell data while maintaining statistical validity and biological interpretability. Specifically, users apply interactive directional sketching to draw trajectories across embeddings and probe continuous processes such as cellular differentiation and cell state transitions. scSketch automatically computes gene-trajectory correlations and applies online false discovery rate (FDR) control to maintain statistical validity during iterative exploration. Significant genes are grouped into Reactome pathways for contextual interpretation. Applied to human oral keratinocytes infected with human cytomegalovirus, scSketch revealed infection-associated gradients involving interferon responses, metabolic remodeling and autophagy. Together, these features position scSketch as a bridge between exploratory visualization and mechanistic insight in single-cell biology.