gene expression

Problem: Gene expression signatures (GESs) derived from bulk RNA-Seq often show inconsistent performance when applied to single-cell (scRNA-Seq) or spatial transcriptomics (ST) data due to differences in data sparsity and resolution.
Solution: The study introduces the signifinder Bioconductor package, a workflow that standardizes the testing and scoring of GESs across bulk, scRNA-Seq (using methods like AUCell), and ST platforms.
Findings: Application to breast cancer signatures revealed that only a small subset were highly robust across all three modalities. The package successfully mapped expression signatures to spatial tissue regions, enabling a more precise, high-resolution analysis of the tumor microenvironment (TME).