singIST: an R/bioconductor library and quarto dashboard for automated single-cell comparative transcriptomics analysis of disease models and humans.

singIST enables standardized, quantitative comparison of disease model and human single-cell transcriptomic data, revealing biological recapitulation across pathways, cell types, and genes.

• Why it matters: Accurately assessing how well preclinical disease models mimic human pathophysiology at the single-cell level is crucial for translational research but remains challenging due to limited tools.
• What they did: The authors developed singIST, an R/Bioconductor package that integrates pathway modeling, cell-type resolution, and orthology mapping, along with an interactive Quarto-based visualization tool.
• The result: singIST offers a reproducible framework for cross-species single-cell comparison, supporting model evaluation and hypothesis generation, with the software and visualization tool freely available online.