CellTune: an integrative software for accurate cell classification in spatial proteomics

Spatial proteomics measures multiple proteins in situ, capturing tissue complexity. However, cell classification in densely packed tissues remains challenging due to the lack of efficient classification algorithms, annotation tools and high-quality labeled datasets to benchmark computational methods. The researchers introduce CellTune, an integrated software for analysis of large spatial proteomics datasets, which streamlines precise cell classification through an optimized human-in-the-loop active learning workflow. It advances core capabilities for analysis of large datasets with an intuitive and code-free interface. To evaluate CellTune, a resource of 40,000 manually annotated cells and 3.5 million high-quality labeled cells across 60 cell types was created. CellTune outperforms alternative methods, achieving accuracy comparable to human performance while enabling increased classification resolution and discovery of novel cell types.