Performance of Organ-Focused Versus Generalized Single-Cell Foundation Models

Determine whether kidney-specific single-cell foundation models pretrained on organ-focused datasets outperform generalized multi-organ single-cell foundation models in terms of accuracy and interpretability within single-cell analysis.

Background

Foundation models such as scGPT and Geneformer have demonstrated strong performance across diverse single-cell tasks by pretraining on large, multi-organ datasets. However, the extent to which organ-specific biological structure can be better captured by specialized, organ-focused models has not been conclusively established.

The kidney’s complex cellular architecture and dynamic microenvironments present challenges for model generalization, batch correction, and cross-modality integration. This motivates the question of whether a kidney-focused foundation model can surpass generalized models in accuracy and interpretability for kidney single-cell analysis.