Identification of High-Risk Cells in Single-Cell Spatially Resolved Transcriptomics Data Using DEGAS Spatial Smoothing
Debolina Chatterjee, Justin L. Couetil, Ziyu Liu, Kun Huang, Chao Chen, Jie Zhang, Michael A. Kalwat, Travis S. Johnson
The paper introduces DEGAS, a method to identify high-risk cells in spatial transcriptomics data by transferring disease attributes to individual cells, validated in cancer and diabetes datasets.
Bioinformatics · Apr 1, 2026Peer-reviewedBioinformatics