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Updated: May 22, 2026
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
Protocol for spatially resolved pathology scores using optimal transport on spatial transcriptomics data
Mohammad Nuwaisir Rahman1, James F Martin2, M Saifur Rahman3
1Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh; Computer Science and Engineering, BRAC University, Dhaka 1212, Bangladesh; Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore.
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Spatial transcriptomics (ST) integrates gene expression with spatial context to study tissue pathology. We present SPaSE (spatially resolved pathology score), a protocol to quantify pathology by computing an optimal transport plan between ST spots of the diseased and the corresponding healthy tissue. We describe steps for assigning pathology scores to each spot and developing support vector regression models to link gene expression with pathological impact. We demonstrate the utility of SPaSE across multiple human and mouse ST datasets. For complete details on the use and execution of this protocol, please refer to Rahman et al.1.
