Tutorial 1: Spatial Transcriptomics (ST) + Cox Survival Analysis

This tutorial demonstrates a complete workflow for integrating Spatial Transcriptomics (ST) data with bulk RNA-seq data to perform a “Cox” survival analysis.

The example uses Colorectal Cancer (CRC) data to identify spatial spots associated with patient prognosis.

Prerequisites: Download the Model

Before running this script, you must download the pre-trained feature extraction model.

Download: Get ctranspath.pth from Zenodo.
Setup: Create a folder named data/pretrainModel/ in your project root and place the file there.

TiRank/
└── data/
    └── pretrainModel/
        └── ctranspath.pth

Full Python Script

This file is available in your repository at Example/ST-Cox-CRC.py.