Cell Segmentation-based Analysis

This is an example to illustrate aggregating the spatial transcriptomic data from NovaScope at the cell level, and clustering those identified cells using Seurat build-in graph-based clustering approach.

Figure 2: A Brief Overview of the Inputs, Outputs, and Process Steps for Cell Segmentation-based Analysis. SGE: spatial digital gene expression matrix; UMAP: Uniform Manifold Approximation and Projection.

Step-by-Step Procedure

Before beginning the analysis, ensure that NEDA and its dependencies are installed. Follow these steps as outlined:

1. Create a cell-indexed spatial digital gene expression matrix. This step requires the users manually perform histology-based cell segmentation outside of NEDA using methods such as Watershed and Cellpose.

2. Apply Seurat to identify cell type clusters for those staining-based segmented cells.