Core Analysis Workflow

Following the standard spatial transcriptomics workflow, Spatialsnake organizes the core analysis into four stages:

  1. Data integration (integrate)

  2. Preprocessing (preprocess)

  3. Clustering (clustering)

  4. Annotation support (annotation_help)

Following the most common analytical order and decision points in spatial transcriptomics, we divide the core workflow into the four stages listed above. Together, these steps guide the analysis from raw spatial data to biologically interpretable cell-type identities within the sample. Because the outputs are largely consistent across platforms, this section uses a single-sample Visium HD dataset to illustrate the complete core workflow from start to finish. The final output is a cell annotation result that can be used as input for downstream analysis modules.

If you are working with another spatial transcriptomics platform, or with an already integrated multi-sample dataset, we recommend reading the documentation for each step in full. The individual pages describe any required differences in commands and parameter settings.