> For the complete documentation index, see [llms.txt](https://help.bioinsight.illumina.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.bioinsight.illumina.com/dragen-stratamap/illumina-connected-multiomics/analysis-methods.md). # Analysis Methods A description of the methods used for spatial analysis. ### Filtering and normalization ### PCA ### UMAP ### Clustering ### Differential Expression Differential analysis helps identify differential expression patterns in the dataset. For differential expression analysis of spatial data we have implemented Wilcoxon. A nonparametric statistical hypothesis test that compares two groups and does not assume a normal distribution. Our implementation closely matches Scanpy's scanpy.tl.rank\_genes\_groups when using method='wilcoxon'. **Running Wilcoxon** We recommend normalizing you data prior to running *Wilcoxon*, but it can be invoked on any counts data node. * Click the counts data node * Click the **Differential analysis** section in the toolbox * Click **Wilcoxon** (Figure 1) * Select the attribute to include in the statistical test (Figure 2), and click **Next**

Figure 1. Differential expression analysis method selection page.

Figure 2. Attribute selection page.

* Define the comparisons by dragging and dropping each group in the *Denominator* and *Numerator* boxes and click **Add comparison** (Figure 3)

Figure 3. Comparison setup page.

If the data has not been filtered upstream the **Low value filter** box will be checked by default. You can edit the filtering value and any of the **Advanced options** as needed (Figure 4). Click **Finish** to run the task.

Figure 4. Advanced options menu

### Marker Gene Identification ### Cell Typing --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://help.bioinsight.illumina.com/dragen-stratamap/illumina-connected-multiomics/analysis-methods.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.