Tutorial: Analysis Workflow

Core Feature

This tutorial covers features available in all MATISSE Explorer deployments.

This tutorial demonstrates how to use advanced subsetting and analysis features to investigate specific biological questions in your spatial transcriptomics data.

Scenario

You want to:

1. Find cells that meet multiple criteria
2. Use signatures to analyze pathway activity
3. Combine spatial and transcriptional subsets
4. Save complex subset configurations for reuse

Prerequisites

• Completed the Basic Exploration Workflow
• Familiarity with Subset

Step 1: Define Your Question

Example Question

"Find T cells in the tumor region that have high immune checkpoint expression."

This requires:

• Cell type subset (T cells)
• Spatial subset (tumor region)
• Expression subset (checkpoint genes)

Step 2: Create a Signature

First, create a signature for immune checkpoint genes.

Open Signatures

1. In Explorer sidebar, click Signatures tab
2. Click Create Signature

Define the Gene Set

1. Name: "Immune Checkpoints"
2. Description: "Key immune checkpoint molecules"
3. Variables:

   PDCD1
   CTLA4
   LAG3
   HAVCR2
   TIGIT

4. Click Create

Verify Matches

1. View the created signature
2. Check how many genes matched your data
3. Note any unmatched genes

Step 3: Define Tumor Region

Use lasso selection to define the tumor region.

Switch to Spatial View

1. Ensure you're in Spatial projection
2. Color by a relevant marker to identify tumor region
3. Navigate to see the full tissue

Draw Tumor Region

1. Click Selection mode
2. Draw a lasso around the tumor region
3. Note the selected cell count

Save to Subset

1. Click Items dropdown
2. Select Add selection to subset
3. The lasso condition is saved

Step 4: Build the Complex Subset

Now combine all criteria in the Subset.

Open Subset

1. Open the Subset Panel
2. You should see your lasso condition already added

Add Cell Type Condition

1. Click Add Condition in the same group
2. Select Column type
3. Choose cell type column
4. Select "T cell" category
5. Ensure operator is AND

Add Signature Condition

1. Click Add Condition
2. Select Signature type
3. Choose "Immune Checkpoints"
4. Set combination method to Max
5. Set comparison: > 1.0

Review the Subset

Your subset should now read:

(Tumor Region Lasso) AND (cell_type = T cell) AND (Immune Checkpoints Max > 1.0)

Step 5: Apply and Analyze

Apply the Subset

1. Click Apply
2. View the subset population
3. Note the final cell count

Explore the Results

1. Color by individual checkpoint genes
2. Compare expression levels
3. Examine spatial distribution within the tumor

View in UMAP

1. Switch to UMAP projection
2. See where these cells fall in transcriptional space
3. Check if they cluster together

Step 6: Refine the Analysis

Adjust Thresholds

If results are too few or too many:

1. Edit the signature condition
2. Adjust the threshold (e.g., > 0.5 or > 2.0)
3. Re-apply and check results

Add Additional Conditions

To further refine:

1. Add more expression criteria
2. Adjust spatial region
3. Change combination method

Step 7: Save Your Subset

Save as Saved Subset

1. Click Save
2. Name: "Tumor T cells - High Checkpoint"
3. Press Enter to confirm

Verify Saved Subset

1. Clear the subset
2. Load the saved subset
3. Confirm subset is restored

Step 8: Export Results

Export Subset Data

1. With subset active, export feature data
2. Download cell IDs and features
3. Use in downstream analysis

Document Analysis

Record your analysis:

• Subset configuration
• Signature contents
• Result counts
• Screenshots

Advanced Techniques

Using OR Logic

Find cells matching any of several criteria:

Group 1 (OR):
├── High PDCD1 (> 2.0)
├── High CTLA4 (> 2.0)
└── High LAG3 (> 2.0)

Combining Regions

Compare cells across multiple regions:

Subset (OR):
├── Group 1: Tumor Region AND T cell
└── Group 2: Stroma Region AND T cell

Nested Logic

Complex queries with groups:

Subset (AND):
├── Group 1 (OR):
│   ├── T cell
│   └── NK cell
└── Group 2 (AND):
    ├── Tumor Region
    └── High Checkpoint

Summary

In this tutorial, you learned to:

Step	Skill
1-2	Create signatures for gene groups
3	Define spatial regions with lasso
4	Build multi-condition subsets
5-6	Apply, analyze, and refine results
7-8	Save presets and export data

Next Steps

• Group Comparison Workflow - Compare populations
• Signatures - More on gene groups
• Saved Subsets - Managing saved subsets