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Work with Your Own Data

CartoScope isn't just for public data — it's also designed to help you visualize and analyze your own spatial omics experiments with the same high quality. This guide walks you through the workflow from raw data to interactive visualization.

Workflow Overview

To bring your data into CartoScope, the process generally involves five steps:

  1. Prepare: Convert your raw data into the optimized format using CartLoader.
  2. Host: Store your processed data on an accessible server (AWS S3, Zenodo, or CartoStore).
  3. Load: Access your data in CartoScope — either by pasting a direct URL, or by setting up a Data Library to browse all your datasets in one place.
  4. Explore: Visualize layers, investigate spatial factors, define ROIs, and inspect spots.
  5. Share: Save and share your workspace via bookmarks, links, or exported images.

Step-by-Step Tutorial

Step 1. Prepare Your Data

To visualize your spatial omics data in CartoScope, you first need to convert the raw files (from platforms like Visium, Xenium, or Stereo-seq) into an optimized, multi-scale format. Our dedicated tool, CartLoader, handles this conversion efficiently.

CartLoader streamlines the preparation process by harmonizing data from various platforms, inferring spatial factors with FICTURE, and aligning morphology images. It also processes segmentation and bin-based analysis results, ensuring all outputs are formatted for high-performance visualization in CartoScope.

  • Tool: CartLoader
  • Goal: Generate a catalog.yaml and associated tiles/data.
  • Key Capabilities:
    • Harmonize diverse formats into a unified schema.
    • Infer spatial factors using FICTURE.
    • Align morphology images with ST data.
    • Process cell segmentation-based analysis results.
    • Process bin-based analysis results.
    • Prepare all above data as multi-resolution map tiles.
  • Documentation: CartLoader Documentation

See How to Prepare your Data for detailed instructions.

Step 2. Host Your Data

Once processed, your data needs to be accessible via HTTP/HTTPS.

Currently, CartoScope supports the following hosting methods. Please choose the hosting method that best fits your needs, and follow the instructions below.

Hosting Option Why choose this Things to pay attention to How to host
AWS S3 • Scalability: Handles datasets of any size.
• Control: Offers fine-grained access control (public or private).
• Performance: High availability and fast download speeds globally.		 • Cost: You pay for storage.
• Setup: Requires configuring permissions and CORS policies correctly.		 How to Host on AWS S3
Zenodo • Free: No cost for storage.
• Academic Friendly: Assigns a DOI, perfect for citing.
• Long-term Archival: Guarantees data preservation.		 • Public Access: Generally intended for open data.
• Immutability: Once published, files cannot be easily changed or deleted.
• Size Limits: 50GB limit and 100 files per record.		 How to Host on Zenodo
CartoStore • Fully Managed: Provided by CartoScope team, removing maintenance burden.
• Reliable Infrastructure: Runs on AWS S3.		 • Access by Request: Not self-serve; you must reach out to us.
• Coordination: Uploads and updates are handled through the CartoScope team.		 Please contact us at cartoscope@umich.edu.

Step 3. Load Your Data

With your data hosted, choose how to access it in CartoScope:

Option A: Load via URL

Click the + URL button in the top bar and paste your dataset URL. No extra setup required — ideal for a single dataset or quick access.

Option B: Set Up a Data Library

If you have multiple datasets, set up a Data Library so all your datasets appear in the Datasets view alongside CartoStore — with full browsing and filtering, and no URL pasting needed.

Step 4. Explore Your Data

Once loaded, you can visualize and analyze your data:

  • Visual Exploration:
    • Add Layers: Create a multi-layer map by adding layers of your interest.
    • Orient View: Adjust the map perspective (rotation, flip).
  • In-Depth Analysis:
    • Explore Factors: Identify spatial patterns by examining factor layers, their distributions, marker genes, and UMAP embeddings.
    • Add Alias: Annotate your factor layers with meaningful names using manual edits, uploaded TSV files, or AI-inferred labels.
    • Create ROIs: Define regions of interest (ROIs) to investigate specific biological features.
    • Compare 2 ROIs: Perform differential expression (DE) analysis between ROIs.
    • Inspect a Spot: View detailed molecular profiles for specific locations.

Step 5. Share Your Results

Collaborate with others by sharing your findings directly.

Reference

You can find more detailed instructions on specific features in the following documents:

  • User Manual: A comprehensive guide to all interface elements and features.
  • How-To Guides: Step-by-step instructions for common tasks.