¶ Quick start guide
Welcome to ariadne.ai SPATIAL. This guide walks you through the first steps to get your data loaded and your first analysis running. For a full end-to-end analysis walkthrough, see the Guides section.
¶ Setup
- Open https://spatial.ariadne.ai
- Log in or sign up depending on whether you have an account.
- The dataset management window will appear.
- Click on one of your existing datasets to start working with it, or click + DATASET to upload a new dataset. The upload window will appear where you can select and submit your files.
¶ The main window
SPATIAL is organized around three panels surrounding your image data.
Left panel — Visualization: Shows all available layers for your dataset, organized by category: image channels, segmentations, selections, and marker layers. Click the eye icon to show or hide a layer. Click the layer name to adjust its color, opacity, brightness, and contrast.
Right panel — Statistics: Gives you access to per-cell marker intensities, manual gating, dimensionality reduction results (t-SNE, UMAP), and the outputs of spatial analysis jobs (RCN, Neighborhood Enrichment). Click + to add a new view.
Top panel — Navigation: Shows your current x, y, and z coordinates and zoom level. Use the CENTER button to fit your dataset in view, 1:1 to reset zoom, and the JOBS button to monitor running and completed jobs.
¶ Submitting your first jobs
To analyze your data, click the NEW JOB button (top left) and work through the following jobs in order. Each step builds on the previous one.
- Registration (multi-cycle experiments only) — align image channels from different staining cycles onto a common reference.
- Cell Segmentation or Nucleus Expansion — detect and outline individual cells in your tissue.
- Intensity Map — measure marker expression within each segmented cell, creating a per-cell data table (Mapping).
- t-SNE or UMAP (optional) — reduce your per-cell data to 2D to explore and gate cell populations visually.
- Recurrent Neighborhoods or Neighborhood Enrichment — quantify the spatial organization of your cell populations.
For a detailed description of each job and its parameters, see Submitting Jobs.
¶ Next steps
- New to spatial analysis? Read the Analysis Workflows guide for a complete step-by-step walkthrough.
- Want to understand the methods? See the Statistical analysis page for in-depth descriptions of RCN and Neighborhood Enrichment.
- Questions? Get in touch with the ariadne.ai team — we are happy to help.