Web GUI Quickstart (Standalone)

The bundled web GUI is a visual DAG editor for building pyCyto pipelines without writing YAML by hand — designed for biologists and other non-programmer users.

This guide covers standalone mode: running everything locally via Docker Compose, with no cluster/SLURM connection. If you need cluster execution, see your institution’s advanced setup guide.

1. Start the stack

docker compose -f docker-compose.distribution.yml up

Open http://localhost:3003 in your browser.

2. Build a pipeline

  1. Drag nodes from the palette (left) onto the canvas — organized by stage: Data I/O, Preprocessing, Segmentation, Tabulation, Tracking, Postprocessing.

  2. Connect nodes to define the DAG (data flows top-to-bottom by pipeline stage).

  3. Click a node to open the Inspector (right panel) and set its parameters (e.g. channel names, model thresholds).

  4. Use the File Browser to point Data I/O nodes at your input images, mounted into the container’s /data volume.

3. Compile and run

  1. Click Export to compile the DAG into a pipeline.yaml / pipeline-resources.yaml pair, written under /data/output/webgui_pipelines.

  2. Run the compiled pipeline from a terminal against the cyto service:

    docker compose -f docker-compose.distribution.yml run --rm cyto \
  cyto --pipeline /data/output/webgui_pipelines/<workflow>.yaml -v

The GUI’s in-app Run button currently submits to a SLURM cluster and isn’t available in standalone mode — use the Export + CLI steps above until local execution is added to the web GUI.

4. Save / load

Use Save / Load in the top bar to persist a DAG design as a workflow file you can reopen later or share with a colleague.

Notes

  • Standalone mode has no SLURM/cluster connection — pipeline execution happens via the cyto CLI as shown above.

  • For large datasets, GPU-accelerated segmentation (StarDist/Cellpose) requires the NVIDIA Container Toolkit — see docker-install.