Data portal

copick CZ cryoET Data Portal

The CZ cryoET Data Portal provides standardized access to cryoET datasets and annotations. This tutorial demonstrates how to access datasets and annotations stored on the CZ cryoET Data Portal as static data in a copick project.

Step 1: Install copick

See the quickstart guide for instructions on how to install copick.

Step 2: Set up your project

We will create a project that uses dataset 10301 from the CZ cryoET Data Portal, and store any locally created annotations in a local directory called the "overlay".

You no longer need to write a configuration file by hand — the copick config dataportal command builds it for you:

copick config dataportal \
    --dataset-id 10301 \
    --overlay ./overlay \
    --output copick_config.json

This writes a copick_config.json that reads tomograms, picks, and other annotations directly from dataset 10301 (the portal data stays read-only), while anything you create is written to the local ./overlay directory. copick discovers the pickable objects automatically from the dataset's portal annotations — their names, particle vs. segmentation type, ontology/PDB/EMDB metadata, labels, and colors are all filled in for you, so there is no need to list pickable_objects or look up Gene Ontology IDs manually.

To combine several portal datasets into a single project, pass --dataset-id (-ds) once per dataset:

copick config dataportal \
    -ds 10301 -ds 10302 \
    --overlay ./overlay \
    --output copick_config.json

{
    "config_type": "cryoet_data_portal",
    "name": "CZ cryoET Data Portal Dataset",
    "description": "This copick project contains data from datasets [10301].",
    "pickable_objects": [
        {
            "name": "ribosome",
            "is_particle": true,
            "identifier": "GO:0022626",
            "label": 1,
            "color": [0, 117, 220, 255],
            "radius": 150.0
        },
        {
            "name": "membrane",
            "is_particle": false,
            "identifier": "GO:0016020",
            "label": 2,
            "color": [200, 200, 200, 255],
            "radius": 10.0
        }
        // ... remaining objects discovered from the dataset
    ],
    "overlay_root": "local://./overlay",
    "overlay_fs_args": {
        "auto_mkdir": true
    },
    "dataset_ids": [10301]
}

Adding your own objects

You can also annotate structures that are not yet on the portal. Register a new object with copick add object; it is stored only in the overlay, alongside the auto-discovered portal objects:

copick add object --config copick_config.json --name prohibitin \
    --object-type particle --radius 10 --color "155,117,220,255"

Objects added without an --identifier are overlay-only. Pass --identifier GO:… (a Gene Ontology ID or UniProtKB accession) instead to link a new object to matching annotations already on the data portal.

Step 3: Visualize, curate or process the data

You can now use the copick API to access the data from dataset 10301 and the overlay directory. As a first step, you can print the available objects and runs — including the objects copick discovered from the portal.

"""Print all objects and runs in a copick project."""

import copick

# Initialize the root object from a configuration file
root = copick.from_file("path/to/config.json")

# List all available objects
obj_info = [(o.name, o.label) for o in root.pickable_objects]

print("Pickable objects in this project:")
for name, label in obj_info:
    print(f"  {name}: {label}")

# Execute a function on each run in the project
runs = root.runs

print("Runs in this project:")
for run in runs:
    print(f"Run: {run.name}")
    # Do something with the run

Visualization works as with any other copick project. For more information, see the tutorial on ChimeraX-copick integration., or check out CellCanvas or napari-copick for alternative visualization options.