/omero-integration

name: omero-integration
description: Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
license: Unknown
metadata:
    skill-author: K-Dense Inc.

OMERO Integration

Overview

OMERO is an open-source platform for managing, visualizing, and analyzing microscopy images and metadata. Access images via Python API, retrieve datasets, analyze pixels, manage ROIs and annotations, for high-content screening and microscopy workflows.

Routing Boundary

Use this skill for OMERO server access, OMERO Python API work, microscopy image server data retrieval, ROI annotation, image metadata management, and high-content screening image management. Generic microscopy literature search, DICOM tags, IDC/TCIA retrieval, histolab tiling, PathML computational pathology, scRNA-seq, flow cytometry, and generic image processing are outside this skill.

When to Use This Skill

This skill should be used when:

• Working with OMERO Python API (omero-py) to access microscopy data
• Retrieving images, datasets, projects, or screening data programmatically
• Analyzing pixel data and creating derived images
• Creating or managing ROIs (regions of interest) on microscopy images
• Adding annotations, tags, or metadata to OMERO objects
• Storing measurement results in OMERO tables
• Creating server-side scripts for batch processing
• Performing high-content screening analysis

Core Capabilities

This skill covers eight major capability areas. Each is documented in detail in the references/ directory:

1. Connection & Session Management

**File**: `references/connection.md`

Establish secure connections to OMERO servers, manage sessions, handle authentication, and work with group contexts. Use this for initial setup and connection patterns.

**Common scenarios:**

• Connect to OMERO server with credentials
• Use existing session IDs
• Switch between group contexts
• Manage connection lifecycle with context managers

2. Data Access & Retrieval

**File**: `references/data_access.md`

Navigate OMERO's hierarchical data structure (Projects → Datasets → Images) and screening data (Screens → Plates → Wells). Retrieve objects, query by attributes, and access metadata.

**Common scenarios:**

• List all projects and datasets for a user
• Retrieve images by ID or dataset
• Access screening plate data
• Query objects with filters

3. Metadata & Annotations

**File**: `references/metadata.md`

Create and manage annotations including tags, key-value pairs, file attachments, and comments. Link annotations to images, datasets, or other objects.

**Common scenarios:**

• Add tags to images
• Attach analysis results as files
• Create custom key-value metadata
• Query annotations by namespace

4. Image Processing & Rendering

**File**: `references/image_processing.md`

Access raw pixel data as NumPy arrays, manipulate rendering settings, create derived images, and manage physical dimensions.

**Common scenarios:**

• Extract pixel data for computational analysis
• Generate thumbnail images
• Create maximum intensity projections
• Modify channel rendering settings

5. Regions of Interest (ROIs)

**File**: `references/rois.md`

Create, retrieve, and analyze ROIs with various shapes (rectangles, ellipses, polygons, masks, points, lines). Extract intensity statistics from ROI regions.

**Common scenarios:**

• Draw rectangular ROIs on images
• Create polygon masks for segmentation
• Analyze pixel intensities within ROIs
• Export ROI coordinates

6. OMERO Tables

**File**: `references/tables.md`

Store and query structured tabular data associated with OMERO objects. Useful for analysis results, measurements, and metadata.

**Common scenarios:**

• Store quantitative measurements for images
• Create tables with multiple column types
• Query table data with conditions
• Link tables to specific images or datasets

7. Scripts & Batch Operations

**File**: `references/scripts.md`

Create OMERO.scripts that run server-side for batch processing, automated workflows, and integration with OMERO clients.

**Common scenarios:**

• Process multiple images in batch
• Create automated analysis pipelines
• Generate summary statistics across datasets
• Export data in custom formats

8. Advanced Features

**File**: `references/advanced.md`

Covers permissions, filesets, cross-group queries, delete operations, and other advanced functionality.

**Common scenarios:**

• Handle group permissions
• Access original imported files
• Perform cross-group queries
• Delete objects with callbacks

Installation

uv pip install omero-py

**Requirements:**

• Python 3.7+
• Zeroc Ice 3.6+
• Access to an OMERO server (host, port, credentials)

Quick Start

Basic connection pattern:

from omero.gateway import BlitzGateway

# Connect to OMERO server
conn = BlitzGateway(username, password, host=host, port=port)
connected = conn.connect()

if connected:
    # Perform operations
    for project in conn.listProjects():
        print(project.getName())

    # Always close connection
    conn.close()
else:
    print("Connection failed")

**Recommended pattern with context manager:**

from omero.gateway import BlitzGateway

with BlitzGateway(username, password, host=host, port=port) as conn:
    # Connection automatically managed
    for project in conn.listProjects():
        print(project.getName())
    # Automatically closed on exit

Selecting the Right Capability

**For data exploration:**

• Start with `references/connection.md` to establish connection
• Use `references/data_access.md` to navigate hierarchy
• Check `references/metadata.md` for annotation details

**For image analysis:**

• Use `references/image_processing.md` for pixel data access
• Use `references/rois.md` for region-based analysis
• Use `references/tables.md` to store results

**For automati