How does it handle server connections?

It supports secure BlitzGateway connections using credentials or session IDs, with a strong emphasis on using context managers for safe resource management.

Can I manage Regions of Interest (ROIs)?

Yes, you can create, retrieve, and analyze various ROI shapes like polygons, masks, rectangles, and ellipses directly on the server.

Does it support image processing?

Absolutely. It facilitates extracting raw pixel data as NumPy arrays, allowing you to use libraries like scikit-image or OpenCV for analysis.

Can I use this for high-content screening (HCS)?

Yes, it includes specific capabilities for navigating HCS structures including Screens, Plates, Wells, and WellSamples.

What is the primary library used for this skill?

This skill primarily utilizes the omero-py library (BlitzGateway) to interact with OMERO servers for data management and analysis.

OMERO Microscopy Integration

Name: OMERO Microscopy Integration
Author: pur3v4d3r

bypur3v4d3r

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Data Science & ML

Manages and analyzes microscopy data using the OMERO Python API for advanced bioimage informatics workflows.

About

This skill integrates Claude with the OMERO platform, an open-source standard for managing, visualizing, and analyzing microscopy images. It provides comprehensive support for the omero-py library, enabling users to programmatically navigate complex data hierarchies, manipulate raw pixel data as NumPy arrays, and manage Regions of Interest (ROIs). Whether you are performing high-content screening or detailed single-image analysis, this skill streamlines scientific workflows by providing standardized patterns for session management, metadata annotation, and structured data storage via OMERO Tables.

Key Features

Hierarchical data navigation across Projects, Datasets, Screens, and Plates
Raw pixel data extraction into NumPy arrays for computational analysis
1 GitHub stars
Comprehensive OMERO Python API (omero-py) session and connection management
Programmatic management of ROIs, tags, and key-value metadata annotations
Server-side script development for batch processing and automated workflows

Use Cases

Batch processing of large microscopy datasets to generate projections and summary statistics
Automated extraction of pixel data for training machine learning models in bioimaging
Managing large-scale high-content screening data with custom metadata and ROI analysis

About

Key Features

Hierarchical data navigation across Projects, Datasets, Screens, and Plates
Raw pixel data extraction into NumPy arrays for computational analysis
1 GitHub stars
Comprehensive OMERO Python API (omero-py) session and connection management
Programmatic management of ROIs, tags, and key-value metadata annotations
Server-side script development for batch processing and automated workflows

Use Cases

Batch processing of large microscopy datasets to generate projections and summary statistics
Automated extraction of pixel data for training machine learning models in bioimaging
Managing large-scale high-content screening data with custom metadata and ROI analysis