MetaChrome Documentation

MetaChrome Interface

The MetaChrome toolkit for chromosome analysis

An automatic deep learning toolkit for metaphase chromosome analysis, written in Python using Napari and Cellpose. It enables researchers to analyze multi-channel fluorescence microscopy images for chromosome segmentation, spot detection, and intensity quantification.

Chromosome segmentation example

Key Features:

  • Automated Segmentation - Cellpose-based chromosome detection

  • Multi-Channel Analysis - DAPI, DNA-FISH, and protein marker support

  • Spot Detection - Adjustable threshold-based detection

  • Interactive Visualization - Built on Napari platform

  • Batch Processing - High-throughput analysis

  • Manual Corrections - Interactive refinement tools

This toolkit integrates tools for detecting centromeres and measuring CENP-A levels within metaphase chromosome regions, enhancing the accuracy of chromosome analysis for researchers at the National Cancer Institute/NIH and beyond.

Contents

Introduction

Tutorial

User Guide

API Reference

Quick Navigation

I want to…

Go to…

Understand what this toolkit does

Getting Started

Install the software

Installation

Learn to analyze images

Tutorial

Understand the complete workflow

Basic Workflow

Process many images

Batch Processing

Fix detection errors

Manual Corrections

Optimize parameters

Advanced Features

Solve a problem

Troubleshooting

Use the API programmatically

API Documentation

Example Workflow

Spot detection visualization

Example of spot detection results

A typical analysis workflow:

  1. Configure channel identifiers → 2. Load images → 3. Segment chromosomes → 4. Detect spots → 5. Find common regions → 6. Measure intensities → 7. Export results

See the Tutorial for a step-by-step walkthrough.

Use Cases

This toolkit is designed for researchers working on:

Chromosome Structure Analysis

Quantitative assessment of metaphase chromosome morphology and organization.

Protein Localization Studies

Analyze protein markers such as CENP-C, CENP-A, histone modifications, and other chromatin-associated proteins.

DNA-FISH Analysis

Detection and quantification of specific DNA sequences in metaphase chromosomes.

Signal Co-localization

Spatial relationships between different fluorescent markers on chromosomes.

High-Throughput Screening

Automated analysis of large image datasets from screening experiments.

Image Requirements

Required Channels:

  • DAPI - Chromosome/nuclear staining for segmentation

  • DNA-FISH (Channel 1) - Specific DNA sequence detection

  • Protein Marker (Channel 2) - Protein localization (e.g., CENP-C, CENP-A, histone modifications)

Supported Formats:

TIFF (recommended), PNG, JPG

File Naming:

Images should contain identifiable strings (e.g., sample_001_w435.tif, sample_001_w525.tif, sample_001_w679.tif)

Example Results

Multi-channel analysis result

Complete analysis showing detected spots in both channels

Outputs:

  • Visual overlays (segmented chromosomes + detected spots)

  • CSV files with coordinates and intensity measurements

  • Summary statistics for batch-processed datasets

  • Exportable images for presentations and publications

Performance

Processing Speed:

  • Single image: ~30-60 seconds (with GPU)

  • Batch of 100 images: ~1-2 hours (with GPU)

Accuracy:

  • Chromosome segmentation: High accuracy with trained Cellpose models

  • Spot detection: Adjustable sensitivity via threshold controls

  • Manual correction: Interactive refinement for maximum accuracy

Citation

If you use this toolkit in your research, please cite:

bioRxiv preprint: https://www.biorxiv.org/content/10.1101/2025.09.02.673813v1

Author: Md Abdul Kader Sagar Email: sagarm2@nih.gov Affiliation: HITIF/LRBGE/CCR/NCI (National Cancer Institute/NIH)

License

This project is developed at the National Cancer Institute/NIH.

Contact and Support

Questions or Issues?

Community Resources:

Indices and Tables