TANGO

TANGO analyzes 3D fluorescence microscopy images to quantify nuclear architecture and extract measurements for statistical analysis of nuclear compartments.

Key Features:

• Integrated framework: Integration of ImageJ for image processing and segmentation with R (rtango) for statistical processing of measurement results.
• ImageJ plug-in for 3D image processing and segmentation: Implements segmentation procedures and extracts quantitative measurements from 3D fluorescence image datasets.
• rtango R package for statistical analysis: Processes measurement results from ImageJ to perform statistical analyses within R.
• High-throughput scalability: Capable of processing large sets of images to support quantitative studies of nuclear organization.
• Quantitative exploration of nuclear architecture: Combines image processing and statistical analysis to derive quantitative descriptors of nuclear compartments and spatial organization.

Scientific Applications:

• Nuclear architecture studies: Quantitative analysis of the spatial organization of the nucleus and nuclear compartments from 3D fluorescence images.
• Gene expression and DNA replication research: Supports investigations into how nuclear organization influences gene expression and DNA replication.
• High-throughput quantitative cell biology: Enables extraction of quantitative data from large 3D imaging datasets for cellular biology studies.

Methodology:

Computational workflow uses an ImageJ plug-in for image processing and segmentation and the rtango package in R for statistical analysis of the extracted measurements.