Analysis Module
The analysis module provides comprehensive tools for quantitative analysis of cellular imaging data, extracting biologically meaningful features from segmented organelles and partitioned cytoplasmic regions.
Overview
Based on the radial cytoplasmic partitioning framework, iPA extracts diverse organelle features across four key dimensions (as described in the manuscript):
Morphology: Volume, surface area, length, and shape descriptors of subcellular structures
Spatial Arrangement: Radial Distribution Functions (RDF), organelle pools, angle distributions, and aggregation patterns
Dynamics: 3D velocity and radial velocity from time-lapse imaging
Interactions: Distance-based and contact-based analysis between different organelle types
This multi-dimensional feature extraction enables both intra-modal analysis (within a single imaging modality) and inter-modal comparison (across WFM, SIM, SXT, and cryo-ET), providing a comprehensive view of cell structure and function.
Key Capabilities
Radial Distribution Function (RDF): Standardized quantification of organelle localization from NE to PM
14 Predefined Interaction Types: Comprehensive coverage of organelle-organelle spatial relationships
Multi-Organelle Support: ISGs, F-actin, microtubules, mitochondria, ER, vesicles
Cross-Modal Compatibility: Consistent analysis pipeline across all supported imaging modalities
Statistical Rigor: Pearson correlation, distance statistics, contact probability calculations
Supported Analyses
The analysis module is organized into four specialized sub-modules:
Morphology Analysis: Extract structural features (volume, length, shape) from segmented masks
Distribution Analysis: Calculate RDF and analyze spatial arrangement patterns
Interaction Analysis: Quantify distances and contacts between different organelle types
Dynamics Analysis: Analyze velocity and motion patterns from time-lapse data
Each sub-module provides both low-level functions for custom workflows and high-level analysis pipelines for standard use cases.