4DNvestigator

4DNvestigator analyzes time-series genome-wide Hi-C and RNA-seq data to quantify temporal changes in chromosome conformation and gene expression for studying 4D Nucleome dynamics.

Key Features:

• Integration of time-series Hi-C and RNA-seq: Integrates time-series Hi-C (chromosome conformation capture) and RNA-seq datasets to combine chromatin interaction and gene expression information.
• Entropy metrics: Computes network entropy to measure complexity and variability of chromatin interaction networks and tensor entropy to assess multi-dimensional structure in genomic interaction data.
• Statistical analysis of temporal changes: Implements statistical methods to detect significant changes in Hi-C data across time points and genomic scales.
• Network-based analyses: Constructs and analyzes chromatin interaction networks from Hi-C to quantify topological properties over time and support interpretation.
• Large-scale data processing: Processes and analyzes large-scale genome-wide Hi-C and RNA-seq datasets.
• Implementation: Provided as a MATLAB toolbox for processing and analysis of time-series genome-wide data.

Scientific Applications:

• Genome organization studies: Analyzes Hi-C data to explore the spatial organization of chromosomes and its temporal evolution.
• Gene expression dynamics: Relates RNA-seq gene expression changes to chromatin conformation over time.
• Epigenetic research: Investigates how temporal changes in genome structure relate to epigenetic modifications and cellular function.

Methodology:

Uses a network-based approach to construct chromatin interaction networks from time-series Hi-C, integrates RNA-seq, computes network and tensor entropy metrics, applies statistical tests to identify significant temporal changes across genomic scales, and supports visualization of complex interactions.