HIRAC

HIRAC infers the radial organization of chromosome territories within the nucleus from Hi-C pairwise contact data to analyze 3D genome organization across cell types and conditions.

Key Features:

• Data Input: Uses Hi-C data providing pairwise contact information between genomic loci, including inter-chromosomal contacts.
• Principal Component Analysis (PCA): Applies PCA to a thresholded inter-chromosomal contact matrix to infer relative chromosomal ordering.
• Force-Directed Network Layout: Employs a force-directed network layout to simulate an ensemble of possible chromosome territory (CT) arrangements for radial prediction.
• Integration of Chromosome Properties: Incorporates additional chromosome properties into predictions to enhance accuracy and relevance.
• Validation and Correlation: Predictions have been validated against microscopy imaging in lymphoblastoid, skin fibroblast, and breast epithelial cells and reproduce changes observed in senescent and progeria cells.
• Computational Efficiency: Predicts radial organization with lower computational demand compared to full-scale polymer models.

Scientific Applications:

• Nuclear Organization Analysis: Enables rapid, modular screening for alterations in chromosome territory radial organization across available Hi-C datasets.
• Biological Research: Supports investigation of nuclear architecture roles in gene regulation, cellular aging, and disease states such as progeria by analyzing CT radial arrangements.

Methodology:

Computational steps explicitly include thresholding inter-chromosomal Hi-C contact matrices, Principal Component Analysis (PCA) on the thresholded matrix, and force-directed network layout simulations of CT ensembles, with optional integration of chromosome properties.