FreeHi-C

FreeHi-C simulates and augments high-throughput chromatin conformation (Hi-C) sequencing data to produce realistic chromatin contact maps for studying three-dimensional genome organization and benchmarking differential chromatin interaction detection.

Key Features:

• Nonparametric empirical estimation: Estimates interaction distributions among genome fragments without relying on predefined parametric models.
• Simulation of Hi-C reads: Simulates Hi-C reads from interacting genomic fragments to generate realistic contact data.
• High biological fidelity: Produces simulated data with high fidelity to actual biological Hi-C datasets for realistic evaluation.
• Data augmentation: Augments Hi-C datasets to increase power for downstream analyses, including differential interaction detection.
• False discovery rate control: Preserves false discovery rate control in augmented datasets to maintain statistical integrity.
• Benchmarking support: Provides realistic datasets suitable for benchmarking various Hi-C data analysis methods.

Scientific Applications:

• Benchmarking Hi-C analysis methods: Generates realistic test data for evaluating accuracy and performance of Hi-C pipelines.
• Development and evaluation of differential interaction detection: Augments data to improve power and assess methods for detecting differential chromatin interactions.
• Study of three-dimensional genome organization: Produces simulated contact maps that facilitate investigation of chromatin architecture.
• Method refinement and validation: Enables rigorous testing and refinement of analytical techniques using realistic simulated datasets.

Methodology:

Applies a nonparametric empirical estimation of interaction distributions among genome fragments and simulates Hi-C reads from interacting genomic fragments; performs data augmentation for differential interaction detection while preserving false discovery rate control.