hichipper

hichipper processes HiChIP sequencing data in Python to perform bias-corrected peak calling, library quality control, and DNA loop calling for chromatin conformation analysis.

Key Features:

• Bias-Corrected Peak Calling: Performs bias-corrected peak calling on HiChIP data to accurately identify enriched chromatin regions while minimizing systematic sequencing and assay biases.
• Library Quality Control: Computes library QC metrics specific to HiChIP library preparation and sequencing to assess data integrity prior to downstream analysis.
• DNA Loop Calling: Identifies DNA loops and chromatin interactions from HiChIP contact data to map three-dimensional genome organization.
• Output for Downstream Analysis and Visualization: Produces processed data outputs formatted for integration into downstream analytical workflows and visualization tools.

Scientific Applications:

• Gene Regulation Studies: Enables analysis of chromatin interactions that influence gene expression by providing peaks and loop calls from HiChIP data.
• Epigenetic Research: Supports investigation of protein-mediated chromatin interactions and their roles in epigenetic regulation using HiChIP-derived contacts and peaks.
• Disease Mechanism Exploration: Facilitates identification of structural genomic alterations and interaction changes associated with disease states from HiChIP datasets.

Methodology:

Implements bias-correction algorithms and statistical models for peak calling, library quality control, and DNA loop calling as a Python-based preprocessing pipeline for HiChIP data.