CWL-Based Analysis Pipeline for Hi-C Data: From FASTQ Files to Matrices

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• The Hi-C method has been pivotal in analyzing 3D genome organization for over a decade.
• Analysis of large Hi-C datasets, generated using next-generation sequencing (NGS), is computationally intensive.
• A growing need exists to simplify Hi-C data processing for broader accessibility and utilization.

Purpose of the Study:

• To present a standardized, reproducible, and portable Common Workflow Language (CWL)-based pipeline for Hi-C data analysis.
• To enable users to generate Hi-C contact matrices in standard formats (.hic, .mcool) comparable to those in the 4D Nucleome (4DN) Data Portal.
• To facilitate comparative genomic analyses by providing a consistent analysis framework.

Main Methods:

• Implementation of a CWL-based analysis pipeline within the 4DN Data Portal ecosystem.
• Processing of raw FASTQ files to generate standard Hi-C contact matrices.
• Utilizing custom scripts, made available on GitHub, for pipeline execution.

Main Results:

• The pipeline successfully generates standard Hi-C contact matrices from FASTQ files.
• The analyzed data is compatible with the formats available on the 4DN Data Portal, enabling direct comparison.
• The CWL pipeline ensures reproducibility and portability of Hi-C data analysis.

Conclusions:

• The developed CWL pipeline significantly reduces the computational burden of Hi-C data analysis.
• This standardized approach enhances the usability of large Hi-C datasets for research.
• The pipeline supports efficient comparative analysis of 3D genome organization across different studies and cell types.