FisHiCal: an R package for iterative FISH-based calibration of Hi-C data

Area of Science:

• Genomics
• Computational Biology
• Molecular Biology

Background:

• Fluorescence in situ hybridization (FISH) provides physical distance data between loci through image analysis.
• Hi-C technology offers high-throughput data on chromosomal contacts, both within and between chromosomes.
• Integrating these complementary methods can yield a more comprehensive understanding of 3D genome organization.

Purpose of the Study:

• To present FisHiCal, an R package designed for iterative calibration of FISH and Hi-C data.
• To develop and implement 3D inference methods for enhanced usability and accuracy.
• To establish an iterative calibration pipeline for quality assessment and meta-analysis of 3D genome data.

Main Methods:

• Developed an R package, FisHiCal, for iterative FISH-based Hi-C calibration.
• Implemented a calibration model that leverages information from both FISH and Hi-C data.
• Introduced 3D reconstruction via local stress minimization and spatial inconsistency detection methods.
• Validated the calibration model across three human cell lines.

Main Results:

• FisHiCal successfully integrates FISH and Hi-C data, providing enhanced resolution of 3D genome structure.
• The developed 3D inference methods improve the usability and reliability of the calibration.
• The iterative calibration pipeline demonstrates utility in quality assessment and meta-analysis.

Conclusions:

• FisHiCal offers a robust framework for calibrating FISH and Hi-C data, advancing 3D genome studies.
• The package facilitates improved interpretation of genomic spatial organization.
• This approach supports quality control and enables meta-analyses of diverse 3D genomics datasets.