peakC: a flexible, non-parametric peak calling package for 4C and Capture-C data

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Chromosome organization is crucial for gene regulation.
• High-resolution techniques like 4C, Capture-C, and promoter capture Hi-C (PCHiC) reveal chromatin loops between regulatory elements.
• Reliable statistical identification of these loops is essential for accurate analysis.

Purpose of the Study:

• To present peakC, a user-friendly R package for robustly identifying chromatin loops from 4C, Capture-C, and PCHiC data.
• To provide a statistical method for peak calling in one-vs-all chromosome capture experiments.

Main Methods:

• Development of a non-parametric peak caller based on rank-products.
• Generation of 4C data from 13 viewpoints in two tissues, with replicates.
• Analysis of factors influencing 4C experiment success, such as read depth and template quality.

Main Results:

• PeakC enables robust and reproducible statistical identification of chromatin loops.
• Template quality, not read depth, is the key determinant of 4C experiment success.
• Replicate experiments significantly reduce false positive rates in peak calling.

Conclusions:

• PeakC offers a reliable software solution for analyzing chromosome capture data.
• The package facilitates accurate identification of chromatin loops, advancing gene regulation research.
• Emphasis on template quality and replicates is crucial for high-confidence 4C/Capture-C/PCHiC results.