Assessing Reproducibility of Hi-C Chromatin Interactions using Stratum-Adjusted Irreproducible Discovery Rate.

Xue, Chen; Zhang, Feipeng; Li, Qunhua · Bioinformatics · 2026

basic_science · Level V

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Abstract

Hi-C is a powerful technology for mapping chromatin interactions genome-wide. However, interaction loops identified from Hi-C contact maps often vary across replicate experiments due to experimental noise, making reproducibility assessment essential. A major challenge lies in the genomic distance dependence of interaction strength, which systematically affects reproducibility but is overlooked by existing methods for reproducibility assessment. We introduce Stratum-Adjusted Irreproducible Discovery Rate (SIDR), a novel statistical model that integrates distance stratification into the widely-used Irreproducible Discovery Rate (IDR) framework. SIDR explicitly models the confounding effect of genomic distance, enabling global control of irreproducibility across interaction ranges. Through simulations and real Hi-C datasets, we demonstrate that SIDR improves discriminative power and recovers more biologically meaningful interactions than existing approaches, making it a valuable tool for robust and reproducible Hi-C analysis. The R package SIDR is freely available on GitHub https://github.com/qunhualilab/SIDR.