# Robust mapping of chromatin loops from sparse or single cell Hi-C data with DeepLoop

> **NIH NIH R01** · CASE WESTERN RESERVE UNIVERSITY · 2022 · $621,802

## Abstract

Project Abstract
 Mapping the gene-regulatory chromatin interactions within topologically associated domains (sub-
TAD) remains a major challenge in 3D genome research. It is generally believed that multibillion-read
sequencing depth are required for Hi-C analysis at kilobase-resolution due to the complex bias structure
and severe data sparsity. However, we recently discovered that this is problem can be largely solved
computationally without the need for ultradeep-sequencing. We developed a new pipeline named
DeepLoop that can robustly identify high-resolution chromatin interactions from low-depth Hi-C data. The
conceptual innovation of DeepLoop is to handle systematic biases and random noises separately: we
used HiCorr to improve the rigor of bias correction, and then applied deep-learning techniques for noise
reduction and loop signal enhancement. Preliminary results showed that DeepLoop significantly improves
the sensitivity, robustness, and quantitation of Hi-C loop analyses, and can be used to reanalyze most
published low-depth Hi-C datasets. Remarkably, DeepLoop can identify chromatin loops with Hi-C data
from a few dozen single cells. These successes motivate us to further optimize, benchmark, simplify and
upgrade DeepLoop into a versatile tool for the 3D genome field. Aim 1 will optimize and benchmark
DeepLoop performance, improve its compatibility with a variety of different Hi-C protocols, and expand
its utility to ultra-resolution analysis. Aim 2 will develop new DeepLoop-based pipelines to enable robust
mapping of dynamic chromatin loops at high-resolution, including the identification of homolog-specific
loops and loops affected by structure variants. Aim 3 will develop a full-package solution for high-
resolution loop analysis of complex tissues with single cell Hi-C, a significant amount of data will be
generated in this project as a resource for the scientific community.

## Key facts

- **NIH application ID:** 10519772
- **Project number:** 2R01HG009658-06
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** Fulai Jin
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $621,802
- **Award type:** 2
- **Project period:** 2017-08-03 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10519772

## Citation

> US National Institutes of Health, RePORTER application 10519772, Robust mapping of chromatin loops from sparse or single cell Hi-C data with DeepLoop (2R01HG009658-06). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10519772. Licensed CC0.

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