iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution

Author:

Li Kai12,Zhang Ping12ORCID,Wang Zilin12,Shen Wei12,Sun Weicheng12,Xu Jinsheng12,Wen Zi12,Li Li123ORCID

Affiliation:

1. Hubei Key Laboratory of Agricultural Bioinformatics , College of Informatics, , Wuhan 430070 , China

2. Huazhong Agricultural University , College of Informatics, , Wuhan 430070 , China

3. Hubei Hongshan Laboratory, Huazhong Agricultural University , Wuhan 430070 , China

Abstract

Abstract Although sequencing-based high-throughput chromatin interaction data are widely used to uncover genome-wide three-dimensional chromatin architecture, their sparseness and high signal-noise-ratio greatly restrict the precision of the obtained structural elements. To improve data quality, we here present iEnhance (chromatin interaction data resolution enhancement), a multi-scale spatial projection and encoding network, to predict high-resolution chromatin interaction matrices from low-resolution and noisy input data. Specifically, iEnhance projects the input data into matrix spaces to extract multi-scale global and local feature sets, then hierarchically fused these features by attention mechanism. After that, dense channel encoding and residual channel decoding are used to effectively infer robust chromatin interaction maps. iEnhance outperforms state-of-the-art Hi-C resolution enhancement tools in both visual and quantitative evaluation. Comprehensive analysis shows that unlike other tools, iEnhance can recover both short-range structural elements and long-range interaction patterns precisely. More importantly, iEnhance can be transferred to data enhancement of other tissues or cell lines of unknown resolution. Furthermore, iEnhance performs robustly in enhancement of diverse chromatin interaction data including those from single-cell Hi-C and Micro-C experiments.

Funder

Huazhong Agricultural University Scientific and Technological Self-innovation Foundation

Hefei Advanced Computing Center

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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