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bioRxiv · 10.1101/2021.03.10.434870

Normalization and De-noising of Single-cell Hi-C Data with BandNorm and 3DVI

Zheng, Y.·Shen, S.·Keles, S.
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Abstract

Single-cell high-throughput chromatin conformation capture methodologies (scHi-C) enable profiling long-range genomic interactions at the single-cell resolution; however, data from these technologies are prone to technical noise and bias that, when unaccounted for, hinder downstream analysis. Here we developed a fast band normalization approach, BandNorm, and a deep generative modeling framework, 3DVI, to explicitly account for scHi-C specific technical biases. We present robust performances of BandNorm and 3DVI compared to existing state-of-the-art methods. BandNorm is effective in separating cell types, identification of interaction features, and recovery of cell-cell relationship, whereas de-noising by 3DVI successfully enables 3D compartments and domains recovery, especially for rare cell types.

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Zheng, Y., Shen, S., Keles, S.. 2021-03-11. Normalization and De-noising of Single-cell Hi-C Data with BandNorm and 3DVI. https://doi.org/10.1101/2021.03.10.434870

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