Normalization and de-noising of single-cell Hi-C data with BandNorm and scVI-3D

Ye Zheng, Siqi Shen & Sündüz Keleş
Abstract Single-cell high-throughput chromatin conformation capture methodologies (scHi-C) enable profiling of long-range genomic interactions. However, data from these technologies are prone to technical noise and biases that hinder downstream analysis. We develop a normalization approach, BandNorm, and a deep generative modeling framework, scVI-3D, to account for scHi-C specific biases. In benchmarking experiments, BandNorm yields leading performances in a time and memory efficient manner for cell-type separation, identification of interacting loci, and recovery of cell-type relationships,...
This data repository is not currently reporting usage information. For information on how your repository can submit usage information, please see our documentation.