ArticleGenome biology2022
Normalization and de-noising of single-cell Hi-C data with BandNorm and scVI-3D.
Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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48 citing papers in PubMed.
- Nuclear mechanotransduction: tools for mechanical perturbation and chromatin characterization.Nucleus (Austin, Tex.) · 2026Review
- ssJSD: A Fusion of Sparsity and Spatial Information for HiC Single-Cell Clustering.bioRxiv : the preprint server for biology · 2026Article
- Hi-Cformer enables multiscale chromatin contact map modeling for single-cell Hi-C data analysis.Science advances · 2026Article
- A generalizable Hi-C foundation model for chromatin architecture, single-cell and multiomics analysis across species.Nature methods · 2026Article
- Integrating single-cell RNA sequencing with multi-omics to decode disease microenvironments.Molecular biology reports · 2026Review
- MINTsC learns multi-way chromatin interactions from single cell high throughput chromatin conformation data.Nature communications · 2026Article
- ScSpTITH: a rank-correlation framework for robust quantification of multi-dimensional tumor heterogeneity.Human genetics · 2026Article
- Simultaneous modeling of chromatin conformation changes from multiple single-cell interaction maps with ChromMovie.Genome research · 2026Article
- SCUDDO: an unsupervised clustering algorithm for single-cell Hi-C maps using diagonal diffusion operators.Bioinformatics (Oxford, England) · 2026Article
- MINTsC learns multi-way chromatin interactions from single cell high throughput chromatin conformation data.bioRxiv : the preprint server for biology · 2026Article
- scDIAGRAM: detecting chromatin compartments from individual single-cell Hi-C matrix without imputation or reference features.Briefings in bioinformatics · 2026Article
- Harmonizing single-cell 3D genome data with STARK and scNucleome.Genome biology · 2026Article
- Cell-type-specific alkaloid and terpenoid biosynthesis in glandular trichomes: single-cell and spatial transcriptomic perspectives.Frontiers in plant science · 2026Review
- STRIVE: interpretable multimodal subtype discovery in Women's cancers using an attention-weighted joint variational autoencoder.Frontiers in bioinformatics · 2026Article
- Accurate and robust 3D genome feature discovery from multiplexed DNA FISH.bioRxiv : the preprint server for biology · 2025Article
- A comprehensive benchmark of single-cell Hi-C embedding tools.Nature communications · 2025Article
- Single-cell long-read Hi-C, scNanoHi-C2, details 3D genome reorganization in embryonic-stage germ cells.Nature structural & molecular biology · 2025Article
- Navigating the 3D genome at single-cell resolution: techniques, computation, and mechanistic landscapes.Briefings in bioinformatics · 2025Review
- scHiCcompare: An R Package for Differential Analysis of Single-cell Hi-C Data.Journal of molecular biology · 2025Article
- scHiCSRS: a self-representation smoothing method with Gaussian mixture model for imputing single cell Hi-C data.BMC bioinformatics · 2025Article
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3 authors.
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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, while scVI-3D exhibits advantages for rare cell types and under high sparsity scenarios. Application of BandNorm coupled with gene-associating domain analysis reveals scRNA-seq validated sub-cell type identification.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.