ArticleNature communications2024
scCASE: accurate and interpretable enhancement for single-cell chromatin accessibility sequencing data.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Graph neural networks for single-cell omics data: a review of approaches and applications.Briefings in bioinformatics · 2025Pooled it
- DiTSim: A Diffusion-Transformers Based Single-Cell ATAC-seq Data Simulator.Interdisciplinary sciences, computational life sciences · 2026Article
- Integrative Epigenomics: Bioinformatics Strategies for Multi-Omics Data Analysis in Health and Disease.Epigenomes · 2026Review
- Dissecting epigenetic heterogeneity in single-cell DNA methylomes with a unified framework.Nature communications · 2026Article
- Deep learning-driven prediction of on-target activity, off-target risk, and repair outcomes in CRISPR/Cas9: current landscape and multi-scale perspectives.Journal of translational medicine · 2026Review
- High-fidelity bidirectional translation between single-cell transcriptomes and DNA methylomes with scBOND.Genome research · 2026Article
- Bridging the dimensional gap from planar spatial transcriptomics to 3D cell atlases.Nature methods · 2026Article
- Human-scATAC-Corpus: a comprehensive database of scATAC-seq data.Nucleic acids research · 2026Article
- Article
- Recent advances in methodologies of epigenomics.Epigenomics · 2026Review
- EpiAgent: foundation model for single-cell epigenomics.Nature methods · 2025Article
- Imputing not available values in single-cell DNA methylation data using the median is straightforward and effective.Quantitative biology (Beijing, China) · 2025Article
- soFusion: facilitating tissue structure identification via spatial multi-omics data fusion.Briefings in bioinformatics · 2025Article
- IMATAC imputes single-cell ATAC-seq data by deep hierarchical network with denoising autoencoder.Briefings in bioinformatics · 2025Article
- MINGLE: a mutual information-based interpretable framework for automatic cell type annotation in single-cell chromatin accessibility data.Genome biology · 2025Article
- CREATE: cell-type-specific cis-regulatory element identification via discrete embedding.Nature communications · 2025Article
- EpiCarousel: memory- and time-efficient identification of metacells for atlas-level single-cell chromatin accessibility data.Bioinformatics (Oxford, England) · 2024Article
- scCASE: accurate and interpretable enhancement for single-cell chromatin accessibility sequencing data.Nature communications · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell chromatin accessibility sequencing (scCAS) has emerged as a valuable tool for interrogating and elucidating epigenomic heterogeneity and gene regulation. However, scCAS data inherently suffers from limitations such as high sparsity and dimensionality, which pose significant challenges for downstream analyses. Although several methods are proposed to enhance scCAS data, there are still challenges and limitations that hinder the effectiveness of these methods. Here, we propose scCASE, a scCAS data enhancement method based on non-negative matrix factorization which incorporates an iteratively updating cell-to-cell similarity matrix. Through comprehensive experiments on multiple datasets, we demonstrate the advantages of scCASE over existing methods for scCAS data enhancement. The interpretable cell type-specific peaks identified by scCASE can provide valuable biological insights into cell subpopulations. Moreover, to leverage the large compendia of available omics data as a reference, we further expand scCASE to scCASER, which enables the incorporation of external reference data to improve enhancement performance.
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Registered trials
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.