ArticleNature communications2021
Sc-compReg enables the comparison of gene regulatory networks between conditions using single-cell data.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Joint inference of paired dynamical gene regulatory networks reveals distinct cell-state landscapes of neutrophil reprogramming.bioRxiv : the preprint server for biology · 2026Article
- Inference of spatial chromatin accessibility via integration of spatial transcriptomics and single-cell multi-omics data.Nature communications · 2026Article
- Differential gene regulatory network analysis reveals transcriptional disruption in opioid.NAR genomics and bioinformatics · 2026Article
- REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research.Bioinformatics (Oxford, England) · 2026Article
- Conserved Cell-Type-Specific Transcriptomic Networks and Regulatory Programs Underlie Alcohol Dependence Across Mouse and Human.Research square · 2026Article
- Benchmarking component choices for unpaired single cell RNA and epigenomic integration.Genome biology · 2026Article
- Leveraging transcription factor physical proximity for enhancing gene regulation inference.Bioinformatics (Oxford, England) · 2025Article
- The differential transpiration response of plants to stress.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Review
- Gene2role: a role-based gene embedding method for comparative analysis of signed gene regulatory networks.BMC bioinformatics · 2025Article
- CoTF-reg reveals cooperative transcription factors in oligodendrocyte gene regulation using single-cell multi-omics.Communications biology · 2025Article
- A mechanism-informed deep neural network enables prioritization of regulators that drive cell state transitions.Nature communications · 2025Article
- Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data.Nature biotechnology · 2025Article
- Small data methods in omics: the power of one.Nature methods · 2024Review
- Article
- Enhancer-driven gene regulatory networks inference from single-cell RNA-seq and ATAC-seq data.Briefings in bioinformatics · 2024Article
- Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights.BioEssays : news and reviews in molecular, cellular and developmental biology · 2024Review
- Unique challenges and best practices for single cell transcriptomic analysis in toxicology.Current opinion in toxicology · 2024Article
- Integration of single-cell transcriptome and chromatin accessibility and its application on tumor investigation.Life medicine · 2024Review
- Decoding leukemia at the single-cell level: clonal architecture, classification, microenvironment, and drug resistance.Experimental hematology & oncology · 2024Review
- Recent advances in exploring transcriptional regulatory landscape of crops.Frontiers in plant science · 2024Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
The comparison of gene regulatory networks between diseased versus healthy individuals or between two different treatments is an important scientific problem. Here, we propose sc-compReg as a method for the comparative analysis of gene expression regulatory networks between two conditions using single cell gene expression (scRNA-seq) and single cell chromatin accessibility data (scATAC-seq). Our software, sc-compReg, can be used as a stand-alone package that provides joint clustering and embedding of the cells from both scRNA-seq and scATAC-seq, and the construction of differential regulatory networks across two conditions. We apply the method to compare the gene regulatory networks of an individual with chronic lymphocytic leukemia (CLL) versus a healthy control. The analysis reveals a tumor-specific B cell subpopulation in the CLL patient and identifies TOX2 as a potential regulator of this subpopulation.
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