ArticleBriefings in bioinformatics2021
Joint reconstruction of cis-regulatory interaction networks across multiple tissues using single-cell chromatin accessibility data.
Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Inference of spatial chromatin accessibility via integration of spatial transcriptomics and single-cell multi-omics data.Nature communications · 2026Article
- Single-cell omics: experimental workflow, data analyses and applications.Science China. Life sciences · 2025Review
- DECA: harnessing interpretable transformer model for cellular deconvolution of chromatin accessibility profile.Briefings in bioinformatics · 2024Article
- Complex regulatory networks influence pluripotent cell state transitions in human iPSCs.Nature communications · 2024Article
- simCAS: an embedding-based method for simulating single-cell chromatin accessibility sequencing data.Bioinformatics (Oxford, England) · 2023Article
- A systematic evaluation of the computational tools for ligand-receptor-based cell-cell interaction inference.Briefings in functional genomics · 2022Article
- scEpiLock: A Weakly Supervised Learning Framework forBiomolecules · 2022Article
- Approximate distance correlation for selecting highly interrelated genes across datasets.PLoS computational biology · 2021Article
- Improving Chromatin-Interaction Prediction Using Single-Cell Open-Chromatin Profiles and Making Insight Into theFrontiers in genetics · 2021Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid accumulation of single-cell chromatin accessibility data offers a unique opportunity to investigate common and specific regulatory mechanisms across different cell types. However, existing methods for cis-regulatory network reconstruction using single-cell chromatin accessibility data were only designed for cells belonging to one cell type, and resulting networks may be incomparable directly due to diverse cell numbers of different cell types. Here, we adopt a computational method to jointly reconstruct cis-regulatory interaction maps (JRIM) of multiple cell populations based on patterns of co-accessibility in single-cell data. We applied JRIM to explore common and specific regulatory interactions across multiple tissues from single-cell ATAC-seq dataset containing ~80 000 cells across 13 mouse tissues. Reconstructed common interactions among 13 tissues indeed relate to basic biological functions, and individual cis-regulatory networks show strong tissue specificity and functional relevance. More importantly, tissue-specific regulatory interactions are mediated by coordination of histone modifications and tissue-related TFs, and many of them may reveal novel regulatory mechanisms.
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