ArticleeLife2021
Simultaneous trimodal single-cell measurement of transcripts, epitopes, and chromatin accessibility using TEA-seq.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 174 papers.
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Who cites it
174 citing papers in PubMed.
- Unifying multimodal single-cell data with a mixture-of-experts β-variational autoencoder framework.Genome research · 2026Article
- The dual-enhanced graph learning framework DePass allows paired data integration in single-cell and spatial multiomics.Nature cell biology · 2026Article
- Review
- Continual integration of single-cell multimodal data with MIRACLE.Nature computational science · 2026Article
- Scalable joint non-negative matrix factorization for paired single cell gene expression and chromatin accessibility data.NAR genomics and bioinformatics · 2026Article
- Topology-guided dual-masked contrastive learning for weakly supervised cell-type annotation in single-cell multi-omics.Briefings in bioinformatics · 2026Article
- mmVelo: a deep generative model for estimating cell state-dependent dynamics across multiple modalities.Bioinformatics (Oxford, England) · 2026Article
- Semi-supervised Omics Factor Analysis (SOFA) disentangles known and latent sources of variation in multi-omic data.Nature communications · 2026Article
- Article
- Unifying multimodal single-cell data with a mixture-of-expertsbioRxiv : the preprint server for biology · 2026Article
- UDEC-MO: an uncertainty-guided deep embedded clustering framework for bulk and single-cell multi-omics data.Briefings in bioinformatics · 2026Article
- Single-nucleus chromatin accessibility and gene expression co-profiling by ISSAAC-seq.Nature protocols · 2026Review
- Interpretable deep generative ensemble learning for single-cell omics with Hydra.Molecular systems biology · 2026Article
- Single-Cell CRISPR: An Efficient Strategy for Decoding Plant Cis-Regulatory Complexity.Plant biotechnology journal · 2026Review
- Enhancers integrate microenvironmental signals in muscle stem cells during regeneration in health, disease, and aging.Skeletal muscle · 2026Review
- Decoding Immune Regulation: From Genetic Variation to Mechanism Through Single-Cell Genomics.Immune network · 2026Review
- Interpretable modality-aware mapping of gene regulation in single-cell multiomics with scMAGCA.Nature communications · 2026Article
- Robust integration of single-cell datasets with imbalanced modality composition.Nature communications · 2026Article
- CAPTAIN: a multimodal foundation model pretrained on co-assayed single-cell RNA and protein.Nature communications · 2026Article
- Single-cell data integration across weakly linked modalities.PLoS computational biology · 2026Article
114 more citing papers are in PubMed but not listed here.
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell measurements of cellular characteristics have been instrumental in understanding the heterogeneous pathways that drive differentiation, cellular responses to signals, and human disease. Recent advances have allowed paired capture of protein abundance and transcriptomic state, but a lack of epigenetic information in these assays has left a missing link to gene regulation. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases signal-to-noise and allows paired measurement of cell surface markers and chromatin accessibility: integrated cellular indexing of chromatin landscape and epitopes, called ICICLE-seq. We extended this approach using a droplet-based multiomics platform to develop a trimodal assay that simultaneously measures transcriptomics (scRNA-seq), epitopes, and chromatin accessibility (scATAC-seq) from thousands of single cells, which we term TEA-seq. Together, these multimodal single-cell assays provide a novel toolkit to identify type-specific gene regulation and expression grounded in phenotypically defined cell types.
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