ArticleNature biotechnology2023
SEACells infers transcriptional and epigenomic cellular states from single-cell genomics data.
Article in Nature biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 139 papers.
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Who cites it
139 citing papers in PubMed, 219 citations in OpenAlex.
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- Flexible use of conserved motifs constrains genome access in cell type evolution.Nature ecology & evolution · 2026Article
- Atlas of cell types and regulatory elements underlying human facial diversity.Nature genetics · 2026Article
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- Empirical Estimation of Ambient Contamination in Combinatorial Single-Cell Methods Using Multi-Reference Mapping.bioRxiv : the preprint server for biology · 2026Article
- Single-cell multi-omics dissects transcript isoform and immune repertoire dynamics in human immunosenescence.Science China. Life sciences · 2026Article
- Epigenetic modulation of stromal cell states underpins pathological tissue niches in Crohn's disease.Nature immunology · 2026Article
- CellRank: consistent and data view agnostic fate mapping for single-cell genomics.Nature protocols · 2026Review
- Mapping enhancer-gene regulatory interactions from single-cell data.Nature genetics · 2026Article
- A multimodal interrogation of Broca's area in the pediatric and adult human brain.bioRxiv : the preprint server for biology · 2026Article
- Single-cell multimodal profiling of pan-cancer cell lines uncovers gene regulatory principles underlying intrinsic cell states and environmental features.Nature communications · 2026Article
- A unified network systems approach uncovers a core program underlying T follicular helper cell differentiation.Nature communications · 2026Article
- Distinct cell type-specific mechanisms underlie cognitive dysfunction during persistent integrated stress response activation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Context-aware sequence-to-function model of human gene regulation.Nature communications · 2026Article
- SupeRJump: Determining normal and leukemic differentiation fate through semi-supervised jump diffusion modeling.bioRxiv : the preprint server for biology · 2026Article
- Competing gene regulatory networks drive naive and memory B cell differentiation.Molecular systems biology · 2026Article
- Multi-omics profiling reveals systemic rejuvenation of the aged kidney through senolytic therapy.NPJ Regenerative medicine · 2026Article
- Hierarchical classification of immune cell transcriptomes at population-scale.bioRxiv : the preprint server for biology · 2026Article
79 more citing papers are in PubMed but not listed here.
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Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
Abstract
Metacells are cell groupings derived from single-cell sequencing data that represent highly granular, distinct cell states. Here we present single-cell aggregation of cell states (SEACells), an algorithm for identifying metacells that overcome the sparsity of single-cell data while retaining heterogeneity obscured by traditional cell clustering. SEACells outperforms existing algorithms in identifying comprehensive, compact and well-separated metacells in both RNA and assay for transposase-accessible chromatin (ATAC) modalities across datasets with discrete cell types and continuous trajectories. We demonstrate the use of SEACells to improve gene-peak associations, compute ATAC gene scores and infer the activities of critical regulators during differentiation. Metacell-level analysis scales to large datasets and is particularly well suited for patient cohorts, where per-patient aggregation provides more robust units for data integration. We use our metacells to reveal expression dynamics and gradual reconfiguration of the chromatin landscape during hematopoietic differentiation and to uniquely identify CD4 T cell differentiation and activation states associated with disease onset and severity in a Coronavirus Disease 2019 (COVID-19) patient cohort.
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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.