ArticleGenomics, proteomics & bioinformatics2023
deCS: A Tool for Systematic Cell Type Annotations of Single-cell RNA Sequencing Data among Human Tissues.
Article in Genomics, proteomics & bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 23 citations in OpenAlex.
- celltypeEnrich: a consensus-based scRNA-seq cluster annotation tool.bioRxiv : the preprint server for biology · 2026Article
- scDIG: An R Shiny Application for Interactive Density-Based Gating of Single-Cell Proteomic and Transcriptomic Data.bioRxiv : the preprint server for biology · 2026Article
- SPICEY: an R package for quantifying tissue specificity from single cell multi-omics data.BMC bioinformatics · 2026Article
- SAA1/FPR2 signaling between keratinocytes and neutrophils sustains chronic inflammation in Sweet syndrome.The Journal of clinical investigation · 2025Article
- Article
- Mapping Cell Identity from scRNA-seq: A primer on computational methods.Computational and structural biotechnology journal · 2025Review
- BrainCellR: A precise cell type nomenclature pipeline for comparative analysis across brain single-cell datasets.Computational and structural biotechnology journal · 2024Article
- CXCL9, CXCL10, and CCL19 synergistically recruit T lymphocytes to skin in lichen planus.JCI insight · 2024Article
- Recruitment of CXCR4+ type 1 innate lymphoid cells distinguishes sarcoidosis from other skin granulomatous diseases.The Journal of clinical investigation · 2024Article
- Single-cell multiomics decodes regulatory programs for mouse secondary palate development.Nature communications · 2024Article
- CellSTAR: a comprehensive resource for single-cell transcriptomic annotation.Nucleic acids research · 2024Article
- Automatic Cell Type Annotation Using Marker Genes for Single-Cell RNA Sequencing Data.Biomolecules · 2022Article
- scGWAS: landscape of trait-cell type associations by integrating single-cell transcriptomics-wide and genome-wide association studies.Genome biology · 2022Article
- Identifying candidate genes and drug targets for Alzheimer's disease by an integrative network approach using genetic and brain region-specific proteomic data.Human molecular genetics · 2022Article
- Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments.Genes · 2022Article
- WebCSEA: web-based cell-type-specific enrichment analysis of genes.Nucleic acids research · 2022Article
- Comprehensive characterization of tumor immune landscape following oncolytic virotherapy by single-cell RNA sequencing.Cancer immunology, immunotherapy : CII · 2022Article
- Prioritization of risk genes in multiple sclerosis by a refined Bayesian framework followed by tissue-specificity and cell type feature assessment.BMC genomics · 2022Article
- Decoding regulatory associations of G-quadruplex with epigenetic and transcriptomic functional components.Frontiers in genetics · 2022Article
- Single-cell RNA sequencing reveals a strong connection betweenMolecular therapy oncolytics · 2021Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
Single-cell RNA sequencing (scRNA-seq) is revolutionizing the study of complex and dynamic cellular mechanisms. However, cell type annotation remains a main challenge as it largely relies on a priori knowledge and manual curation, which is cumbersome and subjective. The increasing number of scRNA-seq datasets, as well as numerous published genetic studies, has motivated us to build a comprehensive human cell type reference atlas.Here, we present decoding Cell type Specificity (deCS), an automatic cell type annotation method augmented by a comprehensive collection of human cell type expression profiles and marker genes. We used deCS to annotate scRNA-seq data from various tissue types and systematically evaluated the annotation accuracy under different conditions, including reference panels, sequencing depth, and feature selection strategies. Our results demonstrate that expanding the references is critical for improving annotation accuracy. Compared to many existing state-of-the-art annotation tools, deCS significantly reduced computation time and increased accuracy. deCS can be integrated into the standard scRNA-seq analytical pipeline to enhance cell type annotation. Finally, we demonstrated the broad utility of deCS to identify trait-cell type associations in 51 human complex traits, providing deep insights into the cellular mechanisms underlying disease pathogenesis. All documents for deCS, including source code, user manual, demo data, and tutorials, are freely available at https://github.com/bsml320/deCS.
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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 Socratic graph.