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ScImmOmics is a manually curated single-cell multi-omics immune database constructed based on high-quality immune cells with known immune cell labels and is a comprehensive and valuable platform for unraveling the heterogeneity and diversity of immune cells and elucidating the specific regulatory mechanisms at the single-cell level.
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Single-cell sequencing technology has enabled the discovery and characterization of subpopulations of immune cells with unique functions, which is critical for revealing immune responses under healthy or disease conditions. Efforts have been made to collect and curate single-cell RNA sequencing (scRNA-seq) data, yet an immune-specific single-cell multi-omics atlas with harmonized metadata is still lacking. Here, we present scImmOmics (https://bio.liclab.net/scImmOmics/home), a manually curated single-cell multi-omics immune database constructed based on high-quality immune cells with known immune cell labels. Currently, scImmOmics documents >2.9 million cell-type labeled immune cells derived from seven single-cell sequencing technologies, involving 131 immune cell types, 47 tissues and 4 species. To ensure data consistency, we standardized the nomenclature of immune cell types and presented them in a hierarchical tree structure to clearly describe the lineage relationships within the immune system. scImmOmics also provides comprehensive immune regulatory information, including T-cell/B-cell receptor sequencing clonotype information, cell-specific regulatory information (e.g. gene/chromatin accessibility/protein/transcription factor states within known cell types, cell-to-cell communication and co-expression networks) and immune cell responses to cytokines. Collectively, scImmOmics is a comprehensive and valuable platform for unraveling the heterogeneity and diversity of immune cells and elucidating the specific regulatory mechanisms at the single-cell level.
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@article{Li2024scImmOmics,
title = {scImmOmics: a manually curated resource of single-cell multi-omics immune data},
author = {Yanyu Li and Li‐Wei Zhou and Fengcui Qian and Qiao-Li Fang and Zhengmin Yu and Ting Cui and Fu-Juan Dong and Tingting Yu and Lidong Li and Qiuyu Wang and Yanbing Zhu and Huifang Tang and Baoyang Hu and Chunquan Li},
journal = {Nucleic Acids Research},
year = {2024},
doi = {10.1093/nar/gkae985},
url = {https://doi.org/10.1093/nar/gkae985}
}
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