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Domínguez Conde, C; Xu, C; Jarvis, L B; Rainbow, D B; Wells, S B; Gomes, T; Howlett, S K; Suchanek, O; Polanski, K; King, H W; Mamanova, L; Huang, N; Szabo, P A; Richardson, L; Bolt, L; Fasouli, E S; Mahbubani, K T; Prete, M; Tuck, L; Richoz, N; Tuong, Z K; Campos, L; Mousa, H S; Needham, E J; Pritchard, S; Li, T; Elmentaite, R; Park, J; Rahmani, E; Chen, D; Menon, D K; Bayraktar, O A; James, L K; Meyer, K B; Yosef, N; Clatworthy, M R; Sims, P A; Farber, D L; Saeb-Parsy, K; Jones, J L; Teichmann, S A
Science (American Association for the Advancement of Science), 05/2022, Letnik: 376, Številka: 6594Journal Article
Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. We surveyed the immune compartment of 16 tissues from 12 adult donors by single-cell RNA sequencing and VDJ sequencing generating a dataset of ~360,000 cells. To systematically resolve immune cell heterogeneity across tissues, we developed CellTypist, a machine learning tool for rapid and precise cell type annotation. Using this approach, combined with detailed curation, we determined the tissue distribution of finely phenotyped immune cell types, revealing hitherto unappreciated tissue-specific features and clonal architecture of T and B cells. Our multitissue approach lays the foundation for identifying highly resolved immune cell types by leveraging a common reference dataset, tissue-integrated expression analysis, and antigen receptor sequencing.
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Dostop do baze podatkov JCR je dovoljen samo uporabnikom iz Slovenije. Vaš trenutni IP-naslov ni na seznamu dovoljenih za dostop, zato je potrebna avtentikacija z ustreznim računom AAI.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
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Vir: Osebne bibliografije
in: SICRIS
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