
Cell, Journal Year: 2018, Volume and Issue: 173(6), P. 1439 - 1453.e19
Published: May 1, 2018
Language: Английский
Cell, Journal Year: 2018, Volume and Issue: 173(6), P. 1439 - 1453.e19
Published: May 1, 2018
Language: Английский
Cell, Journal Year: 2021, Volume and Issue: 184(13), P. 3573 - 3587.e29
Published: May 31, 2021
The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce "weighted-nearest neighbor" analysis, unsupervised framework to learn the relative utility each data type in cell, enabling integrative analysis modalities. We apply our procedure a CITE-seq dataset 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending 228 antibodies construct reference atlas circulating immune system. Multimodal substantially improves ability resolve cell states, allowing us identify validate previously unreported lymphoid subpopulations. Moreover, demonstrate how leverage this rapidly map new datasets interpret responses vaccination coronavirus disease 2019 (COVID-19). Our approach broadly applicable strategy analyze look beyond transcriptome toward unified definition identity.
Language: Английский
Citations
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Language: Английский
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Language: Английский
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Language: Английский
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Language: Английский
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Language: Английский
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Language: Английский
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Language: Английский
Citations
897