Integrated analysis of multimodal single-cell data

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

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NicheNet: modeling intercellular communication by linking ligands to target genes

Nature Methods, Journal Year: 2019, Volume and Issue: 17(2), P. 159 - 162

Published: Dec. 9, 2019

Language: Английский

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Fibrosis: from mechanisms to medicines

Nature, Journal Year: 2020, Volume and Issue: 587(7835), P. 555 - 566

Published: Nov. 25, 2020

Language: Английский

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Exploring tissue architecture using spatial transcriptomics

Nature, Journal Year: 2021, Volume and Issue: 596(7871), P. 211 - 220

Published: Aug. 11, 2021

Language: Английский

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Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays

Cell, Journal Year: 2022, Volume and Issue: 185(10), P. 1777 - 1792.e21

Published: May 1, 2022

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view current methodologies precludes their systematic application analyze relatively large three-dimensional mid- late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays in situ RNA capture create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq generate mouse organogenesis spatiotemporal atlas (MOSTA), which maps with single-cell high sensitivity kinetics directionality transcriptional variation during organogenesis. used this information gain insight into molecular basis cell heterogeneity fate specification developing tissues dorsal midbrain. Our panoramic will facilitate in-depth investigation longstanding questions concerning normal abnormal development.

Language: Английский

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Deciphering cell–cell interactions and communication from gene expression

Nature Reviews Genetics, Journal Year: 2020, Volume and Issue: 22(2), P. 71 - 88

Published: Nov. 9, 2020

Language: Английский

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Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2

Nature Biotechnology, Journal Year: 2020, Volume and Issue: 39(3), P. 313 - 319

Published: Dec. 7, 2020

Language: Английский

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Multiplex digital spatial profiling of proteins and RNA in fixed tissue

Nature Biotechnology, Journal Year: 2020, Volume and Issue: 38(5), P. 586 - 599

Published: May 1, 2020

Language: Английский

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Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex

Nature Neuroscience, Journal Year: 2021, Volume and Issue: 24(3), P. 425 - 436

Published: Feb. 8, 2021

Language: Английский

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Robust decomposition of cell type mixtures in spatial transcriptomics

Nature Biotechnology, Journal Year: 2021, Volume and Issue: 40(4), P. 517 - 526

Published: Feb. 18, 2021

Language: Английский

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