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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The Immunology of Multisystem Inflammatory Syndrome in Children with COVID-19

Cell, Journal Year: 2020, Volume and Issue: 183(4), P. 968 - 981.e7

Published: Sept. 6, 2020

Summary

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is typically very mild and often asymptomatic in children. A complication the rare multisystem inflammatory children (MIS-C) associated with COVID-19, presenting 4–6 weeks after as high fever, organ dysfunction, strongly elevated markers of inflammation. The pathogenesis unclear but has overlapping features Kawasaki disease suggestive vasculitis a likely autoimmune etiology. We apply systems-level analyses blood immune cells, cytokines, autoantibodies healthy children, enrolled prior to infected SARS-CoV-2, MIS-C. find that response MIS-C differs from cytokine storm severe shares several disease, also this condition respect T cell subsets, interleukin (IL)-17A, biomarkers arterial damage. Finally, autoantibody profiling suggests multiple could be involved

Language: Английский

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Methods and applications for single-cell and spatial multi-omics

Nature Reviews Genetics, Journal Year: 2023, Volume and Issue: 24(8), P. 494 - 515

Published: March 2, 2023

Language: Английский

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MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data

Genome biology, Journal Year: 2020, Volume and Issue: 21(1)

Published: May 11, 2020

Abstract Technological advances have enabled the profiling of multiple molecular layers at single-cell resolution, assaying cells from samples or conditions. Consequently, there is a growing need for computational strategies to analyze data complex experimental designs that include modalities and groups samples. We present Multi-Omics Factor Analysis v2 (MOFA+), statistical framework comprehensive scalable integration multi-modal data. MOFA+ reconstructs low-dimensional representation using computationally efficient variational inference supports flexible sparsity constraints, allowing jointly model variation across sample modalities.

Language: Английский

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Best practices for single-cell analysis across modalities

Nature Reviews Genetics, Journal Year: 2023, Volume and Issue: 24(8), P. 550 - 572

Published: March 31, 2023

Language: Английский

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The technological landscape and applications of single-cell multi-omics

Nature Reviews Molecular Cell Biology, Journal Year: 2023, Volume and Issue: 24(10), P. 695 - 713

Published: June 6, 2023

Language: Английский

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The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution

Cell, Journal Year: 2020, Volume and Issue: 181(2), P. 236 - 249

Published: April 1, 2020

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic ecosystem. Transformative single-cell genomics technologies spatial multiplex situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of National Cancer Institute (NCI) Moonshot Initiative, will establish a clinical, experimental, computational, organizational framework generate informative accessible three-dimensional atlases cancer for diverse set types. This effort complements both ongoing efforts map healthy organs previous large-scale approaches focused on bulk sequencing single point time. Generating single-cell, multiparametric, longitudinal integrating them with clinical outcomes should help identify novel predictive biomarkers features as well therapeutically relevant cell types, states, cellular across transitions. resulting have profound impact our understanding biology potential improve detection, prevention, discovery better precision-medicine treatments patients those risk cancer.

Language: Английский

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Integration strategies of multi-omics data for machine learning analysis

Computational and Structural Biotechnology Journal, Journal Year: 2021, Volume and Issue: 19, P. 3735 - 3746

Published: Jan. 1, 2021

Increased availability of high-throughput technologies has generated an ever-growing number omics data that seek to portray many different but complementary biological layers including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. New insight from these have been obtained by machine learning algorithms produced diagnostic classification biomarkers. Most biomarkers date however only include one omic measurement at a time thus do not take full advantage recent multi-omics experiments now capture the entire complexity systems. Multi-omics integration strategies are needed combine knowledge brought each layer. We summarized most methods/ frameworks into five strategies: early, mixed, intermediate, late hierarchical. In this mini-review, we focus on challenges existing paying special attention applications.

Language: Английский

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Integrated analysis of multimodal single-cell data

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2020, Volume and Issue: unknown

Published: Oct. 12, 2020

Abstract The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on data types. Here, we introduce ‘weighted-nearest neighbor’ unsupervised framework to learn the relative utility each type in cell, enabling integrative analysis modalities. We apply our procedure a CITE-seq dataset hundreds thousands human white blood cells alongside panel 228 antibodies construct reference atlas circulating immune system. demonstrate substantially improves ability resolve cell validate presence previously unreported lymphoid subpopulations. Moreover, how leverage this rapidly map datasets, interpret responses vaccination COVID-19. Our approach broadly applicable strategy analyze including paired measurements RNA chromatin state, look beyond transcriptome towards unified definition identity. Availability Installation instructions, documentation, tutorials, datasets are available at http://www.satijalab.org/seurat

Language: Английский

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Computational principles and challenges in single-cell data integration

Nature Biotechnology, Journal Year: 2021, Volume and Issue: 39(10), P. 1202 - 1215

Published: May 3, 2021

Language: Английский

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