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A generalization of t-SNE and UMAP to single-cell multimodal omics

Emerging single-cell technologies profile multiple types of molecules within individual cells. A fundamental step in the analysis of the produced high-dimensional data is their visualization using dimensionality reduction techniques such as t-SNE and UMAP. We introduce j-SNE and j-UMAP as their natu...

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Detalles Bibliográficos
Autores principales: Do, Van Hoan, Canzar, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8091681/
https://www.ncbi.nlm.nih.gov/pubmed/33941244
http://dx.doi.org/10.1186/s13059-021-02356-5
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author Do, Van Hoan
Canzar, Stefan
author_facet Do, Van Hoan
Canzar, Stefan
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description Emerging single-cell technologies profile multiple types of molecules within individual cells. A fundamental step in the analysis of the produced high-dimensional data is their visualization using dimensionality reduction techniques such as t-SNE and UMAP. We introduce j-SNE and j-UMAP as their natural generalizations to the joint visualization of multimodal omics data. Our approach automatically learns the relative contribution of each modality to a concise representation of cellular identity that promotes discriminative features but suppresses noise. On eight datasets, j-SNE and j-UMAP produce unified embeddings that better agree with known cell types and that harmonize RNA and protein velocity landscapes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-021-02356-5).
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spelling pubmed-80916812021-05-04 A generalization of t-SNE and UMAP to single-cell multimodal omics Do, Van Hoan Canzar, Stefan Genome Biol Short Report Emerging single-cell technologies profile multiple types of molecules within individual cells. A fundamental step in the analysis of the produced high-dimensional data is their visualization using dimensionality reduction techniques such as t-SNE and UMAP. We introduce j-SNE and j-UMAP as their natural generalizations to the joint visualization of multimodal omics data. Our approach automatically learns the relative contribution of each modality to a concise representation of cellular identity that promotes discriminative features but suppresses noise. On eight datasets, j-SNE and j-UMAP produce unified embeddings that better agree with known cell types and that harmonize RNA and protein velocity landscapes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-021-02356-5). BioMed Central 2021-05-03 /pmc/articles/PMC8091681/ /pubmed/33941244 http://dx.doi.org/10.1186/s13059-021-02356-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Short Report
Do, Van Hoan
Canzar, Stefan
A generalization of t-SNE and UMAP to single-cell multimodal omics
title A generalization of t-SNE and UMAP to single-cell multimodal omics
title_full A generalization of t-SNE and UMAP to single-cell multimodal omics
title_fullStr A generalization of t-SNE and UMAP to single-cell multimodal omics
title_full_unstemmed A generalization of t-SNE and UMAP to single-cell multimodal omics
title_short A generalization of t-SNE and UMAP to single-cell multimodal omics
title_sort generalization of t-sne and umap to single-cell multimodal omics
topic Short Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8091681/
https://www.ncbi.nlm.nih.gov/pubmed/33941244
http://dx.doi.org/10.1186/s13059-021-02356-5
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