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Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM

Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell trans...

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Autores principales: Chen, Huidong, Albergante, Luca, Hsu, Jonathan Y., Lareau, Caleb A., Lo Bosco, Giosuè, Guan, Jihong, Zhou, Shuigeng, Gorban, Alexander N., Bauer, Daniel E., Aryee, Martin J., Langenau, David M., Zinovyev, Andrei, Buenrostro, Jason D., Yuan, Guo-Cheng, Pinello, Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478907/
https://www.ncbi.nlm.nih.gov/pubmed/31015418
http://dx.doi.org/10.1038/s41467-019-09670-4
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author Chen, Huidong
Albergante, Luca
Hsu, Jonathan Y.
Lareau, Caleb A.
Lo Bosco, Giosuè
Guan, Jihong
Zhou, Shuigeng
Gorban, Alexander N.
Bauer, Daniel E.
Aryee, Martin J.
Langenau, David M.
Zinovyev, Andrei
Buenrostro, Jason D.
Yuan, Guo-Cheng
Pinello, Luca
author_facet Chen, Huidong
Albergante, Luca
Hsu, Jonathan Y.
Lareau, Caleb A.
Lo Bosco, Giosuè
Guan, Jihong
Zhou, Shuigeng
Gorban, Alexander N.
Bauer, Daniel E.
Aryee, Martin J.
Langenau, David M.
Zinovyev, Andrei
Buenrostro, Jason D.
Yuan, Guo-Cheng
Pinello, Luca
author_sort Chen, Huidong
collection PubMed
description Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data. We have tested STREAM on several synthetic and real datasets generated with different single-cell technologies. We further demonstrate its utility for understanding myoblast differentiation and disentangling known heterogeneity in hematopoiesis for different organisms. STREAM is an open-source software package.
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spelling pubmed-64789072019-04-25 Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM Chen, Huidong Albergante, Luca Hsu, Jonathan Y. Lareau, Caleb A. Lo Bosco, Giosuè Guan, Jihong Zhou, Shuigeng Gorban, Alexander N. Bauer, Daniel E. Aryee, Martin J. Langenau, David M. Zinovyev, Andrei Buenrostro, Jason D. Yuan, Guo-Cheng Pinello, Luca Nat Commun Article Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data. We have tested STREAM on several synthetic and real datasets generated with different single-cell technologies. We further demonstrate its utility for understanding myoblast differentiation and disentangling known heterogeneity in hematopoiesis for different organisms. STREAM is an open-source software package. Nature Publishing Group UK 2019-04-23 /pmc/articles/PMC6478907/ /pubmed/31015418 http://dx.doi.org/10.1038/s41467-019-09670-4 Text en © The Author(s) 2019 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Chen, Huidong
Albergante, Luca
Hsu, Jonathan Y.
Lareau, Caleb A.
Lo Bosco, Giosuè
Guan, Jihong
Zhou, Shuigeng
Gorban, Alexander N.
Bauer, Daniel E.
Aryee, Martin J.
Langenau, David M.
Zinovyev, Andrei
Buenrostro, Jason D.
Yuan, Guo-Cheng
Pinello, Luca
Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM
title Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM
title_full Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM
title_fullStr Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM
title_full_unstemmed Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM
title_short Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM
title_sort single-cell trajectories reconstruction, exploration and mapping of omics data with stream
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478907/
https://www.ncbi.nlm.nih.gov/pubmed/31015418
http://dx.doi.org/10.1038/s41467-019-09670-4
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