Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/44569
Title: Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM.
Authors: Chen, H
Albergante, L
Hsu, JY
Lareau, CA
Lo Bosco, G
Guan, J
Zhou, S
Gorban, AN
Bauer, DE
Aryee, MJ
Langenau, DM
Zinovyev, A
Buenrostro, JD
Yuan, G-C
Pinello, L
First Published: 23-Apr-2019
Publisher: Nature Research (part of Springer Nature)
Citation: Nature Communications, 2019, 10:1903
Abstract: 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.
DOI Link: 10.1038/s41467-019-09670-4
eISSN: 2041-1723
Links: https://www.nature.com/articles/s41467-019-09670-4
http://hdl.handle.net/2381/44569
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Description: The authors declare that the data supporting the findings of this study are available within the paper and its supplementary information files (Supplementary Data 1 and 2). STREAM is available as a user-friendly open-source software and can be used interactively as a web-application at http://stream.pinellolab.org (Supplementary Fig. 11, Supplementary Note 4), a bioconda package ‘stream’ for step-by-step analysis https://bioconda.github.io/recipes/stream/README.html (Supplementary Note 5), or as a standalone command-line tool: https://github.com/pinellolab/STREAM (Supplementary Note 6). All the analyses presented in this manuscript can be reproduced using the bioconda package and the provided Jupyter notebooks in Supplementary Data 1 and 2.
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