University of Leicester
Browse
s41467-019-09670-4.pdf (3.4 MB)

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

Download (3.4 MB)
journal contribution
posted on 2019-06-24, 10:54 authored by H Chen, L Albergante, JY Hsu, CA Lareau, G Lo Bosco, J Guan, S Zhou, AN Gorban, DE Bauer, MJ Aryee, DM Langenau, A Zinovyev, JD Buenrostro, G-C Yuan, L Pinello
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.

Funding

This project has been made possible in part by grant number 2018- 182734 to L.P. from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation. L.P. is also partially supported by a National Human Genome Research Institute (NHGRI) Career Development Award (R00HG008399). G.Y.’s research was supported by a Claudia Adams Barr Award and a Bridge Award. J.D.B. acknowledges support from the Harvard Society of Fellows and Broad Institute Fellowship. J.D.B. also acknowledges the Allen Distinguished Investigator Program, through The Paul G. Allen Frontiers Group for funding. A.Z. and L.A. were supported by ITMO Cancer SysBio program (MOSAIC) and INCa PLBIO program (CALYS, INCA_11692). D.M.L was supported by R24OD016761 and R01CA211734. D.E.B. was supported by NHLBI (DP2OD022716, P01HL032262) and the Burroughs Wellcome Fund. A.N.G was supported by Ministry of Education and Science of Russia (Project No. 14.Y26.31.0022). J.G. was supported by National Natural Science Foundation of China (NSFC) (grant No. 61772367). S.Z. was supported by the National Key Research and Development Program of China (grant No. 2016YFC0901704). We thank Stuart H Orkin, Luca Biasco, Danilo Pellin, Ruben Dries, Sara Garcia, Micheal Vinyard, and the members of the Pinello Lab for helpful discussions. We also thank P. G. Camara and R. Rabadan for sharing both simulation code and data. We also thank V. Svensson for helpful discussions regarding GPFates. We also thank F. Theis and L. Haghverdi for the suggestion on adapting DPT on sc-qPCR data. We also thank Xiaojie Qiu for sharing the data and the scripts to reproduce Monocle2 analyses (Fig. S16, PMID: 28825705). We also thank Johannes Köster and the bioconda team for helping us in the development of the bioconda stream package. Schematic panels from Fig. 6a were modified from Buenrostro et al., 2018 Cell.

History

Citation

Nature Communications, 2019, 10:1903

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Mathematics

Version

  • VoR (Version of Record)

Published in

Nature Communications

Publisher

Nature Research (part of Springer Nature)

eissn

2041-1723

Acceptance date

2019-03-22

Copyright date

2019

Available date

2019-06-24

Publisher version

https://www.nature.com/articles/s41467-019-09670-4

Notes

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.

Language

en

Usage metrics

    University of Leicester Publications

    Categories

    Keywords

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC