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Wishbone identifies bifurcating developmental trajectories from single-cell data

Nature Biotechnology volume 34, pages 637–645 (2016)Cite this article

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Abstract

Recent single-cell analysis technologies offer an unprecedented opportunity to elucidate developmental pathways. Here we present Wishbone, an algorithm for positioning single cells along bifurcating developmental trajectories with high resolution. Wishbone uses multi-dimensional single-cell data, such as mass cytometry or RNA-Seq data, as input and orders cells according to their developmental progression, and it pinpoints bifurcation points by labeling each cell as pre-bifurcation or as one of two post-bifurcation cell fates. Using 30-channel mass cytometry data, we show that Wishbone accurately recovers the known stages of T-cell development in the mouse thymus, including the bifurcation point. We also apply the algorithm to mouse myeloid differentiation and demonstrate its generalization to additional lineages. A comparison of Wishbone to diffusion maps, SCUBA and Monocle shows that it outperforms these methods both in the accuracy of ordering cells and in the correct identification of branch points.

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Figure 1: Alignment of cells along bifurcating trajectories.
Figure 2: Wishbone robustly recovers hallmarks of T-cell differentiation.
Figure 3: Heterogeneity in gated populations is explained in part by variance along a trajectory.
Figure 4: Transcription factors show distinct dynamics in SP populations.
Figure 5: Generalization of Wishbone to branches in human and mouse myeloid development spanning mass cytometry and single-cell RNA-Seq.
Figure 6: Wishbone outperformed competing methods in both ordering of cells and branch associations.

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Acknowledgements

We would like to thank A. Bloemendal, Z. Good, N. Hacohen, S. Krishnaswamy, J. Levine and A.J. Carr for their helpful comments. M.D.T. is supported by an NSF graduate fellowship. This work was supported by NSF MCB-1149728, NIH DP1- HD084071, NIH R01CA164729 to D.P. D.P. holds a Packard Fellowship for Science and Engineering. This work was also supported by David and Fela Shapell Family Foundation INCPM Fund, the WIS staff scientists grant from the Nissim Center, for the Development of Scientific Resources, and ISF 1184/15 to N.F.

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Author notes

  1. Manu Setty and Michelle D Tadmor: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Biological Sciences, Department of Systems Biology, Columbia University, New York, New York, USA

    Manu Setty, Michelle D Tadmor, Pooja Kathail, Kristy Choi & Dana Pe'er

  2. Department of Immunology, Weizmann Institute of Science, Rehovot, Israel

    Shlomit Reich-Zeliger & Nir Friedman

  3. Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada

    Omer Angel

  4. Biological Services Unit, Weizmann Institute of Science, Rehovot, Israel

    Tomer Meir Salame

  5. Department of Pathology, Stanford University, Stanford, California, USA

    Sean Bendall

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  1. Manu Setty
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Contributions

S.B. and D.P. conceived the study. M.S., M.D.T., O.A., and D.P. designed and developed Wishbone. M.S. and D.P. performed statistical analysis and comparison of Wishbone. S.R.-Z., T.M.S., and N.F. performed all bench experiments and data acquisition. M.S., S.R.-Z., N.F., and D.P. performed the biological analysis and interpretation. M.D.T., M.S., P.K., and K.C. programmed the software tools. M.S., S.R.-Z., N.F., and D.P. wrote the manuscript.

Corresponding author

Correspondence to Dana Pe'er.

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Setty, M., Tadmor, M., Reich-Zeliger, S. et al. Wishbone identifies bifurcating developmental trajectories from single-cell data. Nat Biotechnol 34, 637–645 (2016). https://doi.org/10.1038/nbt.3569

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