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Nat Biotechnol. 2016 Jun;34(6):637-45. doi: 10.1038/nbt.3569. Epub 2016 May 2.

Wishbone identifies bifurcating developmental trajectories from single-cell data.

Author information

1
Department of Biological Sciences, Department of Systems Biology, Columbia University, New York, New York, USA.
2
Department of Immunology, Weizmann Institute of Science, Rehovot, Israel.
3
Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.
4
Biological Services Unit, Weizmann Institute of Science, Rehovot, Israel.
5
Department of Pathology, Stanford University, Stanford, California, USA.

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.

PMID:
27136076
PMCID:
PMC4900897
DOI:
10.1038/nbt.3569
[Indexed for MEDLINE]
Free PMC Article

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