Wishbone identifies bifurcating developmental trajectories from single-cell data
Open accessAbstract
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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Large variation induced by the cell cycle in some scRNA-seq experiments may conceal other important biological variation, especially differentiation.
“Thus, the large variation induced by the cell cycle in some scRNA-seq experiments may conceal other important sources of biological variation101, especially cellular differentiation processes137,141,151,152.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [151]
Single cell transcriptome analysis enables the reconstruction of gene expression dynamics along differentiation trajectories.
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- Authors
- Setty, M., Tadmor, M. D., Reich-Zeliger, S., Angel, O., Salame, T. M., Kathail, P., Choi, K., Bendall, S., Friedman, N., & Pe'er, D.
- Affiliations
- Columbia University (US)
- Weizmann Institute of Science (IL)
- University of British Columbia (CA)
- Stanford Medicine (US)
- Venue
- Nature Biotechnology
- Published
- 2016-05-02
- Volume
- 34
- Issue
- 6
- Pages
- 637-645
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC4900897
- OpenAlex
- W2344887288
- Cited by
- 558
- References
- 41
- Citations by year
- 2026: 15 · 2025: 37 · 2024: 26 · 2023: 27 · 2022: 55 · 2021: 50 · 2020: 71 · 2019: 81 · 2018: 101 · 2017: 78 · 2016: 17
- FWCI
- 48.35
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (R01CA164729)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (DP1HD084071)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Keywords
- wishbone, single-cell trajectory analysis, T cell development, thymus, myeloid differentiation, mass cytometry, single-cell RNA sequencing, cell fate determination, diffusion maps, monocle, SCUBA
- MeSH terms
- Algorithms, Animals, Cell Differentiation, Computer Simulation, Models, Biological, Morphogenesis, Software, T-Lymphocytes, Mice
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