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Wishbone specifications


Unique identifier OMICS_17996
Name Wishbone
Software type Package/Module
Interface Command line interface
Input data Some multidimensional single-cell data, mass cytometry or RNA-seq data.
Operating system Unix/Linux, Mac OS, Windows
Programming languages MATLAB, Python
License GNU General Public License version 2.0
Computer skills Advanced
Stability Stable
Maintained Yes




No version available


  • person_outline Dana Pe’er

Additional information

https://github.com/ManuSetty/wishbone; A registration is needed to access to tools.

Publication for Wishbone

Wishbone citations


Single Cell Computational Strategies for Lineage Reconstruction in Tissue Systems

PMCID: 5924749
PMID: 29713661
DOI: 10.1016/j.jcmgh.2018.01.023

[…] re major structures and progressive trends in the data. Multiple such embedding approaches have been adopted for single-cell data analysis, including Diffusion maps used in various algorithms such as Wishbone,, local linear embedding used in Selective Locally Linear Inference of Cellular Expression Relationships, and multidimensional scaling and mapper in scTDA. Adoption of nonlinear embedding al […]


HopLand: single cell pseudotime recovery using continuous Hopfield network based modeling of Waddington’s epigenetic landscape

PMCID: 5870541
PMID: 28881967
DOI: 10.1093/bioinformatics/btx232

[…] In this section, we evaluate the performance of HopLand by comparing it with 6 state-of-the-art methods, i.e. Monocle, Topslam, Wanderlust, Wishbone, SCUBA and Diffusion map, on 11 testing datasets including a qPCR dataset GUO2010 (), 5 synthetic datasets and 5 scRNA-seq datasets, i.e. DENG2014 using Smart-seq2 (), YAN2013 () using scRNA- […]


Computational approaches for interpreting scRNA‐seq data

PMCID: 5575496
PMID: 28524227
DOI: 10.1002/1873-3468.12684

[…] progenitor cells can develop into multiple distinct cell types. This means the cells will not follow a single trajectory in the high‐dimensional space. A couple of heuristics have been published: in Wishbone , cells are clustered by the pairwise detour distance relative to a reference cell, using geodesic distance. This method is reported to be correctly recovering the known stages and bifurcatio […]


Model based branching point detection in single cell data by K branches clustering

PMCID: 5860029
PMID: 28582478
DOI: 10.1093/bioinformatics/btx325

[…] ccessfully applied to challenging datasets that include sparsity and complex geometries.The main idea of the proposed methodology is different from that of commonly used methods such as DPT, Monocle, Wishbone, SLICER or TSCAN. To be precise, these methods aim to assign each cell to a distinct branch in the differentiation process and also calculate pseudotime: an ordering of the cells, relevant to […]


CymeR: cytometry analysis using KNIME, docker and R

PMCID: 5870801
PMID: 27998935
DOI: 10.1093/bioinformatics/btw707

[…] ith large multi-center flow cytometry experiments. In the first case, we currently provide access to Cytofkit (), Destiny (), FlowSOM (), PhenoGraph (), SCAFoLLD (), SPADE (), t-SNE (), VorteX () and Wishbone (), and in the latter case we have provided a simple GUI for OpenCyto (). For almost all CymeR functions, the main output is a new FCS file with new columns corresponding to new dimensions, c […]


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Wishbone institution(s)
Department of Biological Sciences, Department of Systems Biology, Columbia University, New York NY, USA; Department of Immunology, Weizmann Institute of Science, Rehovot, Israel; Department of Mathematics, University of British Columbia, Vancouver, BC, Canada; Biological Services Unit, Weizmann Institute of Science, Rehovot, Israel; Department of Pathology, Stanford University, Stanford, CA, USA
Wishbone funding source(s)
Supported by NSF MCB-1149728, NIH DP1- HD084071, NIH R01CA164729; by a Packard Fellowship for Science and Engineering; 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.

Wishbone review

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Anonymous user #45955

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very good!