Unsupervised Trajectory Inference Using Graph Mining

  • Leen De BaetsEmail author
  • Sofie Van Gassen
  • Tom Dhaene
  • Yvan Saeys
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9874)


Cell differentiation is a complex dynamic process and although the main cellular states are well studied, the intermediate stages are often still unknown. Single cell data (such as obtained by flow cytometry) is typically analysed by clustering the cells into distinct cell types, which does not model these gradual changes. Alternative approaches that explicitly model such gradual changes using seriation methods seems promising, but are only able to model a single differentiation pathway. In this paper, we introduce a new, graph-based approach that is able to model multiple branching differentiation pathways as continuous trajectories. Results on synthetic and real data show that this is a promising approach which is moreover robust to parameter changes.


False Positive Rate High False Positive Rate Flow Cytometry Data Single Trajectory Start Cell 
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We would like to thank Lianne van de Laar and Bart Lambrecht for providing a biologically relevant dataset to test our algorithm. Sofie Van Gassen is funded by the Flanders Agency for Innovation by Science and Technology (IWT).


  1. 1.
    Qiu, P., Simonds, E.F., Bendall, S.C., Jr. Gibbs, K.D., Bruggner, R.V., Linderman, M.D., Sachs, K., Nolan, G.P., Plevritis, S.K.: Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nat. Biotechnol. 29(10), 886–891 (2011)CrossRefGoogle Scholar
  2. 2.
    Amir, E.D., Davis, K.L., Tadmor, M.D., Simonds, E.F., Levine, J.H., Bendall, S.C., Shenfeld, D.K., Krishnaswamy, S., Nolan, G.P., Pe’er, D.: viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat. Biotechnol. 36(6), 545–552 (2013)CrossRefGoogle Scholar
  3. 3.
    Van Gassen, S., Callebaut, B., Van Helden, M.J., Lambrecht, B.N., Demeester, P., Dhaene, T., Saeys, Y.: FlowSOM: Using selforganizing maps for visualization and interpretation of cytometry data. Cytometry Part A (2015)Google Scholar
  4. 4.
    Magwene, P.M., Lizardi, P., Kim, J.: Reconstructing the temporal ordering of biological samples using microarray data. Bioinformatics 19(7), 842–850 (2003)CrossRefGoogle Scholar
  5. 5.
    Liiv, I.: Seriation and matrix reordering methods: an historical overview. Stat. Anal. Data Min. ASA Data Sci. J. 3(2), 70–91 (2010)MathSciNetGoogle Scholar
  6. 6.
    Braak, T., Cajo, J.F., Van Tongeren, O.F.R.: Data Analysis in Community and Landscape Ecology. Cambridge University Press, Cambridge (1995)Google Scholar
  7. 7.
    Trapnell, C., et al.: The dynamics, regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32(4), 381–386 (2014)CrossRefGoogle Scholar
  8. 8.
    Bendall, S.C., et al.: Single-cell trajectory detection uncovers progression andregulatory coordination in human B cell development. Cell 157(3), 714–725 (2014)CrossRefGoogle Scholar
  9. 9.
    Trapnell, C., et al.: The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. (2014)Google Scholar
  10. 10.
    Seita, J., Weissman, I.L.: Hematopoietic stem cell: selfrenewal versus differentiation. Wiley Interdisc. Rev. Syst. Biol. Med. 2(6), 640–653 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Leen De Baets
    • 1
    Email author
  • Sofie Van Gassen
    • 1
    • 2
  • Tom Dhaene
    • 1
  • Yvan Saeys
    • 2
    • 3
  1. 1.Internet Based Communication Networks and Services (IBCN)Ghent University - iMindsGhentBelgium
  2. 2.Data Mining and Modelling for Biomedicine (DaMBi)VIB Inflammation Research CenterGhentBelgium
  3. 3.Department of Internal MedicineGhent UniversityGhentBelgium

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