Introduction

Recent technical developments have enabled the transcriptomes of hundreds of cells to be assayed in an unbiased manner, opening up the possibility that new subpopulations of cells can be found. However, the effects of potential confounding factors, such as the cell cycle, on the heterogeneity of gene expression and therefore on the ability to robustly identify subpopulations remain unclear. We present and validate a computational approach that uses latent variable models to account for such hidden factors. We show that our single-cell latent variable model (scLVM) allows the identification of otherwise undetectable subpopulations of cells that correspond to different stages during the differentiation of naive T cells into T helper 2 cells. Our approach can be used not only to identify cellular subpopulations but also to tease apart different sources of gene expression heterogeneity in single-cell transcriptomes.

Publications

  1. Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells.
    Cite this
    Buettner F, Natarajan KN, Casale FP, Proserpio V, Scialdone A, Theis FJ, Teichmann SA, Marioni JC, Stegle O, 2015-02-01 - Nature biotechnology

Credits

  1. Florian Buettner
    Developer

    1] Helmholtz Zentrum München-German Research Center for Environmental Health, Institute of Computational Biology, Germany

  2. Kedar N Natarajan
    Developer

    1] European Molecular Biology Laboratory, European Bioinformatics Institute

  3. F Paolo Casale
    Developer

    European Molecular Biology Laboratory, European Bioinformatics Institute

  4. Valentina Proserpio
    Developer

    1] European Molecular Biology Laboratory, European Bioinformatics Institute

  5. Antonio Scialdone
    Developer

    1] European Molecular Biology Laboratory, European Bioinformatics Institute

  6. Fabian J Theis
    Developer

    1] Helmholtz Zentrum München-German Research Center for Environmental Health, Institute of Computational Biology, Germany

  7. Sarah A Teichmann
    Developer

    1] European Molecular Biology Laboratory, European Bioinformatics Institute

  8. John C Marioni
    Developer

    1] European Molecular Biology Laboratory, European Bioinformatics Institute

  9. Oliver Stegle
    Investigator

    European Molecular Biology Laboratory, European Bioinformatics Institute

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Summary
AccessionBT007019
Tool TypeApplication
Category
PlatformsLinux/Unix
Technologies
User InterfaceTerminal Command Line
Download Count0
Submitted ByOliver Stegle