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Sincell: an R/Bioconductor package for statistical assessment of cell-state hierarchies from single-cell RNA-seq

Juliá, Miguel ; Telenti, Amalio ; Rausell, Antonio

In: Bioinformatics, 2015, vol. 31, no. 20, p. 3380-3382

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    Title
    • Sincell: an R/Bioconductor package for statistical assessment of cell-state hierarchies from single-cell RNA-seq
    Author
    • Juliá, Miguel. Vital-IT group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
    • Telenti, Amalio. J. Craig Venter Institute, La Jolla, CA 92037
    • Rausell, Antonio. Vital-IT group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
    Document Type
    • Postprint
    OAI-PMH Identifier
    • oai:doc.rero.ch:293853
    Summary
    Summary: Cell differentiation processes are achieved through a continuum of hierarchical intermediate cell states that might be captured by single-cell RNA seq. Existing computational approaches for the assessment of cell-state hierarchies from single-cell data can be formalized under a general framework composed of (i) a metric to assess cell-to-cell similarities (with or without a dimensionality reduction step) and (ii) a graph-building algorithm (optionally making use of a cell clustering step). The Sincell R package implements a methodological toolbox allowing flexible workflows under such a framework. Furthermore, Sincell contributes new algorithms to provide cell-state hierarchies with statistical support while accounting for stochastic factors in single-cell RNA seq. Graphical representations and functional association tests are provided to interpret hierarchies. The functionalities of Sincell are illustrated in a real case study, which demonstrates its ability to discriminate noisy from stable cell-state hierarchies. Availability and implementation: Sincell is an open-source R/Bioconductor package available at http://bioconductor.org/packages/sincell. A detailed manual and a vignette are provided with the package. Contact: antonio.rausell@isb-sib.ch Supplementary information: Supplementary data are available at Bioinformatics online