Sincell – for statistical assessment of cell-state hierarchies from single-cell RNA-Seq

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 might 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.


Overall workflow for the statistical assessment of cell-state hierarchies implemented by the Sincell R package. Dashed arrows correspond to optional steps in the analysis.

Availability – Sincell is an open-source R/Bioconductor package available at A detailed manual and vignette is provided with the package.

Juliá M, Telenti A, Rausell A. (2015) Sincell: an R/Bioconductor package for statistical assessment of cell-state hierarchies from single-cell RNA-seq. Bioinformatics [Epub ahead of print]. [article]

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