title: Sincell: an R/Bioconductor package for statistical assessment of cell-state hierarchies from single-cell RNA-seq.
abstract: 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.
  
  
  METHODS
  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.
  
  
  BACKGROUND
  antonio.rausell@isb-sib.ch
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Vital-IT group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, University of Lausanne, 1015 Lausanne, Switzerland and.
authors.forename: Miguel
authors.initials: M
authors.lastname: Juliá
authors.affiliation: J. Craig Venter Institute, La Jolla, CA 92037.
authors.forename: Amalio
authors.initials: A
authors.lastname: Telenti
authors.affiliation: Vital-IT group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, University of Lausanne, 1015 Lausanne, Switzerland and.
authors.forename: Antonio
authors.initials: A
authors.lastname: Rausell
mesh_terms: D000465:Algorithms; D002454:Cell Differentiation / Q000235:genetics*; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling; D017423:Sequence Analysis, RNA; D059010:Single-Cell Analysis; D012984:Software