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 workflow composed of i) a metric to assess cell-to-cell similarities (combined or not with a dimensionality reduction step), and ii) a graph-building algorithm (optionally making use of a cells-clustering step). Sincell R package implements a methodological toolbox allowing flexible workflows under such 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.
|Author||Miguel Julia <firstname.lastname@example.org>, Amalio Telenti <email@example.com>, Antonio Rausell <firstname.lastname@example.org>|
|Bioconductor views||BiomedicalInformatics CellBiology Clustering FunctionalGenomics GeneExpression GeneSetEnrichment GraphAndNetwork ImmunoOncology RNASeq Sequencing SystemsBiology Visualization|
|Maintainer||Miguel Julia <email@example.com>, Antonio Rausell<firstname.lastname@example.org>|
|License||GPL (>= 2)|
|Package repository||View on Bioconductor|
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