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# Sincell ### R/Bioconductor package for the statistical assessment of cell state hierarchies from single-cell RNA-seq data [Bioconductor version: Release (3.8)]( 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 <migueljuliamolina at>, Amalio Telenti <atelenti at>, Antonio Rausell <antonio.rausell at> Maintainer: Miguel Julia <migueljuliamolina at>, Antonio Rausell <antonio.rausell at> Citation (from within R, enter `citation("sincell")`): ``` Juliá M, Telenti A, Rausell A (2014). “Sincell: R package for the statistical assessment of cell state hierarchies from single-cell RNA-seq data.” bioRxiv. ``` ## Installation To install this package, start R (version "3.5") and enter: ``` if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("sincell", version = "3.8") ``` For older versions of R, please refer to the appropriate [Bioconductor release]( ## Documentation To view documentation for the version of this package installed in your system, start R and enter: ``` browseVignettes("sincell") ``` | Document | Script | Title | | :-------------: |:-------------:| :------------------| | [PDF]( | [R Script]( | Sincell: Analysis of cell state hierarchies from single-cell RNA-seq | | [PDF]( | - | Reference Manual | | [Text]( | - | NEWS | ## [Download stats](