recipe bioconductor-sincell

R package for the statistical assessment of cell state hierarchies from single-cell RNA-seq data

Homepage

https://bioconductor.org/packages/3.11/bioc/html/sincell.html

License

GPL (>= 2)

Recipe

/bioconductor-sincell/meta.yaml

Links

biotools: sincell

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.

package bioconductor-sincell

Versions

1.20.0-0, 1.18.0-0, 1.16.0-1, 1.16.0-0, 1.14.1-0, 1.14.0-0, 1.12.0-0, 1.10.0-0

Depends

• libblas >=3.8.0,<4.0a0

• libgcc-ng >=7.3.0

• liblapack >=3.8.0,<3.9.0a0

• libstdcxx-ng >=7.3.0

• r-base >=4.0,<4.1.0a0

• r-cluster

• r-entropy

• r-fastica

• r-fields

• r-ggplot2

• r-igraph

• r-mass

• r-proxy

• r-rcpp >=0.11.2

• r-reshape2

• r-rtsne

• r-scatterplot3d

• r-statmod

• r-tsp

Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-sincell

and update with:

conda update bioconductor-sincell

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-sincell:<tag>

(see bioconductor-sincell/tags for valid values for <tag>)

Link to this page

Render an badge with the following MarkDown:

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