recipe bioconductor-scmap

Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. scmap is a method for projecting cells from a scRNA-seq experiment on to the cell-types or individual cells identified in a different experiment.

Homepage

https://bioconductor.org/packages/3.9/bioc/html/scmap.html

License

GPL-3

Recipe

/bioconductor-scmap/meta.yaml

package bioconductor-scmap

Versions

1.6.0-1, 1.4.0-0

Depends

• bioconductor-biobase >=2.44.0,<2.45.0

• bioconductor-biocgenerics >=0.30.0,<0.31.0

• bioconductor-s4vectors >=0.22.0,<0.23.0

• bioconductor-singlecellexperiment >=1.6.0,<1.7.0

• bioconductor-summarizedexperiment >=1.14.0,<1.15.0

• libgcc-ng >=7.3.0

• libstdcxx-ng >=7.3.0

• r-base >=3.6,<3.7.0a0

• r-dplyr

• r-e1071

• r-ggplot2

• r-googlevis

• r-matrixstats

• r-proxy

• r-randomforest

• r-rcpp >=0.12.12

• r-rcpparmadillo

• r-reshape2

Required By

• scmap-cli

Installation

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

conda install bioconductor-scmap

and update with:

conda update bioconductor-scmap

or use the docker container:

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

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

Link to this page

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-scmap/README.html)