- recipe bioconductor-scmap
A tool for unsupervised projection of single cell RNA-seq data
- Homepage:
- License:
GPL-3
- Recipe:
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.
- package bioconductor-scmap¶
- versions:
1.24.0-0,1.22.3-0,1.20.0-1,1.20.0-0,1.16.0-2,1.16.0-1,1.16.0-0,1.14.0-0,1.12.0-1,1.24.0-0,1.22.3-0,1.20.0-1,1.20.0-0,1.16.0-2,1.16.0-1,1.16.0-0,1.14.0-0,1.12.0-1,1.12.0-0,1.10.0-0,1.8.0-0,1.6.0-1,1.4.0-0- depends bioconductor-biobase:
>=2.62.0,<2.63.0- depends bioconductor-biobase:
>=2.62.0,<2.63.0a0- depends bioconductor-biocgenerics:
>=0.48.0,<0.49.0- depends bioconductor-biocgenerics:
>=0.48.1,<0.49.0a0- depends bioconductor-s4vectors:
>=0.40.0,<0.41.0- depends bioconductor-s4vectors:
>=0.40.2,<0.41.0a0- depends bioconductor-singlecellexperiment:
>=1.24.0,<1.25.0- depends bioconductor-singlecellexperiment:
>=1.24.0,<1.25.0a0- depends bioconductor-summarizedexperiment:
>=1.32.0,<1.33.0- depends bioconductor-summarizedexperiment:
>=1.32.0,<1.33.0a0- depends libblas:
>=3.9.0,<4.0a0- depends libgcc-ng:
>=12- depends liblapack:
>=3.9.0,<4.0a0- depends libstdcxx-ng:
>=12- depends r-base:
>=4.3,<4.4.0a0- depends r-dplyr:
- depends r-e1071:
- depends r-ggplot2:
- depends r-googlevis:
- depends r-matrixstats:
- depends r-proxy:
- depends r-randomforest:
- depends r-rcpp:
>=0.12.12- depends r-rcpparmadillo:
- depends r-reshape2:
- requirements:
- additional platforms:
Installation
You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).
While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.
Given that you already have a conda environment in which you want to have this package, install with:
mamba install bioconductor-scmap and update with:: mamba update bioconductor-scmap
To create a new environment, run:
mamba create --name myenvname bioconductor-scmap
with
myenvnamebeing a reasonable name for the environment (see e.g. the mamba docs for details and further options).Alternatively, use the docker container:
docker pull quay.io/biocontainers/bioconductor-scmap:<tag> (see `bioconductor-scmap/tags`_ for valid values for ``<tag>``)
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-scmap/README.html)
