- recipe bioconductor-pcaexplorer
Interactive Visualization of RNA-seq Data Using a Principal Components Approach
- Homepage:
https://bioconductor.org/packages/3.17/bioc/html/pcaExplorer.html
- License:
MIT + file LICENSE
- Recipe:
- Links:
biotools: pcaexplorer, doi: 10.18547/gcb.2017.vol3.iss1.e39
This package provides functionality for interactive visualization of RNA-seq datasets based on Principal Components Analysis. The methods provided allow for quick information extraction and effective data exploration. A Shiny application encapsulates the whole analysis.
- package bioconductor-pcaexplorer¶
- versions:
2.26.1-0,2.24.0-0,2.20.0-0,2.18.0-0,2.16.0-1,2.16.0-0,2.14.0-0,2.12.0-0,2.10.0-1,2.26.1-0,2.24.0-0,2.20.0-0,2.18.0-0,2.16.0-1,2.16.0-0,2.14.0-0,2.12.0-0,2.10.0-1,2.8.0-0,2.6.0-0,2.4.0-0,2.2.1-0,2.0.0-0- depends bioconductor-annotationdbi:
>=1.62.0,<1.63.0- depends bioconductor-biomart:
>=2.56.0,<2.57.0- depends bioconductor-deseq2:
>=1.40.0,<1.41.0- depends bioconductor-genefilter:
>=1.82.0,<1.83.0- depends bioconductor-genomicranges:
>=1.52.0,<1.53.0- depends bioconductor-go.db:
>=3.17.0,<3.18.0- depends bioconductor-gostats:
>=2.66.0,<2.67.0- depends bioconductor-iranges:
>=2.34.0,<2.35.0- depends bioconductor-limma:
>=3.56.0,<3.57.0- depends bioconductor-s4vectors:
>=0.38.0,<0.39.0- depends bioconductor-summarizedexperiment:
>=1.30.0,<1.31.0- depends bioconductor-topgo:
>=2.52.0,<2.53.0- depends r-base:
>=4.3,<4.4.0a0- depends r-base64enc:
- depends r-dt:
- depends r-ggplot2:
>=2.0.0- depends r-ggrepel:
- depends r-heatmaply:
- depends r-knitr:
- depends r-nmf:
- depends r-pheatmap:
- depends r-plotly:
- depends r-plyr:
- depends r-rmarkdown:
- depends r-scales:
- depends r-shiny:
>=0.12.0- depends r-shinyace:
- depends r-shinybs:
- depends r-shinydashboard:
- depends r-threejs:
- depends r-tidyr:
- requirements:
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-pcaexplorer and update with:: mamba update bioconductor-pcaexplorer
To create a new environment, run:
mamba create --name myenvname bioconductor-pcaexplorer
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-pcaexplorer:<tag> (see `bioconductor-pcaexplorer/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-pcaexplorer/README.html)
