Package Recipe 'bioconductor-pcaexplorer'

recipe bioconductor-pcaexplorer

Interactive Visualization of RNA-seq Data Using a Principal Components Approach

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/pcaExplorer.html
License:: MIT + file LICENSE
Recipe:: /bioconductor-pcaexplorer/meta.yaml
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:

3.4.0-0, 3.0.0-0, 2.28.0-0, 2.26.1-0, 2.24.0-0, 2.20.0-0, 2.18.0-0, 2.16.0-1, 2.16.0-0,

3.4.0-0, 3.0.0-0, 2.28.0-0, 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:

on bioconductor-annotationdbi >=1.72.0,<1.73.0
on bioconductor-biomart >=2.66.0,<2.67.0
on bioconductor-deseq2 >=1.50.0,<1.51.0
on bioconductor-genefilter >=1.92.0,<1.93.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-go.db >=3.22.0,<3.23.0
on bioconductor-gostats >=2.76.0,<2.77.0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-limma >=3.66.0,<3.67.0
on bioconductor-mosdef >=1.6.0,<1.7.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on bioconductor-topgo >=2.62.0,<2.63.0
on r-base >=4.5,<4.6.0a0
on r-base64enc
on r-dt
on r-ggplot2 >=2.0.0
on r-ggrepel
on r-heatmaply
on r-knitr
on r-nmf
on r-pheatmap
on r-plotly
on r-plyr
on r-rmarkdown
on r-scales
on r-shiny >=0.12.0
on r-shinyace
on r-shinybs
on r-shinydashboard
on r-threejs
on r-tidyr

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-pcaexplorer

to add into an existing workspace instead, run:

pixi add bioconductor-pcaexplorer

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-pcaexplorer

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-pcaexplorer

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

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

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

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

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-pcaexplorer/README.html)