Package Recipe 'bioconductor-rnaseqsamplesize'

recipe bioconductor-rnaseqsamplesize

RnaSeqSampleSize

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/RnaSeqSampleSize.html
License:: GPL (>= 2)
Recipe:: /bioconductor-rnaseqsamplesize/meta.yaml

RnaSeqSampleSize package provides a sample size calculation method based on negative binomial model and the exact test for assessing differential expression analysis of RNA-seq data. It controls FDR for multiple testing and utilizes the average read count and dispersion distributions from real data to estimate a more reliable sample size. It is also equipped with several unique features, including estimation for interested genes or pathway, power curve visualization, and parameter optimization.

package bioconductor-rnaseqsamplesize¶

Versions:

2.20.0-0, 2.16.0-0, 2.12.0-0, 2.10.0-0, 2.8.0-1, 2.8.0-0, 2.4.1-1, 2.4.1-0, 2.4.0-0,

2.20.0-0, 2.16.0-0, 2.12.0-0, 2.10.0-0, 2.8.0-1, 2.8.0-0, 2.4.1-1, 2.4.1-0, 2.4.0-0, 2.2.0-0, 2.0.0-2, 2.0.0-1, 1.17.0-1, 1.16.0-1, 1.14.0-0, 1.12.0-2

Depends:

on bioconductor-biomart >=2.66.0,<2.67.0
on bioconductor-biomart >=2.66.0,<2.67.0a0
on bioconductor-edger >=4.8.0,<4.9.0
on bioconductor-edger >=4.8.2,<4.9.0a0
on bioconductor-keggrest >=1.50.0,<1.51.0
on bioconductor-keggrest >=1.50.0,<1.51.0a0
on bioconductor-recount >=1.36.0,<1.37.0
on bioconductor-recount >=1.36.0,<1.37.0a0
on bioconductor-rnaseqsamplesizedata >=1.42.0,<1.43.0
on bioconductor-rnaseqsamplesizedata >=1.42.0,<1.43.0a0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-dplyr
on r-ggplot2
on r-ggpubr
on r-heatmap3
on r-matlab
on r-rcpp >=0.11.2
on r-tidyr
on r-tidyselect

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-rnaseqsamplesize

to add into an existing workspace instead, run:

pixi add bioconductor-rnaseqsamplesize

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-rnaseqsamplesize

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-rnaseqsamplesize

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-rnaseqsamplesize:<tag>

(see bioconductor-rnaseqsamplesize/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-rnaseqsamplesize/README.html)