recipe bioconductor-phenotest

Tools to test association between gene expression and phenotype in a way that is efficient, structured, fast and scalable. We also provide tools to do GSEA (Gene set enrichment analysis) and copy number variation.

Homepage:

https://bioconductor.org/packages/3.16/bioc/html/phenoTest.html

License:

GPL (>=2)

Recipe:

/bioconductor-phenotest/meta.yaml

Tools to test correlation between gene expression and phenotype in a way that is efficient, structured, fast and scalable. GSEA is also provided.

package bioconductor-phenotest

Versions:

1.46.0-0,  1.42.0-0,  1.40.0-0,  1.38.0-1,  1.38.0-0,  1.36.0-0,  1.34.0-0,  1.32.0-1,  1.30.0-0

Depends:

• bioconductor-annotate >=1.76.0,<1.77.0

• bioconductor-annotationdbi >=1.60.0,<1.61.0

• bioconductor-biobase >=2.58.0,<2.59.0

• bioconductor-biomart >=2.54.0,<2.55.0

• bioconductor-category >=2.64.0,<2.65.0

• bioconductor-genefilter >=1.80.0,<1.81.0

• bioconductor-gseabase >=1.60.0,<1.61.0

• bioconductor-heatplus >=3.6.0,<3.7.0

• bioconductor-hgu133a.db >=3.13.0,<3.14.0

• bioconductor-hopach >=2.58.0,<2.59.0

• bioconductor-limma >=3.54.0,<3.55.0

• r-base >=4.2,<4.3.0a0

• r-bma

• r-ellipse

• r-ggplot2

• r-gplots

• r-hmisc

• r-mgcv

• r-survival

• r-xtable

Required By:

• bioconductor-cancer

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-phenotest

and update with:

conda update bioconductor-phenotest

or use the docker container:

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

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

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-phenotest/README.html)