recipe bioconductor-poma

User-friendly Workflow for Metabolomics and Proteomics Data Analysis

Homepage:

https://bioconductor.org/packages/3.14/bioc/html/POMA.html

License:

GPL-3

Recipe:

/bioconductor-poma/meta.yaml

A structured, reproducible and easy-to-use workflow for the visualization, pre-processing, exploratory data analysis, and statistical analysis of metabolomics and proteomics data. The main aim of POMA is to enable a flexible data cleaning and statistical analysis processes in one comprehensible and user-friendly R package. This package also has a Shiny app version that implements all POMA functions. See https://github.com/pcastellanoescuder/POMAShiny.

package bioconductor-poma

Versions:

1.4.0-0,  1.2.0-0,  1.0.0-2,  1.0.0-1

Depends:

• bioconductor-complexheatmap >=2.10.0,<2.11.0

• bioconductor-impute >=1.68.0,<1.69.0

• bioconductor-limma >=3.50.0,<3.51.0

• bioconductor-mixomics >=6.17.0,<6.18.0

• bioconductor-msnbase >=2.20.0,<2.21.0

• bioconductor-rankprod >=3.20.0,<3.21.0

• r-base >=4.1,<4.2.0a0

• r-broom

• r-caret

• r-clisymbols

• r-crayon

• r-dplyr

• r-e1071

• r-ggcorrplot

• r-ggplot2

• r-ggraph

• r-ggrepel

• r-glasso >=1.11

• r-glmnet

• r-knitr

• r-magrittr

• r-patchwork

• r-qpdf

• r-randomforest

• r-rmarkdown

• r-tibble

• r-tidyr

• r-vegan

Required By:

Installation

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

conda install bioconductor-poma

and update with:

conda update bioconductor-poma

or use the docker container:

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

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

Download stats

Link to this page

Render an badge with the following MarkDown:

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