recipe bioconductor-omicspca

An R package for quantitative integration and analysis of multiple omics assays from heterogeneous samples

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/OMICsPCA.html

License:

GPL-3

Recipe:

/bioconductor-omicspca/meta.yaml

OMICsPCA is an analysis pipeline designed to integrate multi OMICs experiments done on various subjects (e.g. Cell lines, individuals), treatments (e.g. disease/control) or time points and to analyse such integrated data from various various angles and perspectives. In it's core OMICsPCA uses Principal Component Analysis (PCA) to integrate multiomics experiments from various sources and thus has ability to over data insufficiency issues by using the ingegrated data as representatives. OMICsPCA can be used in various application including analysis of overall distribution of OMICs assays across various samples /individuals /time points; grouping assays by user-defined conditions; identification of source of variation, similarity/dissimilarity between assays, variables or individuals.

package bioconductor-omicspca

versions:

1.20.0-0,  1.18.0-0,  1.16.0-0,  1.12.0-0,  1.10.0-0,  1.8.0-1,  1.8.0-0,  1.5.0-0,  1.2.0-1

depends bioconductor-genomeinfodb:

>=1.38.0,<1.39.0

depends bioconductor-helloranges:

>=1.28.0,<1.29.0

depends bioconductor-iranges:

>=2.36.0,<2.37.0

depends bioconductor-multiassayexperiment:

>=1.28.0,<1.29.0

depends bioconductor-omicspcadata:

>=1.20.0,<1.21.0

depends bioconductor-rtracklayer:

>=1.62.0,<1.63.0

depends r-base:

>=4.3,<4.4.0a0

depends r-cluster:

depends r-clvalid:

depends r-corrplot:

depends r-cowplot:

depends r-data.table:

depends r-factoextra:

depends r-factominer:

depends r-fpc:

depends r-ggplot2:

depends r-kableextra:

depends r-magick:

depends r-mass:

depends r-nbclust:

depends r-pdftools:

depends r-performanceanalytics:

depends r-reshape2:

depends r-rgl:

depends r-rmarkdown:

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-omicspca

and update with::

   mamba update bioconductor-omicspca

To create a new environment, run:

mamba create --name myenvname bioconductor-omicspca

with myenvname being 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-omicspca:<tag>

(see `bioconductor-omicspca/tags`_ for valid values for ``<tag>``)

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Link to this page

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