Package Recipe 'bioconductor-moonlight2r'

recipe bioconductor-moonlight2r

Identify oncogenes and tumor suppressor genes from omics data

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/Moonlight2R.html
License:: GPL-3
Recipe:: /bioconductor-moonlight2r/meta.yaml

The understanding of cancer mechanism requires the identification of genes playing a role in the development of the pathology and the characterization of their role (notably oncogenes and tumor suppressors). We present an updated version of the R/bioconductor package called MoonlightR, namely Moonlight2R, which returns a list of candidate driver genes for specific cancer types on the basis of omics data integration. The Moonlight framework contains a primary layer where gene expression data and information about biological processes are integrated to predict genes called oncogenic mediators, divided into putative tumor suppressors and putative oncogenes. This is done through functional enrichment analyses, gene regulatory networks and upstream regulator analyses to score the importance of well-known biological processes with respect to the studied cancer type. By evaluating the effect of the oncogenic mediators on biological processes or through random forests, the primary layer predicts two putative roles for the oncogenic mediators: i) tumor suppressor genes (TSGs) and ii) oncogenes (OCGs). As gene expression data alone is not enough to explain the deregulation of the genes, a second layer of evidence is needed. We have automated the integration of a secondary mutational layer through new functionalities in Moonlight2R. These functionalities analyze mutations in the cancer cohort and classifies these into driver and passenger mutations using the driver mutation prediction tool, CScape-somatic. Those oncogenic mediators with at least one driver mutation are retained as the driver genes. As a consequence, this methodology does not only identify genes playing a dual role (e.g. TSG in one cancer type and OCG in another) but also helps in elucidating the biological processes underlying their specific roles. In particular, Moonlight2R can be used to discover OCGs and TSGs in the same cancer type. This may for instance help in answering the question whether some genes change role between early stages (I, II) and late stages (III, IV). In the future, this analysis could be useful to determine the causes of different resistances to chemotherapeutic treatments.

package bioconductor-moonlight2r¶

Versions:

1.8.1-0, 1.4.0-0, 1.0.0-0

Depends:

on bioconductor-annotationhub >=4.0.0,<4.1.0
on bioconductor-biobase >=2.70.0,<2.71.0
on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-clusterprofiler >=4.18.0,<4.19.0
on bioconductor-complexheatmap >=2.26.0,<2.27.0
on bioconductor-dose >=4.4.0,<4.5.0
on bioconductor-epimix >=1.12.0,<1.13.0
on bioconductor-experimenthub >=3.0.0,<3.1.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-geoquery >=2.78.0,<2.79.0
on bioconductor-org.hs.eg.db >=3.22.0,<3.23.0
on bioconductor-rtracklayer >=1.70.0,<1.71.0
on r-base >=4.5,<4.6.0a0
on r-circlize
on r-data.table
on r-doparallel
on r-dplyr
on r-easypubmed
on r-foreach
on r-fuzzyjoin
on r-ggplot2
on r-gplots
on r-hiver
on r-magrittr
on r-parmigene
on r-purrr
on r-qpdf
on r-randomforest
on r-rcolorbrewer
on r-readr
on r-rismed
on r-rlang
on r-seqminer
on r-stringr
on r-tibble
on r-tidyheatmap
on r-tidyr
on r-withr

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-moonlight2r

to add into an existing workspace instead, run:

pixi add bioconductor-moonlight2r

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-moonlight2r

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-moonlight2r

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-moonlight2r:<tag>

(see bioconductor-moonlight2r/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-moonlight2r/README.html)