MoonlightR

DOI: 10.18129/B9.bioc.MoonlightR  

Identify oncogenes and tumor suppressor genes from omics data

Bioconductor version: Release (3.16)

Motivation: 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). Results: We present an R/bioconductor package called MoonlightR which returns a list of candidate driver genes for specific cancer types on the basis of TCGA expression data. The method first infers gene regulatory networks and then carries out a functional enrichment analysis (FEA) (implementing an upstream regulator analysis, URA) to score the importance of well-known biological processes with respect to the studied cancer type. Eventually, by means of random forests, MoonlightR predicts two specific roles for the candidate driver genes: i) tumor suppressor genes (TSGs) and ii) oncogenes (OCGs). 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, MoonlightR can be used to discover OCGs and TSGs in the same cancer type. This may help in answering the question whether some genes change role between early stages (I, II) and late stages (III, IV) in breast cancer. In the future, this analysis could be useful to determine the causes of different resistances to chemotherapeutic treatments.

Author: Antonio Colaprico [aut], Catharina Olsen [aut], Matthew H. Bailey [aut], Gabriel J. Odom [aut], Thilde Terkelsen [aut], Mona Nourbakhsh [aut], Astrid Saksager [aut], Tiago C. Silva [aut], André V. Olsen [aut], Laura Cantini [aut], Andrei Zinovyev [aut], Emmanuel Barillot [aut], Houtan Noushmehr [aut], Gloria Bertoli [aut], Isabella Castiglioni [aut], Claudia Cava [aut], Gianluca Bontempi [aut], Xi Steven Chen [aut], Elena Papaleo [aut], Matteo Tiberti [cre, aut]

Maintainer: Matteo Tiberti <tiberti at cancer.dk>

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("MoonlightR")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("MoonlightR")

 

HTML	R Script	Vignette Title
PDF		Reference Manual
Text		NEWS

Details

biocViews	DNAMethylation, DifferentialExpression, DifferentialMethylation, GeneExpression, GeneRegulation, GeneSetEnrichment, MethylationArray, Network, NetworkEnrichment, Pathways, Software, Survival
Version	1.24.0
In Bioconductor since	BioC 3.4 (R-3.3) (6.5 years)
License	GPL (>= 3)
Depends	R (>= 3.5), doParallel, foreach
Imports	parmigene, randomForest, SummarizedExperiment, gplots, circlize, RColorBrewer, HiveR, clusterProfiler, DOSE, Biobase, limma, grDevices, graphics, TCGAbiolinks, GEOquery, stats, RISmed, grid, utils
LinkingTo
Suggests	BiocStyle, knitr, rmarkdown, testthat, devtools, roxygen2, png
SystemRequirements
Enhances
URL	https://github.com/ELELAB/MoonlightR
BugReports	https://github.com/ELELAB/MoonlightR/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	MoonlightR_1.24.0.tar.gz
Windows Binary	MoonlightR_1.24.0.zip (64-bit only)
macOS Binary (x86_64)	MoonlightR_1.24.0.tgz
macOS Binary (arm64)	MoonlightR_1.24.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/MoonlightR
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/MoonlightR
Bioc Package Browser	https://code.bioconductor.org/browse/MoonlightR/
Package Short Url	https://bioconductor.org/packages/MoonlightR/
Package Downloads Report	Download Stats