Package: Moonlight2R
Type: Package
Title: Identify oncogenes and tumor suppressor genes from omics data
Version: 1.2.0
Date:
Authors@R: 
  c(person("Mona", "Nourbakhsh",
           role="aut"),
    person("Astrid", "Saksager",
           role="aut"),
    person("Nikola", "Tom",
           role="aut"),
    person("Xi Steven", "Chen",
           role="aut"),
    person("Antonio", "Colaprico",
           role="aut"),
    person("Catharina", "Olsen",
           role="aut"),
    person("Matteo", "Tiberti",
           role=c("cre", "aut"),
	   email="tiberti@cancer.dk"),
    person("Elena", "Papaleo",
	   role="aut",
    	   ))
Depends: R (>= 4.3), doParallel, foreach
Imports: parmigene, randomForest, gplots, circlize, RColorBrewer,
        HiveR, clusterProfiler, DOSE, Biobase, grDevices, graphics,
        GEOquery, stats, purrr, RISmed, grid, utils, ComplexHeatmap,
        GenomicRanges, dplyr, fuzzyjoin, rtracklayer, magrittr, qpdf,
        readr, seqminer, stringr, tibble, tidyHeatmap, tidyr,
        AnnotationHub, easyPubMed, org.Hs.eg.db, EpiMix, BiocGenerics,
        ggplot2, ExperimentHub
Description: 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.
License: GPL-3
biocViews: DNAMethylation, DifferentialMethylation, GeneRegulation,
        GeneExpression, MethylationArray, DifferentialExpression,
        Pathways, Network, Survival, GeneSetEnrichment,
        NetworkEnrichment
Suggests: BiocStyle, knitr, rmarkdown, testthat (>= 3.0.0), devtools,
        roxygen2, png
SystemRequirements: CScapeSomatic
VignetteBuilder: knitr
URL: https://github.com/ELELAB/Moonlight2R
BugReports: https://github.com/ELELAB/Moonlight2R/issues
RoxygenNote: 7.2.3
LazyData: false
Encoding: UTF-8
Config/testthat/edition: 3
git_url: https://git.bioconductor.org/packages/Moonlight2R
git_branch: RELEASE_3_19
git_last_commit: 23ea632
git_last_commit_date: 2024-04-30
Repository: Bioconductor 3.19
Date/Publication: 2024-05-01
NeedsCompilation: no
Packaged: 2024-05-02 00:18:21 UTC; biocbuild
Author: Mona Nourbakhsh [aut],
  Astrid Saksager [aut],
  Nikola Tom [aut],
  Xi Steven Chen [aut],
  Antonio Colaprico [aut],
  Catharina Olsen [aut],
  Matteo Tiberti [cre, aut],
  Elena Papaleo [aut]
Maintainer: Matteo Tiberti <tiberti@cancer.dk>
Built: R 4.4.0; ; 2024-05-02 13:08:19 UTC; windows
