Package: AMARETTO
Type: Package
Title: Regulatory Network Inference and Driver Gene Evaluation using
        Integrative Multi-Omics Analysis and Penalized Regression
Version: 1.28.0
Date: 2016-06-06
Author: Jayendra Shinde, Celine Everaert, Shaimaa Bakr, Mohsen Nabian,
        Jishu Xu, Vincent Carey, Nathalie Pochet and Olivier Gevaert
Maintainer: Olivier Gevaert <olivier.gevaert@gmail.com>
Depends: R (>= 3.6), impute, doParallel, grDevices, dplyr, methods,
        ComplexHeatmap
Description: Integrating an increasing number of available multi-omics
        cancer data remains one of the main challenges to improve our
        understanding of cancer. One of the main challenges is using
        multi-omics data for identifying novel cancer driver genes. We
        have developed an algorithm, called AMARETTO, that integrates
        copy number, DNA methylation and gene expression data to
        identify a set of driver genes by analyzing cancer samples and
        connects them to clusters of co-expressed genes, which we
        define as modules. We applied AMARETTO in a pancancer setting
        to identify cancer driver genes and their modules on multiple
        cancer sites. AMARETTO captures modules enriched in
        angiogenesis, cell cycle and EMT, and modules that accurately
        predict survival and molecular subtypes. This allows AMARETTO
        to identify novel cancer driver genes directing canonical
        cancer pathways.
License: Apache License (== 2.0) + file LICENSE
LazyLoad: yes
LazyData: true
Encoding: UTF-8
biocViews:
        StatisticalMethod,DifferentialMethylation,GeneRegulation,GeneExpression,MethylationArray,Transcription,Preprocessing,BatchEffect,DataImport,mRNAMicroarray,MicroRNAArray,Regression,Clustering,RNASeq,CopyNumberVariation,Sequencing,Microarray,Normalization,Network,Bayesian,ExonArray,OneChannel,TwoChannel,ProprietaryPlatforms,AlternativeSplicing,DifferentialExpression,DifferentialSplicing,GeneSetEnrichment,MultipleComparison,QualityControl,TimeCourse
Suggests: testthat, MASS, knitr, BiocStyle
NeedsCompilation: no
Packaged: 2026-04-29 18:08:43 UTC; root
Imports: callr (>= 3.0.0.9001), Matrix, Rcpp, BiocFileCache, DT,
        MultiAssayExperiment, circlize, curatedTCGAData, foreach,
        glmnet, httr, limma, matrixStats, readr, reshape2, tibble,
        rmarkdown, graphics, grid, parallel, stats, knitr, ggplot2,
        gridExtra, utils
Roxygen: list(markdown = TRUE)
RoxygenNote: 6.1.1.9000
LinkingTo: Rcpp
VignetteBuilder: knitr
Config/pak/sysreqs: cmake make libicu-dev libpng-dev libuv1-dev
        libssl-dev perl libx11-dev zlib1g-dev
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2026-04-28 12:49:47 UTC
RemoteUrl: https://github.com/bioc/AMARETTO
RemoteRef: RELEASE_3_23
RemoteSha: 4b60a9dafc2681e6700f8ba6aef3a05cd42275e1
Built: R 4.6.0; ; 2026-04-29 18:35:53 UTC; windows
