AMARETTO

DOI: 10.18129/B9.bioc.AMARETTO    

This is the development version of AMARETTO; to use it, please install the devel version of Bioconductor.

Regulatory Network Inference and Driver Gene Evaluation using Integrative Multi-Omics Analysis and Penalized Regression

Bioconductor version: Development (3.10)

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.

Author: Jayendra Shinde, Celine Everaert, Shaimaa Bakr, Mohsen Nabian, Jishu Xu, Vincent Carey, Nathalie Pochet and Olivier Gevaert

Maintainer: Olivier Gevaert <olivier.gevaert at gmail.com>

Citation (from within R, enter citation("AMARETTO")):

Installation

To install this package, start R (version "3.6") and enter:

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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("AMARETTO")

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("AMARETTO")

 

HTML R Script 1. Introduction
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews AlternativeSplicing, BatchEffect, Bayesian, Clustering, CopyNumberVariation, DataImport, DifferentialExpression, DifferentialMethylation, DifferentialSplicing, ExonArray, GeneExpression, GeneRegulation, GeneSetEnrichment, MethylationArray, MicroRNAArray, Microarray, MultipleComparison, Network, Normalization, OneChannel, Preprocessing, ProprietaryPlatforms, QualityControl, RNASeq, Regression, Sequencing, Software, StatisticalMethod, TimeCourse, Transcription, TwoChannel, mRNAMicroarray
Version 1.1.1
In Bioconductor since BioC 3.9 (R-3.6) (< 6 months)
License Apache License (== 2.0) + file LICENSE
Depends R (>= 3.6), impute, doParallel, grDevices, dplyr, methods, ComplexHeatmap
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
LinkingTo Rcpp
Suggests testthat, MASS, knitr
SystemRequirements
Enhances
URL
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 AMARETTO_1.1.1.tar.gz
Windows Binary AMARETTO_1.1.1.zip
Mac OS X 10.11 (El Capitan) AMARETTO_1.1.1.tgz
Source Repository git clone https://git.bioconductor.org/packages/AMARETTO
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/AMARETTO
Package Short Url https://bioconductor.org/packages/AMARETTO/
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