AMARETTO

DOI: 10.18129/B9.bioc.AMARETTO  

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

Bioconductor version: Release (3.16)

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>

Installation

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

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

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	1.14.0
In Bioconductor since	BioC 3.9 (R-3.6) (4 years)
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_1.14.0.tar.gz
Windows Binary	AMARETTO_1.13.0.zip
macOS Binary (x86_64)	AMARETTO_1.13.0.tgz
macOS Binary (arm64)	AMARETTO_1.14.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/AMARETTO
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/AMARETTO
Bioc Package Browser	https://code.bioconductor.org/browse/AMARETTO/
Package Short Url	https://bioconductor.org/packages/AMARETTO/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.16	Source Archive