AMARETTO
Regulatory Network Inference and Driver Gene Evaluation using Integrative Multi-Omics Analysis and Penalized Regression
Bioconductor version: Release (3.17)
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("AMARETTO")):
Installation
To install this package, start R (version "4.3") 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")| 1. Introduction | HTML | R Script |
| Reference Manual | ||
| NEWS | Text | |
| LICENSE | Text |
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 | 1.16.0 |
| In Bioconductor since | BioC 3.9 (R-3.6) (4.5 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 |
| Linking To | Rcpp |
| Suggests | testthat, MASS, knitr, BiocStyle |
| System Requirements | |
| Enhances | |
| URL |
See More
| 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_1.16.0.tar.gz |
| Windows Binary | AMARETTO_1.16.0.zip |
| macOS Binary (x86_64) | AMARETTO_1.16.0.tgz |
| macOS Binary (arm64) | AMARETTO_1.16.0.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 |