IntOMICS

This package is for version 3.18 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see .

Integrative analysis of multi-omics data to infer regulatory networks


Bioconductor version: 3.18

IntOMICS is an efficient integrative framework based on Bayesian networks. IntOMICS systematically analyses gene expression (GE), DNA methylation (METH), copy number variation (CNV) and biological prior knowledge (B) to infer regulatory networks. IntOMICS complements the missing biological prior knowledge by so-called empirical biological knowledge (empB), estimated from the available experimental data. An automatically tuned MCMC algorithm (Yang and Rosenthal, 2017) estimates model parameters and the empirical biological knowledge. Conventional MCMC algorithm with additional Markov blanket resampling (MBR) step (Su and Borsuk, 2016) infers resulting regulatory network structure consisting of three types of nodes: GE nodes refer to gene expression levels, CNV nodes refer to associated copy number variations, and METH nodes refer to associated DNA methylation probe(s).

Author: Pacinkova Anna [cre, aut]

Maintainer: Pacinkova Anna <ana.pacinkova at gmail.com>

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

Installation

To install this package, start R (version "4.3") and enter:


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

BiocManager::install("IntOMICS")

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("IntOMICS")
IntOMICS tutorial HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Bayesian, CopyNumberVariation, DNAMethylation, GeneExpression, GeneRegulation, Network, Software, SystemsBiology
Version 1.2.0
In Bioconductor since BioC 3.17 (R-4.3) (1 year)
License GPL-3
Depends
Imports bnlearn, bnstruct, matrixStats, RColorBrewer, bestNormalize, igraph, gplots, stats, utils, graphics, numbers, SummarizedExperiment, ggplot2, ggraph, methods, cowplot, grid, rlang
System Requirements
URL https://github.com/anna-pacinkova/IntOMICS
Bug Reports https://github.com/anna-pacinkova/IntOMICS/issues
See More
Suggests BiocStyle, knitr, rmarkdown, curatedTCGAData, TCGAutils, testthat
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package IntOMICS_1.2.0.tar.gz
Windows Binary IntOMICS_1.2.0.zip
macOS Binary (x86_64) IntOMICS_1.2.0.tgz
macOS Binary (arm64) IntOMICS_1.2.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/IntOMICS
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/IntOMICS
Bioc Package Browser https://code.bioconductor.org/browse/IntOMICS/
Package Short Url https://bioconductor.org/packages/IntOMICS/
Package Downloads Report Download Stats