omicRexposome

DOI: 10.18129/B9.bioc.omicRexposome  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see omicRexposome.

Exposome and omic data associatin and integration analysis

Bioconductor version: 3.17

omicRexposome systematizes the association evaluation between exposures and omic data, taking advantage of MultiDataSet for coordinated data management, rexposome for exposome data definition and limma for association testing. Also to perform data integration mixing exposome and omic data using multi co-inherent analysis (omicade4) and multi-canonical correlation analysis (PMA).

Author: Carles Hernandez-Ferrer [aut, cre], Juan R. González [aut]

Maintainer: Xavier Escribà Montagut <xavier.escriba at isglobal.org>

Installation

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

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

BiocManager::install("omicRexposome")

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("omicRexposome")

 

HTML	R Script	Exposome Data Integration with Omic Data
PDF		Reference Manual
Text		LICENSE

Details

biocViews	DifferentialExpression, DifferentialMethylation, Epigenetics, GeneExpression, GeneRegulation, ImmunoOncology, MultipleComparison, Proteomics, Regression, Software, StatisticalMethod, Transcriptomics, Visualization, WorkflowStep
Version	1.22.0
In Bioconductor since	BioC 3.6 (R-3.4) (6 years)
License	MIT + file LICENSE
Depends	R (>= 3.5.0), Biobase
Imports	stats, utils, grDevices, graphics, methods, rexposome, limma, sva, ggplot2, ggrepel, PMA, omicade4, gridExtra, MultiDataSet, SmartSVA, isva, parallel, SummarizedExperiment, stringr
LinkingTo
Suggests	BiocStyle, knitr, rmarkdown, snpStats, brgedata
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	omicRexposome_1.22.0.tar.gz
Windows Binary	omicRexposome_1.22.0.zip
macOS Binary (x86_64)	omicRexposome_1.22.0.tgz
macOS Binary (arm64)	omicRexposome_1.22.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/omicRexposome
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/omicRexposome
Bioc Package Browser	https://code.bioconductor.org/browse/omicRexposome/
Package Short Url	https://bioconductor.org/packages/omicRexposome/
Package Downloads Report	Download Stats