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RIVER

R package for RIVER (RNA-Informed Variant Effect on Regulation)


Bioconductor version: Release (3.18)

An implementation of a probabilistic modeling framework that jointly analyzes personal genome and transcriptome data to estimate the probability that a variant has regulatory impact in that individual. It is based on a generative model that assumes that genomic annotations, such as the location of a variant with respect to regulatory elements, determine the prior probability that variant is a functional regulatory variant, which is an unobserved variable. The functional regulatory variant status then influences whether nearby genes are likely to display outlier levels of gene expression in that person. See the RIVER website for more information, documentation and examples.

Author: Yungil Kim [aut, cre], Alexis Battle [aut]

Maintainer: Yungil Kim <ipw012 at gmail.com>

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

Installation

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


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

BiocManager::install("RIVER")

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("RIVER")
RIVER HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Bayesian, BiomedicalInformatics, Clustering, FunctionalGenomics, FunctionalPrediction, GeneExpression, GeneRegulation, GeneticVariability, Genetics, GenomicVariation, Regression, SNP, Software, SystemsBiology, Transcription, TranscriptomeVariant, Transcriptomics
Version 1.26.0
In Bioconductor since BioC 3.5 (R-3.4) (7 years)
License GPL (>= 2)
Depends R (>= 3.3.2)
Imports glmnet, pROC, ggplot2, graphics, stats, Biobase, methods, utils
System Requirements
URL https://github.com/ipw012/RIVER
Bug Reports https://github.com/ipw012/RIVER/issues
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Suggests BiocStyle, knitr, rmarkdown, testthat, devtools
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Build Report Build Report

Package Archives

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

Source Package RIVER_1.26.0.tar.gz
Windows Binary RIVER_1.26.0.zip (64-bit only)
macOS Binary (x86_64) RIVER_1.26.0.tgz
macOS Binary (arm64) RIVER_1.26.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/RIVER
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/RIVER
Bioc Package Browser https://code.bioconductor.org/browse/RIVER/
Package Short Url https://bioconductor.org/packages/RIVER/
Package Downloads Report Download Stats