Bioconductor version: Release (3.17)
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")
):
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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("RIVER")
HTML | R Script | RIVER |
Reference Manual | ||
Text | NEWS |
biocViews | Bayesian, BiomedicalInformatics, Clustering, FunctionalGenomics, FunctionalPrediction, GeneExpression, GeneRegulation, GeneticVariability, Genetics, GenomicVariation, Regression, SNP, Software, SystemsBiology, Transcription, TranscriptomeVariant, Transcriptomics |
Version | 1.24.0 |
In Bioconductor since | BioC 3.5 (R-3.4) (6.5 years) |
License | GPL (>= 2) |
Depends | R (>= 3.3.2) |
Imports | glmnet, pROC, ggplot2, graphics, stats, Biobase, methods, utils |
LinkingTo | |
Suggests | BiocStyle, knitr, rmarkdown, testthat, devtools |
SystemRequirements | |
Enhances | |
URL | https://github.com/ipw012/RIVER |
BugReports | https://github.com/ipw012/RIVER/issues |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | RIVER_1.24.0.tar.gz |
Windows Binary | RIVER_1.24.0.zip |
macOS Binary (x86_64) | RIVER_1.24.0.tgz |
macOS Binary (arm64) | RIVER_1.24.0.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 |
Old Source Packages for BioC 3.17 | Source Archive |
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