DOI: 10.18129/B9.bioc.RIVER    

This is the development version of RIVER; for the stable release version, see RIVER.

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

Bioconductor version: Development (3.7)

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>

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biocViews Bayesian, BiomedicalInformatics, Clustering, FunctionalGenomics, FunctionalPrediction, GeneExpression, GeneRegulation, GeneticVariability, Genetics, GenomicVariation, Regression, SNP, Software, SystemsBiology, Transcription, TranscriptomeVariant, Transcriptomics
Version 1.3.0
In Bioconductor since BioC 3.5 (R-3.4) (1 year)
License GPL (>= 2)
Depends R (>= 3.3.2)
Imports glmnet, pROC, ggplot2, graphics, stats, Biobase, methods, utils
Suggests BiocStyle, knitr, rmarkdown, testthat, devtools
URL https://github.com/ipw012/RIVER
BugReports https://github.com/ipw012/RIVER/issues
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Imports Me
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Source Package RIVER_1.3.0.tar.gz
Windows Binary RIVER_1.3.0.zip
Mac OS X 10.11 (El Capitan) RIVER_1.3.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/RIVER
Package Short Url http://bioconductor.org/packages/RIVER/
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