To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("cpvSNP")

In most cases, you don't need to download the package archive at all.

cpvSNP

   

This package is for version 3.3 of Bioconductor; for the stable, up-to-date release version, see cpvSNP.

Gene set analysis methods for SNP association p-values that lie in genes in given gene sets

Bioconductor version: 3.3

Gene set analysis methods exist to combine SNP-level association p-values into gene sets, calculating a single association p-value for each gene set. This package implements two such methods that require only the calculated SNP p-values, the gene set(s) of interest, and a correlation matrix (if desired). One method (GLOSSI) requires independent SNPs and the other (VEGAS) can take into account correlation (LD) among the SNPs. Built-in plotting functions are available to help users visualize results.

Author: Caitlin McHugh, Jessica Larson, and Jason Hackney

Maintainer: Caitlin McHugh <mchughc at uw.edu>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("cpvSNP")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("cpvSNP")

 

PDF R Script Running gene set analyses with the "cpvSNP" package
PDF   Reference Manual
Text   NEWS

Details

biocViews GeneSetEnrichment, Genetics, GenomicVariation, Pathways, Software, StatisticalMethod
Version 1.4.0
In Bioconductor since BioC 3.1 (R-3.2) (1.5 years)
License Artistic-2.0
Depends R (>= 2.10), GenomicFeatures, GSEABase(>= 1.24.0)
Imports methods, corpcor, BiocParallel, ggplot2, plyr
LinkingTo
Suggests TxDb.Hsapiens.UCSC.hg19.knownGene, RUnit, BiocGenerics, ReportingTools, BiocStyle
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source cpvSNP_1.4.0.tar.gz
Windows Binary cpvSNP_1.4.0.zip
Mac OS X 10.9 (Mavericks) cpvSNP_1.4.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/cpvSNP/tree/release-3.3
Package Short Url http://bioconductor.org/packages/cpvSNP/
Package Downloads Report Download Stats

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