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

Bioconductor version: Release (3.19)

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>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


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:

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


biocViews GeneSetEnrichment, Genetics, GenomicVariation, Pathways, Software, StatisticalMethod
Version 1.36.0
In Bioconductor since BioC 3.1 (R-3.2) (9.5 years)
License Artistic-2.0
Depends R (>= 3.5.0), GenomicFeatures, GSEABase(>= 1.24.0)
Imports methods, corpcor, BiocParallel, ggplot2, plyr
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Suggests TxDb.Hsapiens.UCSC.hg19.knownGene, RUnit, BiocGenerics, ReportingTools, BiocStyle
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Follow Installation instructions to use this package in your R session.

Source Package cpvSNP_1.36.0.tar.gz
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macOS Binary (x86_64) cpvSNP_1.36.0.tgz
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