metaCCA

DOI: 10.18129/B9.bioc.metaCCA    

Summary Statistics-Based Multivariate Meta-Analysis of Genome-Wide Association Studies Using Canonical Correlation Analysis

Bioconductor version: Release (3.6)

metaCCA performs multivariate analysis of a single or multiple GWAS based on univariate regression coefficients. It allows multivariate representation of both phenotype and genotype. metaCCA extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.

Author: Anna Cichonska <anna.cichonska at helsinki.fi>

Maintainer: Anna Cichonska <anna.cichonska at helsinki.fi>

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

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("metaCCA")

 

PDF R Script metaCCA
PDF   Reference Manual
Text   LICENSE

Details

biocViews Genetics, GenomeWideAssociation, Regression, SNP, Software, StatisticalMethod
Version 1.6.0
In Bioconductor since BioC 3.3 (R-3.3) (2 years)
License MIT + file LICENSE
Depends
Imports
LinkingTo
Suggests knitr
SystemRequirements
Enhances
URL http://biorxiv.org/content/early/2015/07/16/022665
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Source Package metaCCA_1.6.0.tar.gz
Windows Binary metaCCA_1.6.0.zip
Mac OS X 10.11 (El Capitan) metaCCA_1.6.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/metaCCA
Package Short Url http://bioconductor.org/packages/metaCCA/
Package Downloads Report Download Stats

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