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>

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