metaCCA

This is the released version of metaCCA; for the devel version, see metaCCA.

All versions

3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10, 3.9, 3.8, 3.7, 3.6, 3.5, 3.4, 3.3

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

Bioconductor version: Release (3.23)

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 gmail.com>

Maintainer: Anna Cichonska <anna.cichonska at gmail.com>

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

Anna Cichonska. metaCCA: Summary Statistics-Based Multivariate Meta-Analysis of Genome-Wide Association Studies Using Canonical Correlation Analysis. doi:10.18129/B9.bioc.metaCCA, R package version 1.40.0, https://bioconductor.org/packages/metaCCA.

Generated from the package metadata; it may differ from the package's own citation.

Installation

To install this package, start R (version "4.6") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("metaCCA")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

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

browseVignettes("metaCCA")

metaCCA	PDF	R Script
Reference Manual	PDF
LICENSE	Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	Genetics, GenomeWideAssociation, Regression, SNP, Software, StatisticalMethod
Version	1.40.0
In Bioconductor since	BioC 3.3 (R-3.3) (10.5 years)
License	MIT + file LICENSE
Depends
Imports
System Requirements
URL	https://doi.org/10.1093/bioinformatics/btw052

Suggests	knitr
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report	Build Report, r-universe

Package Archives

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

Source Package	metaCCA_1.40.0.tar.gz
Windows Binary (x86_64)	metaCCA_1.40.0.zip (64-bit only)
macOS Binary (big-sur-x86_64)	metaCCA_1.40.0.tgz
macOS Binary (sonoma-arm64)	metaCCA_1.40.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/metaCCA
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/metaCCA
Package Short Url	https://bioconductor.org/packages/metaCCA/
Package Downloads Report	Download Stats