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metaCCA

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

Bioconductor version: 3.24 · Package version: 1.41.0

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.

Installation

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

BiocManager::install("metaCCA")

Details

MaintainerAnna Cichonska <anna.cichonska@gmail.com>
AuthorAnna Cichonska <anna.cichonska@gmail.com>
LicenseMIT + file LICENSE
URLhttps://doi.org/10.1093/bioinformatics/btw052
Downloads rank364
Source branchdevel
biocViewsGenetics, GenomeWideAssociation, Regression, SNP, Software, StatisticalMethod

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagemetaCCA_1.41.0.tar.gz
Windows binary (x86_64)metaCCA_1.41.0.zip
macOS binary (arm64)metaCCA_1.41.0.tgz
macOS binary (x86_64)metaCCA_1.41.0.tgz
Dependencies

Suggests: knitr