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
| Maintainer | Anna Cichonska <anna.cichonska@gmail.com> |
| Author | Anna Cichonska <anna.cichonska@gmail.com> |
| License | MIT + file LICENSE |
| URL | https://doi.org/10.1093/bioinformatics/btw052 |
| Downloads rank | 364 |
| Source branch | devel |
| biocViews | Genetics, GenomeWideAssociation, Regression, SNP, Software, StatisticalMethod |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | metaCCA_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