metaCCA
Summary Statistics-Based Multivariate Meta-Analysis of Genome-Wide Association Studies Using Canonical Correlation Analysis
Bioconductor version: 3.23 · Package version: 1.40.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
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 |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | Genetics, GenomeWideAssociation, Regression, SNP, Software, StatisticalMethod |
| Package Short Url | https://bioconductor.org/packages/metaCCA/ |
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.
Documentation
Download
Follow the 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 |
| macOS binary (arm64) | metaCCA_1.40.0.tgz |
| macOS binary (x86_64) | metaCCA_1.40.0.tgz |
Dependencies
Suggests: knitr