metaCCA
Summary Statistics-Based Multivariate Meta-Analysis of Genome-Wide Association Studies Using Canonical Correlation Analysis
Bioconductor version: Release (3.17)
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("metaCCA")
):
Installation
To install this package, start R (version "4.3") 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 | R Script | |
Reference Manual | ||
LICENSE | Text |
Details
biocViews | Genetics, GenomeWideAssociation, Regression, SNP, Software, StatisticalMethod |
Version | 1.28.0 |
In Bioconductor since | BioC 3.3 (R-3.3) (7.5 years) |
License | MIT + file LICENSE |
Depends | |
Imports | |
Linking To | |
Suggests | knitr |
System Requirements | |
Enhances | |
URL | https://doi.org/10.1093/bioinformatics/btw052 |
See More
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | metaCCA_1.28.0.tar.gz |
Windows Binary | metaCCA_1.28.0.zip |
macOS Binary (x86_64) | metaCCA_1.28.0.tgz |
macOS Binary (arm64) | metaCCA_1.28.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/metaCCA |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/metaCCA |
Bioc Package Browser | https://code.bioconductor.org/browse/metaCCA/ |
Package Short Url | https://bioconductor.org/packages/metaCCA/ |
Package Downloads Report | Download Stats |