Package: metaCCA 1.33.0
Anna Cichonska
metaCCA: Summary Statistics-Based Multivariate Meta-Analysis of Genome-Wide Association Studies Using Canonical Correlation Analysis
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.
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metaCCA.pdf |metaCCA.html✨
metaCCA/json (API)
| # Install 'metaCCA' in R: |
| install.packages('metaCCA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- N1 - Number of individuals in study 1.
- N2 - Number of individuals in study 2.
- S_XX_study1 - Correlations between 10 SNPs corresponding to the population underlying study 1.
- S_XX_study2 - Correlations between 10 SNPs corresponding to the population underlying study 2.
- S_XY_full_study1 - Univariate summary statistics of 10 traits across 1000 SNPs (study 1).
- S_XY_full_study2 - Univariate summary statistics of 10 traits across 1000 SNPs (study 2).
- S_XY_study1 - Univariate summary statistics of 10 traits across 10 SNPs (study 1).
- S_XY_study2 - Univariate summary statistics of 10 traits across 10 SNPs (study 2).
On BioConductor:metaCCA-1.33.0(bioc 3.20)metaCCA-1.32.0(bioc 3.19)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:14372c65ad
Exports:estimateSyymetaCcaGpmetaCcaPlusGp
Dependencies:
