MultiMeta: Meta-analysis of Multivariate Genome Wide Association Studies
Version 0.1

Allows running a meta-analysis of multivariate Genome Wide Association Studies (GWAS) and easily visualizing results through custom plotting functions. The multivariate setting implies that results for each single nucleotide polymorphism (SNP) include several effect sizes (also known as "beta coefficients", one for each trait), as well as related variance values, but also covariance between the betas. The main goal of the package is to provide combined beta coefficients across different cohorts, together with the combined variance/covariance matrix. The method is inverse-variance based, thus each beta is weighted by the inverse of its variance-covariance matrix, before taking the average across all betas. The default options of the main function \code{multi_meta} will work with files obtained from GEMMA multivariate option for GWAS (Zhou & Stephens, 2014). It will work with any other output, as soon as columns are formatted to have the according names. The package also provides several plotting functions for QQ-plots, Manhattan Plots and custom summary plots.

Getting started

Package details

AuthorDragana Vuckovic
Date of publication2015-01-15 11:44:10
MaintainerDragana Vuckovic <[email protected]>
LicenseGPL (>= 2)
Version0.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("MultiMeta")

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MultiMeta documentation built on May 29, 2017, 11:20 p.m.