CCmed: cross-condition mediation analysis

The goal of CCmed is to provide computationally efficient tools to conduct cross-condition mediation analysis. CCmed identifies trans-associations mediated by cis-effects (e.g. trans-associations of eQTLs mediated by effects on cis-gene expression levels). Mediation analyses can be performed at the gene-level or used to identify trans-associations of complex trait GWAS SNPs/variants.

Setup: dependencies not on CRAN

Note that in order to use CCmed, the Primo package must also be installed. Please follow the following steps to install Primo, if not already installed:

Primo package uses functions from the limma package, which is downloadable from Bioconductor, and the lcmix package, which is downloadable from R-Forge. If you have not yet installed the limma or lcmix packages, please run the following commands prior to installing Primo:

source("https://bioconductor.org/biocLite.R")
biocLite("limma")

install.packages("MASS","matrixStats","nnls","R.methodsS3")
install.packages("lcmix",repos="http://r-forge.r-project.org")

Once you have installed limma and lcmix, you can install and load functions from Primo:

devtools::install_github("kjgleason/Primo")
library("Primo")

Setup

Once you have installed Primo, you can install and load functions from CCmed:

devtools::install_github("kjgleason/CCmed")
library("CCmed")

Citation

To cite CCmed in publications, please use:

Fan Yang, Kevin J. Gleason, Jiebiao Wang, The GTEx consortium, Jubao Duan, Xin He, Brandon L. Pierce and Lin S. Chen. CCmed: cross-condition mediation analysis for identifying robust trans-eQTLs and assessing their effects on human traits. bioRxiv (2019), doi:10.1101/803106.