PleioVar

PleioVar takes as input GWAS data and outputs pleiotropic labels for a list of variants.

Installation

You can install the current version of PleioVar like so:

pkgs = c("data.table", "dplyr", "devtools","stats", "stringr", "parallel", "matrixStats")
  pkgs.na = pkgs[!pkgs %in% installed.packages()[, "Package"]]
  
  if (length(pkgs.na) > 0) {
    install.packages(pkgs.na)
  }
  
  if(!"PleioVar" %in% installed.packages()[, "Package"]) {
  devtools::install_github("martintnr/PleioVar")
  }

Example

This is a basic example to obtain pleiotropic labels from GWAS summary statistics.
Parameters obtained from LHC-MR, LDscores of all variants, and simulated GWAS ZScores are already included.
You should specify the NbCores parameters if your computer can handle parallel computations.

library(data.table)
library(dplyr)
library(stats)
library(stringr)
library(parallel)
library(matrixStats)
library(PleioVar)


if(!file.exists("PleioVar_example/")){system("mkdir PleioVar_example")}
setwd("PleioVar_example")

Prepare_example_data(gzip = T)

ParametersTable <- fread("Data/ParametersTable.csv", header = T, sep = ",")
Index <- fread("Data/Index.csv", header = T, sep = ",")

ListofTraits <- unique(c(ParametersTable$X, ParametersTable$Y))

PleioVar_main(ListofTraits, ParametersTable, Index , NbCores = 1, gzip = T)

In the Results/ folder can be found, for each trait, a file with variants, p-values from PleioVar, and pleiotropy annotation.

library(ggplot2)

Graph <- Example_graph(Trait = "B4")

print(Graph)