pleiotropyPlot

The pleiotropy plot is a tool designed to interpret SNP association studies obtained using PLEIO (link). To install the R package on your local machine, please run the following commands in R:

install.packages("devtools")
install.packages("roxygen2")
devtools::install_github("cuelee/pleiotropyPlot")

In order to run pleiotropyPlot you will need the following R dependencies:

ComplexHeatmap (>= 2.0.0)
circlize (>= 0.4.8)

For users who have never used pleiotropyPlot, you can download an example data from the following link.

Or use wget

wget https://www.dropbox.com/s/2jeoh4149sofjub/pleiotropyPlot_example.zip
unzip pleiotropyPlot_example.zip

After finishing the installation, you can generate circoplot implemented in pleio using the following command.

library(pleiotropyPlot)

To run the example files above, please run the following code in R. Before execution, it is necessary to enter the path where the sample files are saved in the provided code (which is marked by using [[marked]].

library(pleiotropyPlot)

example_folder = [[path to the folder containing example files]]

pleioin = gzfile(file.path(example_folder, 'input.txt.gz'))
pleiores = gzfile(file.path(example_folder, 'output.txt.gz'))
sumstats = gzfile(file.path(example_folder, 'sumstats.txt.gz'))
snps = gzfile(file.path(example_folder, 'snp.txt.gz'))
h2 = gzfile(file.path(example_folder, 'heritability.txt.gz'))
rg = gzfile(file.path(example_folder, 'rg.txt.gz'))
traits = file.path(example_folder, 'traits.txt.gz')
ref = gzfile(file.path(example_folder, '1000G_SNP_CHR_BP_A1_A2_CHR1.txt.gz'))
outf = example_folder

input_parser = function(pleioin, pleiores, sumstats, snps, h2, rg, traits, ref){
  dat = list()

  dat$pleioin = read.table(pleioin, header = T, check.names = F, row.names = 'SNP', sep='\t')
  dat$pleiores = read.table(pleiores,header = T, check.names = F, row.names = 'SNP', sep='\t')
  dat$sumstats = read.table(sumstats,header = T, check.names = F, row.names = 'SNP', sep='\t')
  dat$h2 = as.vector(read.table(h2, header= T, check.names=F))
  dat$rg = as.matrix(read.table(rg, header= T, check.names=F))
  dat$traits = as.matrix(read.table(traits, sep='\t',header= T,check.names=F))
  dat$snps = as.vector(as.matrix(read.table(snps, sep='\t',header= F,check.names=F)))
  dat$ref = read.table(ref,header = T, check.names = F, row.names = 'RSID', sep='\t')
  dat$outf = outf

  change_colname= function(col_name){
    new_colname = NA
    for (i in 1:nrow(dat$traits)){
      asubstr = dat$traits[i,'filename']
      if (grepl(asubstr, col_name)){
        new_colname = gsub(asubstr,dat$traits[i,'traitname'],col_name)
        break
      }
    }
    return(new_colname)
  }

  rownames(dat$rg) = colnames(dat$rg) = sapply(colnames(dat$rg), function(x) dat$traits[which(dat$traits[,'filename']==x),2])
  colnames(dat$h2) = sapply(colnames(dat$h2), function(x) dat$traits[which(dat$traits[,'filename']==x),2])
  colnames(dat$sumstats) = sapply(colnames(dat$sumstats), function(x) change_colname(x) )
  colnames(dat$pleioin) = sapply(colnames(dat$pleioin), function(x) change_colname(x) )

  return(dat)
}

if (!exists('dat')){ dat = input_parser(pleioin, pleiores, sumstats, snps, h2, rg, traits, ref) }

main = function(dat){

  for ( i in 1:length(dat$snps)){

    pleioin = dat$pleioin
    pleiores = dat$pleiores
    snp_reference = dat$ref
    sumstats = dat$sumstats
    rg_matrix = dat$rg
    h2 = dat$h2
    outf = dat$out
    traits = colnames(dat$rg)

    snp = as.character(dat$snps[i])

    jpeg(file.path(outf,paste(snp,'.jpeg',sep='')), width = 7, height = 7, units = 'in', res = 300)
    par(mar =c(0,0,0,0))
    pleioplot(snp, traits, rg_matrix, sumstats, pleioin, pleiores, h2, snp_reference)
    dev.off()

  }

}


main(dat)