library(ggplot2)
library(reshape)
tab = read.table('/Volumes/data/martha/Networks/Data/MAGIC_VarComp_gxe_vc-flatfile.txt', h = T)
plot.dir = '/Volumes/data/martha/Networks/Results/'

explore.variance.components <- function(tab, plot.dir = ''){
  pdffile = paste(plot.dir, 'exploratory.plots.pdf', sep = '')
  pdf(pdffile)
  print(tab[1:10,])
  df.gen = melt(tab, measure.vars = c('Vcis', 'Vtrans'))
  print(head(df.gen))
  df.all = melt(tab, measure.vars = c('Vcis', 'VcisGxE', 'Vtrans', 'VtransGxE'))
  #plot distribution of cis and trans qtls
  p <- ggplot(df.gen) + geom_density(aes(x = value, fill = variable)) + xlab('Genetic variance distribution')
  q <- ggplot(tab) + geom_point(aes(x = Vcis, y = Vtrans)) + xlab('Vcis') + ylab('Vtrans')
  r <- ggplot(df.all) + geom_boxplot(aes(x = variable, y = value, fill = variable))
  h <- ggplot(tab) + geom_histogram(aes(x = Vtrans), binwidth = 0.01)
  print(p)
  print(q)
  print(r)
  print(h)
  dev.off()
}

explore.variance.components(tab, plot.dir)