r - Apply scale_colour_gradient in multiple histogram -

for set of 8 genes have performance , coverage data 3 different methods, represent @ same time both measurements. thinking plotting performance in y-axis , coverage scale_colour_gradient, like:

and data:

genes   p1      p2      p3  coverage1   coverage2   coverage3 gene1   0.520   0.43    0.68    0.826   1.000   0.84 gene2   0.410   0.48    0.91    0.911   1.000   0.96 gene3   0.240   0.65    0.82    0.833   1.000   0.95 gene4   0.470   0.535   0.81    0.853   1.000   0.77 gene5   0.590   0.677   0.84    0.813   1.000   0.89 gene6   0.370   0.55    0.54    0.753   1.000   0.82 gene7   0.420   0.56    0.78    0.867   1.000   0.91 gene8   0.550   0.638   0.76    0.830   1.000   0.83 

could give me guidelines on how that? i've seen examples of single scale gradient per plot, couldn't find this. know other ideas represent 2 dimensions of information @ same time?

thanks.

edit: @jimbou i've tried similar didn't expected: formatted data using melt, changed colnames avoid confusion , plot it:

colnames(d1) <- c("genes", "performer", "performances","coverager","coverages")  ggplot(d1,aes(genes, fill=performer, alpha=coverager)) + geom_bar(aes(weight=performances), position ="dodge") 

but isn't same

you can specify color , alpha parameters within ggplot function. read data using copy & paste. transform data format appropriate ggplot , plot bars.

d <- read.table("clipboard",header=t) library(reshape2) d1 <- melt(d[,1:4]) d2 <- melt(d[,c(1,5:7)],value.name = "cov") d1 <- cbind(d1,d2[,-1]) head(d1)   genes variable value   var_cov   cov 1 gene1       p1  0.52 coverage1 0.826 2 gene2       p1  0.41 coverage1 0.911 3 gene3       p1  0.24 coverage1 0.833 4 gene4       p1  0.47 coverage1 0.853 5 gene5       p1  0.59 coverage1 0.813 6 gene6       p1  0.37 coverage1 0.753 #plot ggplot(d1,aes(genes,fill=variable,alpha=cov))+ geom_bar(aes(weight=value),position = "dodge")