Hello, I have a couple of co-expressed gene clusters corresponding to each developmental stage of a plant, (total 3 such stages). I want to plot the distribution of genes in the modules for each of the stages, in a compact form since I have to put them in a poster. Pie charts are taking too much space.
Kindly suggest a resource where I can do this sort of a thing: Plots with Multiple axes
Example of my data:
Clusters x-stage y-stage z-stage
black 91 190 127
green 163 564 258
turquoise 318 420 149
red 200 381 295
1 answer
I think that you can achieve the goal by using ggplot in order to make individual plots and then combine those with grid & gridExtra packages as it is shown here. Yet another option would be to use facet-grid of ggplot. If you update your post with few examples of the data and figures that you have, I am sure that you'll be able to get more help here.
Here is an easy way of visualization of your data using facets and barplots, i.e. geom_hist:
require(ggplot2)
require(gridExtra)
require(reshape)
dat=read.table(header=T, text="Clusters x-stage y-stage z-stage
black 91 190 127
green 163 564 258
turquoise 318 420 149
red 200 381 295")
dm=melt(dat,id.var=c("Clusters"))
p1 <- ggplot(dm, aes(variable, value, fill=variable)) + theme_bw() +
geom_histogram(stat="identity") + facet_grid(. ~ Clusters)
p2 <- ggplot(dm, aes(Clusters, value, fill=Clusters)) +
geom_histogram(stat="identity") + facet_grid(. ~ variable)
print(arrangeGrob(p1, p2, ncol=1))
You can adjust theme and use other visualizations (geom_boxplot, stat_ydensity) with different data.
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First of all, you can show us how your data looks like.
My answer probably would be ggplot.
You can (should) also try BoxPlotR (a web-tool for generation of box plots).