An ordered dot plot with error bars. Demonstrates creating summarized data (e.g. means), ordering by second variable, error bars on dot plots. Based on the bar chart example at http://martinsbioblogg.wordpress.com/2014/03/19/using-r-barplot-with-ggplot2/

ordered_dotplot_errorbars.R

#' Example Cleveland-style dot plot.
#' Two variables plotted on an facet plot.
#' Ordering of the data in the first facet.
#' Error bars plotted with each dot.

library(ggplot2)
library(reshape2)
library(plyr)

#' Create some data for the demonstration
n <- 10
group <- rep(1:4, n)
mass.means <- c(10, 20, 15, 30)
mass.sigma <- 4
score.means <- c(5, 5, 7, 4)
score.sigma <- 3
mass <- as.vector(model.matrix(~0+factor(group)) %*% mass.means) +
  rnorm(n*4, 0, mass.sigma)
score <- as.vector(model.matrix(~0+factor(group)) %*% score.means) +
  rnorm(n*4, 0, score.sigma)
data <- data.frame(id = 1:(n*4), group, mass, score)

#' Reorder the data on "group," sorted by "mass"
data <- transform(data, group = reorder(group, mass))

#' Change from wide to tall format for ggplot2
melted <- melt(data, id.vars=c("id", "group"))

#' Calculate means and standard deviations
means <- ddply(melted, c("group", "variable"), summarise,
               mean=mean(value))
means.sem <- ddply(melted, c("group", "variable"), summarise,
                   mean=mean(value), sem=sd(value)/sqrt(length(value)))

#' Create the data frame that we will use for the error bars.
means.sem <- transform(means.sem, lower=mean-sem, upper=mean+sem)

#' Note that the order of geoms matters: plot geom_errorbarh first so that the points
#' overlay the error bars. Reversing these plots the error bars over the dots, resulting
#' in a visible gray line through each dot.
#' Note that each geom can work with a different data set than the default passed to
#' ggplot().
means.barplot <- ggplot(data = means, aes(x = mean, y = group)) + 
  geom_errorbarh(data=means.sem, aes(xmax=upper, xmin=lower), height = 0.15, colour = "grey50") + 
  geom_point(size = 5) + 
  facet_grid(facets= . ~ variable, scales="free_x") +
  theme(text = element_text(size = 18))

#' Plot to standard graphics window.
means.barplot