Create a barplot for publication - ggplot.R

barplot for publication - ggplot.R

# ==========================================================================
# Barplot with CI/error bars for publication - ggplot
# see more at: http://www.cookbook-r.com/Graphs/Plotting_means_and_error_bars_(ggplot2)/
# ==========================================================================

library(ggplot2)

# ==================================
# create some data
# ==================================
set.seed(1)
DF <- data.frame(Treatment = rep(c("control", "T1", "T2", "T1&2"), times=2),
                 Species   = rep(c("Sp1", "Sp2"), each=4),
                 means     = c(rnorm(n=4, mean=5), 
                               rnorm(n=4, mean=6)))

# Note that this is fake data, this is not the way to statistically compute CI-s or SE-s
DF$lower.CI  <- DF$means - rnorm(n=8, mean=.5, sd=.1)
DF$upper.CI  <- DF$means + rnorm(n=8, mean=.5, sd=.1)

# ==================================
# Plot barplot with ggplot
# ==================================
ggplot(data = DF, 
       aes(x    = Treatment, 
           y    = means, 
           fill = Species)) +
    
    # add the bars (means)
    geom_bar(stat="identity", position=position_dodge()) +
    # fill the bars manually
    scale_fill_manual(name   = 'Species:',
                      breaks = c("Sp1", "Sp2"),
                      values = c("Sp1" = "gray70", 
                                 "Sp2" = "gray40"),
                      labels = c("Species 1", "Species 2")) + 
    
    # plot CIs (add a point shape as well)
    geom_errorbar(aes(ymax=upper.CI, ymin=lower.CI), size=.4, width=.15, linetype="solid", position=position_dodge(.9)) +
    geom_point(position=position_dodge(width=.9), shape="-", show.legend = FALSE) +
    
    # set order of discrete values on OX axes & adjust the distance (gap) from OY axes
    scale_x_discrete(limits = c("control", "T1", "T2", "T1&2"),
                     labels = c("control", "Treatment 1", "Treatment 2", "Treatment 1 \n and Treatment 2"),
                     expand = c(0, .5)) +
    # set range on OY axes and adjust the distance (gap) from OX axes
    scale_y_continuous(limits = c(0, 10), expand = c(0, 0)) +
    
    # Final adjustments:
    # set axis labels
    labs(x = "", 
         y = "Means") +
    theme_bw() + # eliminate default background 
    theme(panel.grid.major = element_blank(), # eliminate major grids
          panel.grid.minor = element_blank(), # eliminate minor grids
          # set font family for all text within the plot ("serif" should work as "Times New Roman")
          # note that this can be overridden with other adjustment functions below
          text = element_text(family="serif"),
          # adjust X-axis title
          axis.title.x = element_text(size = 10, face = "bold"),
          # adjust X-axis labels
          axis.text.x = element_text(size = 10, face = "bold", color="black"),
          # adjust Y-axis title
          axis.title.y = element_text(size = 10, face = "bold"),
          # adjust legend title appearance
          legend.title = element_text(size = 8, face = "bold"),
          # adjust legend label appearance
          legend.text = element_text(size = 8, face = "italic"),
          # change spacing between legend items
          legend.key.height = unit(4, "mm"),
          # don't draw legend box (check element_rect() for borders and backgrounds)
          legend.background = element_blank(),
          # Put upper-left corner of legend box in upper-left corner of graph
          # Note that the numeric position in legend.position below is relative to the entire area, 
          # including titles and labels, not just the plotting area
          legend.justification = c(0,1),
          legend.position = c(0,1))

# save as pdf
ggsave("barplot with CI bars - ggplot.pdf", width=12, height=8, units="cm")
# save as png
ggsave("barplot with CI bars - ggplot.png", width=12, height=8, units="cm", dpi=300)