Some r code relating to heatmaps and OTU counts

ggheatmaps.R

prop_presence_absence <- function(otu.pa, groups) {
  # Creates a proportional presence-absence melted dataframe suitable for use in
  # ggplot heatmaps to show varying within-group proportions of species.
  # 
  # Args:
  #   otu.pa: Matrix of presence-absence data. Columns are samples, rows are 
  #           species.
  #   groups: Grouping data frame. A column named "SampleID" should be unique 
  #           list of sample identifiers that match the column names of otu.pa. 
  #           The other column, named "group", should correspond to the group 
  #           assignment of each sample.
  
  otu.melt = melt(otu.pa, varnames=c("otu", "SampleID"))
  otu.melt = merge(otu.melt, groups, by="SampleID")
  otu.cast = dcast(otu.melt, formula=otu~group, value.var="value", 
                  fun.aggregate=mean)
  otu.melt = melt(otu.cast)
  return(otu.melt)
}


ggheatmap <- function(otu_counts, ncolors=20, saturation_lim=0.8) {
  # Creates a heatmap from a melted otu count/abundance matrix. Assumes that the
  # x axis will correspond to the column named "variable" in the melted data frame,
  # and the y axis will be the "otu" column. The "value" column will be used for 
  # the tile values, and the color scale uses Kyle's saturated_rainbow function.
  colors = scale_fill_gradientn(colours=saturated_rainbow(ncolors, saturation_lim), 
                                na.value="white")
  p = ggplot(data=otu_counts, aes(x=variable, y=otu)) + 
    geom_tile(aes(fill=value)) + colors
  return(p)
}