Heatmap with ggplot2

Basic heatmap function with ggplot2. I allows either to sort the samples according to a user defined variable, or to do a hierarchichal clustering, using uses ggdendro and grid to plot it

heatgg(...)

# S3 method for default
heatgg(Tab, Map, order.samples.by = NULL, facet = NULL,
  sample.id.var = "SAMPLEID", col.name = "Taxon",
  value.name = "Abundance", trans = "log", guide = "colourbar",
  gradientn.colours = c("white", "#67001F"), facet.scales = "free",
  cluster = FALSE, distfun = dist)

# S3 method for Dataset
heatgg(Dat, order.samples.by = NULL, facet = NULL,
  sample.id.var = "SAMPLEID", col.name = "Taxon",
  value.name = "Abundance", trans = "log", guide = "colourbar",
  gradientn.colours = c("white", "#67001F"), facet.scales = "free",
  cluster = FALSE, distfun = dist)

Arguments

Tab	A numeric matrix with samples as columns and taxons as rows.
Map	A data.frame where the row names correspond to the column names in Tab, matching metadata to each sample.
order.samples.by	If passed, it must be a character variable with the name of a variable in Map (or in the Map attribute of the Dataset object). Samples will be ordered according to this variable.
facet	A faccetting formula expression. If passed, samples wll be arrranged in panels accroding to facet_grid. The variable names should mathc those in the Map object.
sample.id.var	This is the name the sample axis will have in the heatmap.
col.name	The name the x-axis will have in the heatmap.
value.name	The name that will be on the legend indicating the meaning of the color scale.
trans	Transformation to apply to the data during plotting. Ay continuous tranformation supported by ggplot2 can be used. Normally "log10" or "sqrt"
guide	Type of legend to use. This will be passed to the guide option of scale_fill_gradientn. Can be a string like "colourbar" or a function like guide_colourbar
gradientn.colours	Colour range to use in the heatmap.
facet.scales	Argument to pass to the scales option of facet_grid. Only used if option facet is not NULL.
cluster	Logical. Indicates wheather to perform 2 dimensional hierarchichal clustering or not.
distfun	Distance function to use in the hierarchichal clustering. Only relevant if cluster equeals TRUE.
Dat	A Dataset object.

Value

If cluster is FALSE it will return a ggplot2 object that can be furhter manipulated and plotted.

If cluster is TRUE it will return a list of class heatggclus that contains the heatmap tiles and each of the dendogram plots separately. There is print method for this class that will automatically generate the plot visualization

Details

Currently, it supports only 2d clustering, and it does not support the clustering or just samples or taxa.

The faceting and ordering options are only available for samples and when cluster is FALSE.

References

A lot of code and ideas was borrowed from these places:

https://github.com/chr1swallace/random-functions/blob/master/R/ggplot-heatmap.R http://stackoverflow.com/questions/6673162/reproducing-lattice-dendrogram-graph-with-ggplot2 http://stackoverflow.com/questions/12041042/how-to-plot-just-the-legends-in-ggplot2

Examples

data(Rhizo)
data(Rhizo.map)
data(Rhizo.tax)
Dat <- create_dataset(Rhizo,Rhizo.map,Rhizo.tax)
heatgg(Tab = Dat$Tab, Map = Dat$Map, order.samples.by = "fraction")
#> Warning: Transformation introduced infinite values in discrete y-axis
heatgg(Tab = Dat$Tab, Map = Dat$Map, facet = fraction ~ .,
       order.samples.by = "accession")
#> Warning: Transformation introduced infinite values in discrete y-axis
heatgg(Tab = Dat$Tab, Map = Dat$Map, facet = fraction + accession ~ .)
#> Warning: Transformation introduced infinite values in discrete y-axis
heatgg(Tab = Dat$Tab, Map = Dat$Map, facet = fraction + accession ~ .,
       gradientn.colours = c("white", "black"))
#> Warning: Transformation introduced infinite values in discrete y-axis
p1 <- heatgg(Tab = Dat$Tab, Map = Dat$Map,
             gradientn.colours = c("white","black"),cluster = TRUE)

heatgg(Dat = Dat, order.samples.by = "fraction")
#> Warning: Transformation introduced infinite values in discrete y-axis
heatgg(Dat = Dat, facet = fraction ~ ., order.samples.by = "accession")
#> Warning: Transformation introduced infinite values in discrete y-axis
heatgg(Dat = Dat, facet = fraction + accession ~ .,)
#> Warning: Transformation introduced infinite values in discrete y-axis
heatgg(Dat = Dat, facet = fraction + accession ~ .,
       gradientn.colours = c("white", "black"))
#> Warning: Transformation introduced infinite values in discrete y-axis
p1 <- heatgg(Dat = Dat, gradientn.colours = c("white","black"),
             cluster = TRUE)