Display beta diversities in an all vs all grid.

Usage

bdiv_heatmap(
  biom,
  bdiv = "Bray-Curtis",
  weighted = TRUE,
  tree = NULL,
  tracks = NULL,
  grid = "devon",
  label = TRUE,
  label_size = NULL,
  rescale = "none",
  clust = "complete",
  trees = TRUE,
  asp = 1,
  tree_height = 10,
  track_height = 10,
  legend = "right",
  title = TRUE,
  xlab.angle = "auto",
  ...
)

Arguments

biom

An rbiom object, such as from as_rbiom(). Any value accepted by as_rbiom() can also be given here.

bdiv

Beta diversity distance algorithm(s) to use. Options are: "Bray-Curtis", "Manhattan", "Euclidean", "Jaccard", and "UniFrac". For "UniFrac", a phylogenetic tree must be present in biom or explicitly provided via tree=. Default: "Bray-Curtis"

Multiple/abbreviated values allowed.

weighted

Take relative abundances into account. When weighted=FALSE, only presence/absence is considered. Default: TRUE

Multiple values allowed.

tree

A phylo object representing the phylogenetic relationships of the taxa in biom. Only required when computing UniFrac distances. Default: biom$tree

tracks

A character vector of metadata fields to display as tracks at the top of the plot. Or, a list as expected by the tracks argument of plot_heatmap(). Default: NULL

grid

Color palette name, or a list with entries for label, colors, range, bins, na.color, and/or guide. See the Track Definitions section for details. Default: "devon"

label

Label the matrix rows and columns. You can supply a list or logical vector of length two to control row labels and column labels separately, for example label = c(rows = TRUE, cols = FALSE), or simply label = c(T, F). Other valid options are "rows", "cols", "both", "bottom", "right", and "none". Default: TRUE

label_size

The font size to use for the row and column labels. You can supply a numeric vector of length two to control row label sizes and column label sizes separately, for example c(rows = 20, cols = 8), or simply c(20, 8). Default: NULL, which computes: pmax(8, pmin(20, 100 / dim(mtx)))

rescale

Rescale rows or columns to all have a common min/max. Options: "none", "rows", or "cols". Default: "none"

clust

Clustering algorithm for reordering the rows and columns by similarity. You can supply a list or character vector of length two to control the row and column clustering separately, for example clust = c(rows = "complete", cols = NA), or simply clust = c("complete", NA). Options are:

FALSE or NA -: Disable reordering.
An hclust class object: E.g. from stats::hclust().
A method name -: "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median", or "centroid".

Default: "complete"

trees

Draw a dendrogram for rows (left) and columns (top). You can supply a list or logical vector of length two to control the row tree and column tree separately, for example trees = c(rows = T, cols = F), or simply trees = c(T, F). Other valid options are "rows", "cols", "both", "left", "top", and "none". Default: TRUE

asp

Aspect ratio (height/width) for entire grid. Default: 1 (square)

tree_height, track_height

The height of the dendrogram or annotation tracks as a percentage of the overall grid size. Use a numeric vector of length two to assign c(top, left) independently. Default: 10 (10% of the grid's height)

legend

Where to place the legend. Options are: "right" or "bottom". Default: "right"

title

Plot title. Set to TRUE for a default title, NULL for no title, or any character string. Default: TRUE

xlab.angle

Angle of the labels at the bottom of the plot. Options are "auto", '0', '30', and '90'. Default: "auto".

...

Additional arguments to pass on to ggplot2::theme(). For example, labs.subtitle = "Plot subtitle".

Value

A ggplot2 plot.
The computed data points and ggplot command are available as $data and $code, respectively.

Annotation Tracks

Metadata can be displayed as colored tracks above the heatmap. Common use cases are provided below, with more thorough documentation available at https://cmmr.github.io/rbiom .

## Categorical ----------------------------
tracks = "Body Site"
tracks = list('Body Site' = "bright")
tracks = list('Body Site' = c('Stool' = "blue", 'Saliva' = "green"))

## Numeric --------------------------------
tracks = "Age"
tracks = list('Age' = "reds")

## Multiple Tracks ------------------------
tracks = c("Body Site", "Age")
tracks = list('Body Site' = "bright", 'Age' = "reds")
tracks = list(
  'Body Site' = c('Stool' = "blue", 'Saliva' = "green"),
  'Age'       = list('colors' = "reds") )

The following entries in the track definitions are understood:

colors -: A pre-defined palette name or custom set of colors to map to.
range -: The c(min,max) to use for scale values.
label -: Label for this track. Defaults to the name of this list element.
side -: Options are "top" (default) or "left".
na.color -: The color to use for NA values.
bins -: Bin a gradient into this many bins/steps.
guide -: A list of arguments for guide_colorbar() or guide_legend().

All built-in color palettes are colorblind-friendly.

Categorical palette names: "okabe", "carto", "r4", "polychrome", "tol", "bright", "light", "muted", "vibrant", "tableau", "classic", "alphabet", "tableau20", "kelly", and "fishy".

Numeric palette names: "reds", "oranges", "greens", "purples", "grays", "acton", "bamako", "batlow", "bilbao", "buda", "davos", "devon", "grayC", "hawaii", "imola", "lajolla", "lapaz", "nuuk", "oslo", "tokyo", "turku", "bam", "berlin", "broc", "cork", "lisbon", "roma", "tofino", "vanimo", and "vik".

Examples

    library(rbiom)
    
    # Keep and rarefy the 10 most deeply sequenced samples.
    hmp10 <- rarefy(hmp50, n = 10)
    
    bdiv_heatmap(hmp10, tracks=c("Body Site", "Age"))

    
    bdiv_heatmap(hmp10, bdiv="uni", weighted=c(T,F), tracks="sex")