braidReports (version 1.0.1)

geom_braid: BRAID Heatmaps

Description

Summarize and plot measurements of two inputs as a discrete raster or "stained-glass" plot

Usage

geom_braid(
  mapping = NULL,
  data = NULL,
  stat = "braid",
  position = "identity",
  ...,
  space = 1.5,
  trim = TRUE,
  shared = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
stat_braid(
  mapping = NULL,
  data = NULL,
  geom = "tile",
  position = "identity",
  ...,
  space = 1.5,
  trim = TRUE,
  shared = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_braid_glass(
  mapping = NULL,
  data = NULL,
  stat = "braid_glass",
  position = "identity",
  ...,
  space = 1.5,
  trim = TRUE,
  shared = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
stat_braid_glass(
  mapping = NULL,
  data = NULL,
  geom = "polygon",
  position = "identity",
  ...,
  space = 1.5,
  trim = TRUE,
  shared = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

stat

The statistical transformation to use on the data for this layer. When using a geom_*() function to construct a layer, the stat argument can be used the override the default coupling between geoms and stats. The stat argument accepts the following:

• A Stat ggproto subclass, for example StatCount.

• A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".

• For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

• The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

• A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

• For more information and other ways to specify the position, see the layer position documentation.

...

Additional parameters to be passed to ggplot2::geom_tile()

space

Parameter specifying the separation between marginal tiles and the main grid. Describes the distance from the center of the marginal tile to the center of the nearest main grid tile, divided by the width or height of the tile. If a single value is provided, it is used for both left-right and top-bottom margin tiles. If two values are provided, the first is used for left-right margin tiles and the second is used for top-bottom margin tiles.

trim

Should values that are finite in one dimension be dropped if their finite coordinates lie outside the bounds of the main grid?

shared

Should marginal offsets and trimming be calculated separately for each facet if plots are faceted. If FALSE, the default, each facet will have its own bounds and marginal offsets; if TRUE, offsets will be calculated for the full data and shared across all facets.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().

geom

The geometric object to use to display the data for this layer. When using a stat_*() function to construct a layer, the geom argument can be used to override the default coupling between stats and geoms. The geom argument accepts the following:

• A Geom ggproto subclass, for example GeomPoint.

• A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point".

• For more information and other ways to specify the geom, see the layer geom documentation.

Details

While the existing ggplot2 package includes several functions that are extremely effective and versatile for visualizing two-dimensional responses, including ggplot2::geom_raster(), ggplot2::geom_tile(), and ggplot2::geom_contour(), a number of considerations particular to combination data make these functions, as is, somewhat difficult to use. First, these functions are not designed for data in which pairs of x- and y-coordinates are duplicated; yet this is very common in experimental data. While such duplications can be handled prior to calling a visualization function, handling them automatically reduces the barrier to plotting.

A second, and much more challenging consideration, is that for many drug combination studies, drug concentrations are measured as a series of equal ratio dilutions; visualizing such doses is most intuitive on a logarithmic scale. But when inputs are scaled logarithmically, zeros become infinite and are automatically removed by nearly all ggplot2 functions. This makes it very difficult to plot measurements of drugs in isolation and in combination in the same plot. geom_braid addresses this by automatically offsetting any measurements whose transformed coordinates are infinite to margins within the plotted space, so that all values can be plotted together.

While geom_braid is suitable for most response surfaces, some surfaces feature measurements that are not arranged in a evenly spaced checkerboard. For such surfaces, geom_braid_glass produces a set of Voronoi polygons centered on the available transformed coordinates, creating what we call a "stained glass" plot. Marginal points are still represented by rectangles, but with width and height such that boundaries are equidistant between adjacent points.

stat_braid and stat_braid_glass are simply the corresponding stat_ functions for these two functions.

Examples

concentrations <- c(0,2^(-3:3))
surface <- data.frame(
	  concA = rep(rep(concentrations,each=length(concentrations)),each=3),
  concB = rep(rep(concentrations,times=length(concentrations)),each=3),
  replicate = rep(c(1,2,3),times=(length(concentrations)^2))
)
surface$actual <- evalBraidModel(
  surface$concA,
 surface$concB,
 c(1, 1, 3, 3, 2, 0, 100, 100, 100)
)
surface$measure <- surface$actual + rnorm(nrow(surface),sd=7)

ggplot(surface,aes(x=concA,y=concB))+
    geom_braid(aes(fill=measure))+
    scale_x_log10()+
    scale_y_log10()+
    scale_fill_distiller(palette="RdYlBu")+
    coord_equal()+
    labs(x="Drug A",y="Drug B",fill="Effect")

glassSurface <- surface
glassSurface$concA[glassSurface$replicate==2] <-
    glassSurface$concA[glassSurface$replicate==2]*1.25
glassSurface$concB[glassSurface$replicate==3] <-
    glassSurface$concB[glassSurface$replicate==3]*1.25
glassSurface$actual <- evalBraidModel(
    glassSurface$concA,
    glassSurface$concB,
    c(1, 1, 3, 3, -0.5, 0, 60, 100, 100)
)
glassSurface$measure <- glassSurface$actual+rnorm(nrow(glassSurface),sd=7)

ggplot(glassSurface,aes(x=concA,y=concB))+
    geom_braid_glass(aes(fill=measure))+
    scale_x_log10("Drug A")+
    scale_y_log10("Drug B")+
    scale_fill_distiller("Effect",palette="RdYlBu")+
    coord_equal()

glassSurface$tilewidth <- log10(2)*0.9
glassSurface$tilewidth[glassSurface$concA==0] <- log10(2)/2

glassSurface$tileheight <- log10(2)*0.9
glassSurface$tileheight[glassSurface$concB==0] <- log10(2)/2

ggplot(glassSurface,aes(x=concA,y=concB))+
    geom_braid_glass(aes(fill=measure,width=tilewidth,height=tileheight),space=2)+
    scale_x_log10("Drug A")+
    scale_y_log10("Drug B")+
    scale_fill_distiller("Effect",palette="RdYlBu")+
    coord_equal()