scale_x_logFC: Position scales for log fold change data

In ggpmisc: Miscellaneous Extensions to 'ggplot2'

Position scales for log fold change data

Description

Continuous scales for x and y aesthetics with defaults suitable for values expressed as log2 fold change in data and fold-change in tick labels. Supports tick labels and data expressed in any combination of fold-change, log2 fold-change and log10 fold-change. Supports addition of units to axis labels passed as argument to the name formal parameter.

Usage

scale_x_logFC(
  name = "Abundance of x%unit",
  breaks = NULL,
  labels = NULL,
  limits = symmetric_limits,
  oob = scales::squish,
  expand = expansion(mult = 0.05, add = 0),
  log.base.labels = FALSE,
  log.base.data = 2L,
  ...
)

scale_y_logFC(
  name = "Abundance of y%unit",
  breaks = NULL,
  labels = NULL,
  limits = symmetric_limits,
  oob = scales::squish,
  expand = expansion(mult = 0.05, add = 0),
  log.base.labels = FALSE,
  log.base.data = 2L,
  ...
)

Arguments

name	The name of the scale without units, used for the axis-label.
breaks	The positions of ticks or a function to generate them. Default varies depending on argument passed to log.base.labels. if supplied as a numeric vector they should be given using the data as passed to parameter data.
labels	The tick labels or a function to generate them from the tick positions. The default is function that uses the arguments passed to log.base.data and log.base.labels to generate suitable labels.
limits	limits One of: NULL to use the default scale range from ggplot2. A numeric vector of length two providing limits of the scale, using NA to refer to the existing minimum or maximum. A function that accepts the existing (automatic) limits and returns new limits. The default is function symmetric_limits() which keep 1 at the middle of the axis..
oob	Function that handles limits outside of the scale limits (out of bounds). The default squishes out-of-bounds values to the boundary.
expand	Vector of range expansion constants used to add some padding around the data, to ensure that they are placed some distance away from the axes. The default is to expand the scale by 15% on each end for log-fold-data, so as to leave space for counts annotations.
log.base.labels, log.base.data	integer or logical Base of logarithms used to express fold-change values in tick labels and in data. Use FALSE for no logarithm transformation.
...	other named arguments passed to scale_y_continuous.

Details

These scales only alter default arguments of scale_x_continuous() and scale_y_continuous(). Please, see documentation for scale_continuous for details. The name argument supports the use of "%unit" at the end of the string to automatically add a units string, otherwise user-supplied values for names, breaks, and labels work as usual. Tick labels are built based on the transformation already applied to the data (log2 by default) and a possibly different log transformation (default is fold-change with no transformation). The default for handling out of bounds values is to "squish" them to the extreme of the scale, which is different from the default used in 'ggplot2'.

See Also

Other scales for omics data: outcome2factor(), scale_colour_logFC(), scale_shape_outcome(), xy_outcomes2factor()

Examples

set.seed(12346)
my.df <- data.frame(x = rnorm(50, sd = 4), y = rnorm(50, sd = 4))
# we assume that both x and y values are expressed as log2 fold change

ggplot(my.df, aes(x, y)) +
  geom_point() +
  scale_x_logFC() +
  scale_y_logFC()

ggplot(my.df, aes(x, y)) +
  geom_point() +
  scale_x_logFC(labels = scales::trans_format(function(x) {log10(2^x)},
                         scales::math_format())) +
  scale_y_logFC(labels = scales::trans_format(function(x) {log10(2^x)},
                         scales::math_format()))

ggplot(my.df, aes(x, y)) +
  geom_point() +
  scale_x_logFC(log.base.labels = 2) +
  scale_y_logFC(log.base.labels = 2)

ggplot(my.df, aes(x, y)) +
  geom_point() +
  scale_x_logFC("A concentration%unit", log.base.labels = 10) +
  scale_y_logFC("B concentration%unit", log.base.labels = 10)

ggplot(my.df, aes(x, y)) +
  geom_point() +
  scale_x_logFC("A concentration%unit", breaks = NULL) +
  scale_y_logFC("B concentration%unit", breaks = NULL)

# taking into account that data are expressed as log2 FC.
ggplot(my.df, aes(x, y)) +
  geom_point() +
  scale_x_logFC("A concentration%unit", breaks = log2(c(1/100, 1, 100))) +
  scale_y_logFC("B concentration%unit", breaks = log2(c(1/100, 1, 100)))

ggplot(my.df, aes(x, y)) +
  geom_point() +
  scale_x_logFC(labels = scales::trans_format(function(x) {log10(2^x)},
                         scales::math_format())) +
  scale_y_logFC(labels = scales::trans_format(function(x) {log10(2^x)},
                         scales::math_format()))

# override "special" default arguments.
ggplot(my.df, aes(x, y)) +
  geom_point() +
  scale_x_logFC("A concentration",
                breaks = waiver(),
                labels = waiver()) +
  scale_y_logFC("B concentration",
                breaks = waiver(),
                labels = waiver())

ggplot(my.df, aes(x, y)) +
  geom_point() +
  scale_x_logFC() +
  scale_y_logFC() +
  geom_quadrant_lines() +
  stat_quadrant_counts(size = 3.5)

ggpmisc documentation built on Nov. 16, 2023, 5:10 p.m.