Title: Implementation of the Q-Q Boxplot
Version: 0.3.0
Description: A system to implement the Q-Q boxplot. It is implemented as an extension to 'ggplot2'. The Q-Q boxplot is an amalgam of the boxplot and the Q-Q plot and allows the user to rapidly examine summary statistics and tail behavior for multiple distributions in the same pane. As an extension of the 'ggplot2' implementation of the boxplot, possible modifications to the boxplot extend to the Q-Q boxplot.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.1
Imports: ggplot2, grid
Depends: R (≥ 3.3)
Suggests: knitr, rmarkdown, dplyr, gridExtra, testthat (≥ 3.0.0), vdiffr (≥ 0.3.3), scales
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2022-11-20 03:17:28 UTC; jsr6q
Author: Jordan Rodu [aut, cre]
Maintainer: Jordan Rodu <jordan.rodu@gmail.com>
Repository: CRAN
Date/Publication: 2022-11-20 03:30:02 UTC

Simulated normal dataset with mean=5 and variance=1

Description

A dataset that contains simulated data to reproduce a figure in our manuscript

Usage

comparison_dataset

Format

A vector

Source

simulations

Log expression data for select genes

Description

A dataset that contains log expression data for randomly selected genes for two patients, one with autism and one control.

Usage

expression_data

Format

A data frame with 1200 rows and 3 variables:

gene

gene identifier (not meaningful)

specimen

autism or control

log_count

the logged gene expression count

...

Source

https://www.ebi.ac.uk/gxa/experiments/E-GEOD-30573/Results

A modification of the boxplot with information about the tails

Description

A modification of the boxplot with information about the tails

Usage

geom_qqboxplot(
  mapping = NULL,
  data = NULL,
  stat = "qqboxplot",
  position = "dodge2",
  ...,
  outlier.colour = NULL,
  outlier.color = NULL,
  outlier.fill = NULL,
  outlier.shape = 19,
  outlier.size = 1.5,
  outlier.stroke = 0.5,
  outlier.alpha = NULL,
  notch = FALSE,
  notchwidth = 0.5,
  varwidth = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes() or 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

specifies the stat function to use

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

outlier.colour, outlier.color, outlier.fill, outlier.shape, outlier.size, outlier.stroke, outlier.alpha

Default aesthetics for outliers. Set to NULL to inherit from the aesthetics used for the box.

In the unlikely event you specify both US and UK spellings of colour, the US spelling will take precedence.

Sometimes it can be useful to hide the outliers, for example when overlaying the raw data points on top of the boxplot. Hiding the outliers can be achieved by setting outlier.shape = NA. Importantly, this does not remove the outliers, it only hides them, so the range calculated for the y-axis will be the same with outliers shown and outliers hidden.

notch

If FALSE (default) make a standard box plot. If TRUE, make a notched box plot. Notches are used to compare groups; if the notches of two boxes do not overlap, this suggests that the medians are significantly different.

notchwidth

For a notched box plot, width of the notch relative to the body (defaults to notchwidth = 0.5).

varwidth

If FALSE (default) make a standard box plot. If TRUE, boxes are drawn with widths proportional to the square-roots of the number of observations in the groups (possibly weighted, using the weight aesthetic).

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().

Value

Returns an object of class GeomQqboxplot, (inherits from Geom, ggproto), that renders the data for the Q-Q boxplot.

Description

The Q-Q boxplot inherits its summary statistics from the boxplot. See geom_boxplot() for details. The Q-Q boxplot differs from the boxplot by using more informative whiskers than the regular boxplot.

The vertical position of the whiskers can be interpreted as it is in the boxplot, and the maximal vertical value is chosen as it is done in the regular boxplot. The horizontal positioning of the whiskers indicates the deviation of the data set of interest from some reference data set (specified as either a theoretical distribution or an actual data set). Taking the central vertical axis of the boxplot as being zero, deviations to the right indicate that those values are larger than the corresponding data points in the reference data set, where two data points correspond if their quantiles match. Deviations to the left indicate that the values are smaller than their corresponding data points. Consider a situation where your data set has fatter tails than the normal distribution. When the reference distribution is the normal distribution, then the whiskers below the box will be left of the central axis (the left tail values are smaller than they ought to be) and the whiskers above the box will be right of the central axis (the right tail values are larger than the ought to be).

In order to compare the data set of interest to the reference data set, they must be on the same scale. The Q-Q boxplot uses Tukey's g-h distribution to determine the appropriate scaling factor.

Much of the code here is a modification of the geom_boxplot() code.

Examples

p <- ggplot2::ggplot(simulated_data, ggplot2::aes(factor(group,
levels=c("normal, mean=2", "t distribution, df=32", "t distribution, df=16",
"t distribution, df=8", "t distribution, df=4")), y=y))
p + geom_qqboxplot()
p + geom_qqboxplot(reference_dist = "norm")


p + geom_qqboxplot(compdata = comparison_dataset)


# geom_qqboxplot inherits all arguments from geom_boxplot, e.g.:
p + geom_qqboxplot(notch = TRUE)
p + geom_qqboxplot(varwidth=TRUE)
p + geom_qqboxplot(ggplot2::aes(color = group)) + ggplot2::guides(color=FALSE)

World Bank indicator data for Labor Force participation rates

Description

A dataset that contains participation rates (%) for ages 15-24, separated by gender, and measured in the years 2008, 2012, and 2017

Usage

indicators

Format

A data frame with 612 rows and 7 variables:

Country Name

name of country

Country Code

unique country identifier (string)

Series Name

Specifies male/female

Series Code

unique identifier for series

year

year for data

indicator

participation rate in percents

log_indicator

the log of the participation rate

...

Source

https://www.worldbank.org/en/home

Neuron population firing data

Description

A dataset that contains populations of neurons from CA1 and LM and their firing rates for three situations: base firing rate, dot motion, and drifting gradient. Each row represents a neuron

Usage

population_brain_data

Format

A data frame with 13731 rows and 3 variables:

ecephys_structure_acronym

acronym for population location

fr_type

situation under which firing rate was recorded

rate

the firing rate

...

Source

https://allensdk.readthedocs.io/en/latest/visual_coding_neuropixels.html

qqboxplot package

Description

Create qq-boxplots

Simulated t-distributions to show use of q-q boxplots

Description

A dataset that contains simulated data to reproduce the simulated data figures used in our manuscript

Usage

simulated_data

Format

A data frame with 4500 rows and 2 variables:

y

a value simulated from a distribution

group

a string specifying the distribution from which the y value is drawn

...

Source

simulations

Neuron spiking data for neural tuning orientation

Description

A dataset that contains the number of spikes for neurons across several possible orientations of a grating

Usage

spike_data

Format

A data frame with 12800 rows and 5 variables:

orientation

1 to 8, specifies the orientation of the grating

nspikes

number of spikes for a single trial of 1.28 seconds for a particular orientation

region

region of the brain where the neuron is located

...

Source

https://CRCNS.org

Compute values for the Q-Q Boxplot

Description

Compute values for the Q-Q Boxplot

Usage

stat_qqboxplot(
  mapping = NULL,
  data = NULL,
  geom = "qqboxplot",
  position = "dodge2",
  ...,
  coef = 1.5,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  reference_dist = "norm",
  confidence_level = 0.95,
  numboots = 500,
  qtype = 7,
  compdata = NULL
)

Arguments

mapping

Set of aesthetic mappings created by aes() or 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)).

geom

specifies the geom function to use

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

coef

Length of the whiskers as multiple of IQR. Defaults to 1.5.

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().

reference_dist

Specifies theoretical reference distribution.

confidence_level

Sets confidence level for deviation whisker confidence bands

numboots

specifies the number of bootstrap draws for bootstrapped CIs needed only if compdata is not NULL

qtype

an integer between 1 and 9 indicating which one of the quantile algorithms to use.

compdata

specifies a data set to use as the reference distribution. If compdata is not NULL, the argument reference_dist will be ignored.

Value

Returns an object of class StatQqboxplot, (inherits from Geom, ggproto), that helps to render the data for geom_qqboxplot().

Computed variables

stat_qqboxplot() provides the following variables, some of which depend on the orientation:

width

width of boxplot

ymin or xmin

lower whisker = smallest observation greater than or equal to lower hinge - 1.5 * IQR

lower or xlower

lower hinge, 25% quantile

notchlower

lower edge of notch = median - 1.58 * IQR / sqrt(n)

middle or xmiddle

median, 50% quantile

notchupper

upper edge of notch = median + 1.58 * IQR / sqrt(n)

upper or xupper

upper hinge, 75% quantile

ymax or xmax

upper whisker = largest observation less than or equal to upper hinge + 1.5 * IQR