gg_pval_hist: Create p-value histogram
In milanmlft/MMmotley: A motley collection of R functions for data analysis

Description Usage Arguments Details Value Examples

View source: R/gg-pval-hist.R

Use ggplot2::geom_histogram() to create a histogram of p-values but with better binwidths and axis limits.

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gg_pval_hist(p_values, binwidth = 0.05)

geom_pval_hist(mapping = NULL, ..., binwidth = 0.05)

`p_values`	Vector of p-values.
`binwidth`	Binwidth of the histogram. A sensible choice is to use the significance cut-off so that the height of the first bar corresponds to the number of significant cases. Default: 0.05.
`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.
`...`	Arguments passed on to `ggplot2::geom_histogram` `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)`). `position` Position adjustment, either as a string, or the result of a call to a position adjustment function. `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()`. `bins` Number of bins. Overridden by `binwidth`. Defaults to 30. `orientation` The orientation of the layer. The default (`NA`) automatically determines the orientation from the aesthetic mapping. In the rare event that this fails it can be given explicitly by setting `orientation` to either `"x"` or `"y"`. See the Orientation section for more detail. `stat` Use to override the default connection between `geom_histogram()`/`geom_freqpoly()` and `stat_bin()`.

By default, ggplot2::geom_histogram() centers the first and last bins of the histogram on the x-axis lower and upper limits, respectively. In case of p-values, which lie in the interval [0, 1], it makes more sense to set the boundaries of the first and last bins at 0 and 1. The binwidths are also set at 0.05, commonly used as a cut-off for significance, so that the height of the first bar represents the number of p-values lying between 0 and 0.05, i.e. the number of cases that would be deemed significant.

A ggplot object.

pvals <- runif(n = 1000, min = 0, max = 1)
gg_pval_hist(pvals)

## Using a data.frame in combination with `ggplot`
library(ggplot2)
df <- data.frame(pvalue = runif(1000))
ggplot(df, aes(pvalue)) + geom_pval_hist()