geom_compare {plutor}

add p value and fold change on a plot

Description

add p value and fold change on a plot

Usage

geom_compare(
  mapping = NULL,
  data = NULL,
  stat = "compare",
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  lab_pos = NULL,
  step_increase = 0.1,
  tip_length = 0.02,
  lineend = "round",
  cp_label = c("psymbol"),
  ns_lineheight_just = 0.2,
  ignore_ns = FALSE,
  fc_method = NULL,
  comparisons = NULL,
  paired = FALSE,
  alternative = "two.sided",
  test_method = "wilcoxon",
  ns_symbol = "NS",
  cp_ref = NULL,
  cp_inline = FALSE,
  brackets_widen = 0,
  fc_digits = 2,
  cp_result = NULL,
  cp_manual = NULL
)

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, either as a ggproto Geom subclass or as a string naming the stat stripped of the stat_ prefix (e.g. "count" rather than "stat_count")

position

Position adjustment, either as a string naming the adjustment (e.g. "jitter" to use position_jitter), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.

...

Other arguments passed on to ggplot2::geom_segment().

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().

lab_pos

position of the label brackets

step_increase

the increase height for next bracket, a ratio according to the whole panel height

tip_length

the length for tips at the ends of the brackets, a ratio according to the whole panel height

lineend

Line end style (round, butt, square).

cp_label

which values will be add on the plot, a character vector with some of ⁠psymbol, p, right_deno_fc, left_deno_fc⁠ in it. If comparisons is assigned, you can also include ⁠fc1, fc2⁠

ns_lineheight_just

if show psymbol in the label, justify the NS labels to make the lineheights look balanced

ignore_ns

if TRUE will ignore all label items if p >= 0.05, or you can assign a character vector like cp_label to ignore some items of the label

fc_method

fold change method, default is mean. If you use log10 or log2 axis, default is geom_mean.

comparisons

a list of two-element vector, to assign the comparisons should be performed

paired

paired test or not, FALSE as default. If TRUE, you should use mapping=aes(paired_by=col) to indicate pairs by an extra column

alternative

one of ⁠two.sided, greater, less⁠

test_method

wilcoxon as default, one of ⁠wilcoxon, t⁠

ns_symbol

the symbol of non-significant, NS as default

cp_ref

reference item, the others will be compared with it

cp_inline

draw in line or not, default is FALSE

brackets_widen

widen the brackets, can be a negative value

fc_digits

fold change digits

cp_result

comparation result tibble

cp_manual

manual comparisons table, please refer to extract_compare()

Value

ggplot object