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Make Joyplots for multi value trait plantCV data

Source: R/pcvjoyplot.R
pcv.joyplot.Rd

Make Joyplots for multi value trait plantCV data

Usage

pcv.joyplot(
  df = NULL,
  index = NULL,
  group = NULL,
  y = NULL,
  id = NULL,
  bin = "label",
  freq = "value",
  trait = "trait",
  fillx = TRUE
)

Arguments

df

Data frame to use. Long or wide format is accepted.

index

If the data is long then this is a multi value trait as a character string that must be present in `trait`. If the data is wide then this is a string used to find column names to use from the wide data. In the wide case this should include the entire trait name (ie, "hue_frequencies" instead of "hue_freq").

group

A length 1 or 2 character vector. This is used for faceting the joyplot and identifying groups for testing. If this is length 1 then no faceting is done.

y

Optionally a variable to use on the y axis. This is useful when you have three variables to display. This argument will change faceting behavior to add an additional layer of faceting (single length group will be faceted, length 2 group will be faceted group1 ~ group2).

id

Optionally a variable to show the outline of different replicates. Note that ggridges::geom_density_ridges_gradient does not support transparency, so if fillx is TRUE then only the outer line will show individual IDs.

bin

Column containing histogram (multi value trait) bins. Defaults to "label".

freq

Column containing histogram counts. Defaults to "value"

trait

Column containing phenotype names. Defaults to "trait".

fillx

Logical, whether or not to use ggridges::geom_density_ridges_gradient. Default is T, if F then ggridges::geom_density_ridges is used instead, with arbitrary fill. Note that ggridges::geom_density_ridges_gradient may issue a message about deprecated ggplot2 features.

Value

Returns a ggplot.

Examples


library(extraDistr)
dists <- list(
  rmixnorm = list(mean = c(70, 150), sd = c(15, 5), alpha = c(0.3, 0.7)),
  rnorm = list(mean = 90, sd = 20),
  rlnorm = list(meanlog = log(40), sdlog = 0.5)
)
x_wide <- mvSim(
  dists = dists, n_samples = 5, counts = 1000,
  min_bin = 1, max_bin = 180, wide = TRUE
)
pcv.joyplot(x_wide, index = "sim", group = "group")

x_long <- mvSim(
  dists = dists, n_samples = 5, counts = 1000,
  min_bin = 1, max_bin = 180, wide = FALSE
)
x_long$trait <- "x"
p <- pcv.joyplot(x_long, bin = "variable", group = "group")
# we might want to display hues as their hue
p + ggplot2::scale_fill_gradientn(colors = scales::hue_pal(l = 65)(360))
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.

x_long$group2 <- "example"
pcv.joyplot(x_long, bin = "variable", y = "group", fillx = FALSE)