Plot Group-wise Dumbell Plots

Usage

groupwise_dumbell(
  data,
  group,
  trait,
  genotype,
  subset = c("facet", "list", "none"),
  diff.sort = c("none", "ascending", "descending"),
  segment = TRUE,
  segment.size = 3,
  segment.colour = "gray",
  segment.alpha = 0.5,
  point.size = 3,
  point.alpha = 0.8,
  error.bar = TRUE,
  error.bar.width = 0.1,
  ncol = NULL,
  nrow = NULL
)

Arguments

data: The data as a data frame object. The data frame should possess columns specifying the group and trait.
group: Name of column specifying the group as a character string.
trait: Name of column specifying the trait as a character string.
genotype: Name of column specifying the genotype as a character string.
subset: The method for subsetting the plots according to the argument "group". Either "facet" for getting an plot using faceting in ggplot2 or "list" for getting a list of plots.
diff.sort: The order for sorting the genotypes for plotting. Either "ascending", "descending" or "none".
segment: logical. If TRUE, the dumbell segment is plotted. Default is TRUE.
segment.size: The size of the dumbell segment.
segment.colour: The colour of the dumbell segment.
segment.alpha: Alpha transparency for the dumbell segment.
point.size: The size of the points.
point.alpha: Alpha transparency for the points.
error.bar: logical. If TRUE, the error bars depicting standard errors are plotted. Default is TRUE.
error.bar.width: The width of the error bars.
ncol: Number of columns when subset = "facet".
nrow: Number of rows when subset = "facet".

Value

The group-wise dumbell plot as a ggplot2 plot grob or as a list of ggplot2 plot grobs.

Examples

library(agridat)
library(ggplot2)
library(patchwork)

soydata <- australia.soybean
# soydata[soydata$loc == "Nambour", ]$lodging <- NA

checks <- c("G01", "G05")

checkdata <- soydata[soydata$gen %in% checks, ]

clrs <- c("#B2182B", "#2166AC", "#009E53", "#E69F00")
clrs_dark <- colorspace::darken(clrs, amount = 0.2)

# Group-wise dumbell plot with error bar
outg_dumbell1 <-
  groupwise_dumbell(data = checkdata, group = "loc",
                    trait = "lodging", genotype = "gen",
                    subset = "none", diff.sort = "descending")
outg_dumbell1


outg_dumbell1 +
  scale_colour_manual(values = clrs)


# Group-wise dumbell plot without error bar
outg_dumbell2 <-
  groupwise_dumbell(data = checkdata, group = "loc",
                    trait = "lodging", genotype = "gen",
                    subset = "none", diff.sort = "descending",
                    error.bar = FALSE)
outg_dumbell2


outg_dumbell2 +
  scale_colour_manual(values = clrs)


# Group-wise points with error bar as facets
outg_facet <-
  groupwise_dumbell(data = checkdata, group = "loc",
                    trait = "lodging", genotype = "gen",
                    subset = "facet")
outg_facet


outg_facet +
  scale_colour_manual(values = clrs)


# Group-wise points with error bar as list
outg_list <-
  groupwise_dumbell(data = checkdata, group = "loc",
                    trait = "lodging", genotype = "gen",
                    subset = "list")

wrap_plots(outg_list, nrow = 2, guides = "collect")


outg_list <-
  lapply(seq_along(outg_list), function(i) {
    outg_list[[i]] +
      scale_colour_manual(values = clrs[i])
  })
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.

wrap_plots(outg_list, nrow = 2, guides = "collect")