47 Supplementary Figure 20

47.1 Summary

This is the accessory documentation of Figure S20. The Figure can be recreated by running the R script plot_SF20.R:

cd $BASE_DIR

Rscript --vanilla R/fig/plot_SF20.R \
    2_analysis/GxP/50000/

47.2 Details of plot_SF20.R

In the following, the individual steps of the R script are documented. It is an executable R script that depends on the accessory R package GenomicOriginsScripts, as well as on the packages hypoimg, hypogen and patchwork

47.2.1 Config

The scripts start with a header that contains copy & paste templates to execute or debug the script:

#!/usr/bin/env Rscript
# run from terminal:
# Rscript --vanilla R/fig/plot_SF20.R \
#     2_analysis/GxP/50000/
# ===============================================================
# This script produces Suppl. Figure 20 of the study "Rapid radiation in a
# highly diverse marine environment" by Hench, Helmkampf, McMillan and Puebla
# ---------------------------------------------------------------
# ===============================================================
# args <- c('2_analysis/GxP/50000/')
# script_name <- "R/fig/plot_SF20.R"
args <- commandArgs(trailingOnly = FALSE)

The next section processes the input from the command line. It stores the arguments in the vector args. The needed R packages are loaded and the script name and the current working directory are stored inside variables (script_name, plot_comment). This information will later be written into the meta data of the figure to help us tracing back the scripts that created the figures in the future.

Then we drop all the imported information besides the arguments following the script name and print the information to the terminal.

# setup -----------------------
renv::activate()
library(GenomicOriginsScripts)
library(hypoimg)
library(hypogen)

cat('\n')
script_name <- args[5] %>%
  str_remove(.,'--file=')

plot_comment <- script_name %>%
  str_c('mother-script = ',getwd(),'/',.)

args <- process_input(script_name, args)

#> ── Script: R/fig/plot_SF20.R ────────────────────────────────────────────
#> Parameters read:
#> ★ 1: 2_analysis/GxP/50000/
#> ────────────────────────────────────────── /current/working/directory ──

The directory containing the PCA data is received and stored in a variable. Also the default color scheme is updated and the size of the hamlet ann.

# config -----------------------
gxp_path <- as.character(args[1])

# configure which gxp data to load
trait_tib  <- tibble(file = dir(gxp_path) %>% .[str_detect(.,"Bars|Peduncle|Snout")]) %>%
  mutate(prep = file) %>%
  separate(prep , into = c("trait", "model_type", "win", "step", "filetype", "zip"),
           sep = "\\.") %>%
  select(file, trait, model_type) %>%
  mutate(path = gxp_path)

# load gxp data
data <- pmap_dfr(trait_tib,get_gxp_both_models)

# compose final figure
p_done <- data %>%
  ggplot(aes(x = gpos, y = AVG_p_wald))+
  # add gray/white LGs background
  geom_hypo_LG()+
  # add gxp data points
  geom_point(color = plot_clr, size = .3)+
  # set axis layout
  scale_x_hypo_LG()+
  scale_fill_hypo_LG_bg()+
  # set axis titles
  labs(y = expression(G~x~P~(average~italic(p)[wald])))+
  # general plot structure separated by model type and trait
  facet_grid(trait+model_type ~ ., scales = "free_y")+
  # general plot layout
  theme_hypo()

Finally, we can export Figure S20.

# export final figure
hypo_save(filename = "figures/SF20.png",
       plot = p_done,
       width = 11,
       height = 7,
       dpi = 600,
       type = "cairo",
       comment = plot_comment)

system("convert figures/SF20.png figures/SF20.pdf")
system("rm figures/SF20.png")
create_metadata <- str_c("exiftool -overwrite_original -Description=\"", plot_comment, "\" figures/SF20.pdf")
system(create_metadata)