ggiraph functionality in volcano and PCA plots

[OlaCaster]

Note: This is a draft only. This is a POC to demonstrate how we could add plot interactivity (tooltip, hover, and select) using ggiraph.

Documentation is only updated to a bare minimum (i.e., new arguments are described). No tests have been added.

Some example code (note that you obviously need ggiraph installed - if not, you will be prompted):

# Volcano plot
library(dplyr)
npx_df <- npx_data1 %>% filter(!grepl('control',SampleID, ignore.case = TRUE))
ttest_results <- olink_ttest(df=npx_df,
                             variable = 'Treatment',
                             alternative = 'two.sided') %>%
  mutate(tool = paste0("OlinkID: ", OlinkID, "\nAssay: ", Assay, "\nUniProt: ", UniProt))
ggiraph::girafe(ggobj = olink_volcano_plot(ttest_results, tooltip_variable = "tool", data_id_variable = "OlinkID"))

# Single PCA
# Tooltip per Sample, hover effect per Subject
library(dplyr)
npx_data <- npx_data1 %>%
  mutate(SampleID = paste(SampleID, "_", Index, sep = ""))
ggiraph::girafe(ggobj = olink_pca_plot(df=npx_data %>% dplyr::mutate(tool=paste0("Subject: ",Subject,"\nSampleID: ",SampleID)),
                                       color_g = "QC_Warning", tooltip_variable="tool", data_id_variable = "Subject", quiet=TRUE)[[1L]])

# Multiple linked PCAs
# Tooltip and hover per Sample ID - the two plots are linked by data_id
library(dplyr)
library(patchwork)
npx_data <- npx_data1 %>%
  mutate(SampleID = paste(SampleID, "_", Index, sep = ""))
g <- olink_pca_plot(df=npx_data, color_g = "QC_Warning", tooltip_variable="SampleID", data_id_variable = "SampleID",
                    quiet=TRUE, byPanel=TRUE)
ggiraph::girafe(code = print(g[[1L]] + g[[2L]]), width_svg=10,
                options=list(
                  ggiraph::opts_tooltip(opacity=0.7),
                  ggiraph::opts_hover(    css="fill:darkgreen; stroke:darkgreen; r:4pt;"),
                  ggiraph::opts_hover_inv(css="opacity:0.3;")
                ))