Plot relative protein abundance as a function of rank by abundance

Usage

plot_abundance_vs_percent(
  percInfo,
  cfg_config,
  top_N = 10,
  factors = TRUE,
  colors = c(`^REV_` = "red", `^CON_` = "orange"),
  columnAb = "abundance_percent",
  group = "BB",
  alpha = 1,
  logY = TRUE
)

Arguments

percInfo: data frame with percentage abundance info
cfg_config: AnalysisConfiguration object
top_N: number of top proteins to label
factors: if TRUE facet by factors
colors: named vector of colors for special proteins
columnAb: column name for abundance values
group: crosstalk group identifier
alpha: point transparency
logY: if TRUE use log10 y-axis

Value

ggplot2

Examples


library(prolfqua)
istar <- prolfqua::prolfqua_data('data_ionstar')$filtered()
#> Column added : nr_peptide_Id_IN_protein_Id
data <- istar$data |> dplyr::filter(protein_Id %in% sample(protein_Id, 100))
lfqdata <- prolfqua::LFQData$new(data, istar$config)
sr <- lfqdata$get_Summariser()
undebug(plot_abundance_vs_percent)
#> Warning: argument is not being debugged
plot_abundance_vs_percent(sr$percentage_abundance(),
 lfqdata$get_config(),
 top_N = 6, factors = FALSE, logY = TRUE)


pd <- plot_abundance_vs_percent(
  sr$percentage_abundance(),
  lfqdata$get_config(), top_N = NULL, factors = FALSE)
#> creating shared data with key :  ~ protein_Id
plot_abundance_vs_percent(
  sr$percentage_abundance(),
  lfqdata$get_config(), top_N = 4, factors = TRUE)
#> Warning: Removed 208 rows containing missing values or values outside the scale range
#> (`geom_point()`).

plot_abundance_vs_percent(
  sr$percentage_abundance(),
  lfqdata$get_config(), top_N = NULL, factors = TRUE)
#> creating shared data with key :  ~ protein_Id
#> Warning: Removed 208 rows containing missing values or values outside the scale range
#> (`geom_point()`).