Plot normalized values

plot_normalization() is a GGplot2 implementation for plotting the normalization effects visualized as a box plot.

Usage

plot_normalization(data = NULL, ...)

Arguments

data

tidyproteomics data object

...

passthrough for ggsave see plotting

Value

a (tidyproteomics data-object | ggplot-object)

Examples

library(dplyr, warn.conflicts = FALSE)
library(tidyproteomics)

# subset for fast execution
hela_proteins <- hela_proteins %>% subset(description %like% "Ribosome")
#> 
#> ℹ Subsetting data: description %like% Ribosome
#> ✔ Subsetting data: description %like% Ribosome ... done
#> 

hela_proteins %>%
  normalize(.method = c("scaled", "median", "linear", "limma", "loess")) %>%
  plot_normalization()
#> ℹ Normalizing quantitative data
#> ℹ ... using scaled shift
#> ✔ ... using scaled shift [14ms]
#> 
#> ℹ ... using median shift
#> ✔ ... using median shift [14ms]
#> 
#> ℹ ... using linear regression
#> ✔ ... using linear regression [24ms]
#> 
#> ℹ ... using limma regression
#> ✔ ... using limma regression [18ms]
#> 
#> ℹ ... using loess regression
#> ✔ ... using loess regression [24ms]
#> 
#> ℹ Selecting best normalization method
#> ✔ Selecting best normalization method ... done
#> 
#> ℹ  ... selected loess
#> Warning: Removed 48 rows containing non-finite outside the scale range
#> (`stat_boxplot()`).