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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)
hela_proteins %>%
  normalize(.method = c("scaled", "median", "linear", "limma", "loess")) %>%
  plot_normalization()
#>  Normalizing quantitative data
#>  ... using scaled shift
#>  ... using scaled shift [240ms]
#> 
#>  ... using median shift
#>  ... using median shift [136ms]
#> 
#>  ... using linear regression
#>  ... using linear regression [203ms]
#> 
#>  ... using limma regression
#>  ... using limma regression [368ms]
#> 
#>  ... using loess regression
#>  ... using loess regression [1.2s]
#> 
#>  Selecting best normalization method
#>  Selecting best normalization method ... done
#> 
#>   ... selected loess
#> Warning: Removed 73038 rows containing non-finite outside the scale range
#> (`stat_boxplot()`).