Plots the coefficient of variation for different replicates.

This function plots the coefficient of variation within replicates for a given value. If decoys are present these are removed before plotting.

plot_variation(
  data,
  column.values = "Intensity",
  comparison = transition_group_id + Condition ~ BioReplicate,
  fun_aggregate = NULL,
  label = FALSE,
  title = "cv across conditions",
  boxplot = TRUE,
  ...
)

Arguments

data

Data frame that is produced by the OpenSWATH/pyProphet workflow.

column.values

Indicates the columns for which the variation is assessed. This can be the Intensity or Signal, but also the retention time.

comparison

The comparison for assessing the variability. Default is to assess the variability per transition_group_id and Condition over the different Replicates. Comparison is performed using the dcast() function of the reshape2 package.

fun_aggregate

If for the comparison values have to be aggregated one needs to provide the function here.

label

Option to print value of median cv.

title

Title of plot. Default: "cv across conditions"

boxplot

Logical. If boxplot should be plotted. Default: TRUE

...

further arguments passed to method.

Value

Returns a list with the data and calculated cv and a table that summarizes the mean, median and mode cv per Condition (if Condition is contained in the comparison). In addition it plots in Rconsole a violin plot with the observed coefficient of variations.

Author

Peter Blattmann

Examples

{
 data("OpenSWATH_data", package="SWATH2stats")
 data("Study_design", package="SWATH2stats")
 data <- sample_annotation(OpenSWATH_data, Study_design)
 var_summary <- plot_variation(data)
 }