plot_variation_vs_total: Plots the total variation versus variation within replicates

In peterblattmann/SWATH2stats: Transform and Filter SWATH Data for Statistical Packages

Plots the total variation versus variation within replicates

Description

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

Usage

plot_variation_vs_total(
  data,
  column.values = "Intensity",
  comparison1 = transition_group_id ~ BioReplicate + Condition,
  comparison2 = transition_group_id + Condition ~ BioReplicate,
  fun_aggregate = NULL,
  label = FALSE,
  title = "coefficient of variation - total versus within replicates",
  boxplot = TRUE,
  ...
)

Arguments

data	Data table 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.
comparison1	The comparison for assessing the total variability. Default is to assess the variability per transition_group_id over the combination of Replicates and different Conditions.
comparison2	The comparison for assessing the variability within the replicates. Default is to assess the variability per transition_group_id and Condition over the different Replicates.
fun_aggregate	If depending on the comparison values have to be aggregated one needs to provide the function here. (I think this should be sum, yesno?)
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
...	Arguments passed through, currently unused.

Value

Plots in Rconsole a violin plot comparing the total variation with the variation within replicates. In addition it returns the data frame from which the plotting is done and a table with the calculated mean, median and mode of the cv for the total or replicate data.

Author(s)

Peter Blattmann

Examples

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

peterblattmann/SWATH2stats documentation built on July 2, 2023, 9:42 p.m.