plot_variation_vs_total: Plots the total variation versus variation within replicates

Description Usage Arguments Value Author(s) Examples

View source: R/plot_variation_vs_total.R

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

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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

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{
 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 April 20, 2021, 12:02 p.m.