plot_variation {SWATH2stats} | R Documentation

## Plots the coefficient of variation for different replicates.

### Description

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

### Usage

    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(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(data)
     }

[Package SWATH2stats version 1.24.0 Index]