View source: R/plot_variation.R
plot_variation | R Documentation |
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,
...
)
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. |
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.
Peter Blattmann
{
data("OpenSWATH_data", package="SWATH2stats")
data("Study_design", package="SWATH2stats")
data <- sample_annotation(OpenSWATH_data, Study_design)
var_summary <- plot_variation(data)
}
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