Skip to contents

Plot the correlation between sample

plot_cor_samples.Rd

The correlation between feature quantifications in each sample can be a useful QC step to assess whether the experiment has worked. This function plots the correlation values in a heatmap. Samples are not clustered and are ordered on the axes in the order they are in the SummarizedExperiment

Usage

plot_cor_samples(obj, i, order = "original", ...)

Arguments

obj

QFeatures. Proteomics dataset

i

string. Index for the SummarizedExperiment you wish to plot

...

addiional arguments passed onto corrplot::corrplot

Value

Returns a ggplot object.

Examples


tmt_qf <- QFeatures::readQFeatures(assayData = psm_tmt_total,
  quantCols = 36:45,
  name = "psms_raw")
#> Checking arguments.
#> Loading data as a 'SummarizedExperiment' object.
#> Formatting sample annotations (colData).
#> Formatting data as a 'QFeatures' object.

cor_sample(tmt_qf, 'psms_raw')
#> Error in cor_sample(tmt_qf, "psms_raw"): could not find function "cor_sample"