plot_CV_distr: Plot CV distribution to compare various steps of the analysis

In symbioticMe/proBatch: Tools for Diagnostics and Corrections of Batch Effects in Proteomics

Plot CV distribution to compare various steps of the analysis

Description

Plot CV distribution to compare various steps of the analysis

Usage

plot_CV_distr(df_long, sample_annotation = NULL,
  feature_id_col = "peptide_group_label",
  sample_id_col = "FullRunName", measure_col = "Intensity",
  biospecimen_id_col = "EarTag", batch_col = NULL, unlog = TRUE,
  log_base = 2, offset = 1, plot_title = NULL, filename = NULL,
  theme = "classic")

Arguments

df_long	as in df_long for the rest of the package, but, when it has entries for intensity, represented in measure_col for several steps, e.g. raw, normalized, batch corrected data, as seen in column Step, then multi-step CV comparison can be carried out.
sample_annotation	data frame with: sample_id_col (this can be repeated as row names) biological covariates technical covariates (batches etc) . See help("example_sample_annotation")
feature_id_col	name of the column with feature/gene/peptide/protein ID used in the long format representation df_long. In the wide formatted representation data_matrix this corresponds to the row names.
sample_id_col	name of the column in sample_annotation table, where the filenames (colnames of the data_matrix are found).
measure_col	if df_long is among the parameters, it is the column with expression/abundance/intensity; otherwise, it is used internally for consistency.
biospecimen_id_col	column in sample_annotation that defines a unique bio ID, which is usually a combination of conditions or groups. Tip: if such ID is absent, but can be defined from several columns, create new biospecimen_id column
batch_col	column in sample_annotation that should be used for batch comparison (or other, non-batch factor to be mapped to color in plots).
unlog	(logical) whether to reverse log transformation of the original data
log_base	base of the logarithm for transformation
offset	small positive number to prevent 0 conversion to -Inf
plot_title	title of the plot (e.g., processing step + representation level (fragments, transitions, proteins) + purpose (meanplot/corrplot etc))
filename	path where the results are saved. If null the object is returned to the active window; otherwise, the object is save into the file. Currently only pdf and png format is supported
theme	ggplot theme, by default classic. Can be easily overriden

Value

ggplot object with the boxplot of CVs on one or several steps

Examples

CV_plot = plot_CV_distr(example_proteome, 
sample_annotation = example_sample_annotation, 
measure_col = 'Intensity', batch_col = 'MS_batch', 
plot_title = NULL, filename = NULL, theme = 'classic')

symbioticMe/proBatch documentation built on April 9, 2023, 11:59 a.m.