plot_sample_corr_distribution: Create violin plot of sample correlation distribution

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

Create violin plot of sample correlation distribution

Description

Useful to visualize within batch vs within replicate vs non-related sample correlation

Usage

plot_sample_corr_distribution(data_matrix, sample_annotation,
  repeated_samples = NULL, sample_id_col = "FullRunName",
  batch_col = "MS_batch", biospecimen_id_col = "EarTag",
  filename = NULL, width = NA, height = NA, units = c("cm", "in",
  "mm"), plot_title = "Sample correlation distribution",
  plot_param = "batch_replicate", theme = "classic")

plot_sample_corr_distribution.corrDF(corr_distribution, filename = NULL,
  width = NA, height = NA, units = c("cm", "in", "mm"),
  plot_title = "Sample correlation distribution",
  plot_param = "batch_replicate", theme = "classic", base_size = 20)

Arguments

data_matrix	features (in rows) vs samples (in columns) matrix, with feature IDs in rownames and file/sample names as colnames. See "example_proteome_matrix" for more details (to call the description, use help("example_proteome_matrix"))
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")
repeated_samples	if NULL, correlation of all samples is plotted
sample_id_col	name of the column in sample_annotation table, where the filenames (colnames of the data_matrix are found).
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).
biospecimen_id_col	column in sample_annotation that captures the biological sample, that (possibly) was profiled several times as technical replicates. Tip: if such ID is absent, but can be defined from several columns, create new biospecimen_id column
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
width	option determining the output image width
height	option determining the output image width
units	units: 'cm', 'in' or 'mm'
plot_title	title of the plot (e.g., processing step + representation level (fragments, transitions, proteins) + purpose (meanplot/corrplot etc))
plot_param	columns, defined in correlation_df, which is output of calculate_sample_corr_distr, specifically, replicate batch_the_same batch_replicate batches
theme	ggplot theme, by default classic. Can be easily overriden
corr_distribution	data frame with correlation distribution, as returned by calculate_sample_corr_distr

Value

ggplot type object with violin plot for each plot_param

See Also

calculate_sample_corr_distr, ggplot

Examples

sample_corr_distribution_plot <- plot_sample_corr_distribution(
example_proteome_matrix,
example_sample_annotation, batch_col = 'MS_batch', 
biospecimen_id_col = "EarTag", 
plot_param = 'batch_replicate')

corr_distribution = calculate_sample_corr_distr(data_matrix = example_proteome_matrix, 
sample_annotation = example_sample_annotation,
batch_col = 'MS_batch',biospecimen_id_col = "EarTag")
sample_corr_distribution_plot <- plot_sample_corr_distribution.corrDF(corr_distribution,
plot_param = 'batch_replicate')

## Not run: 
sample_corr_distribution_plot <- plot_sample_corr_distribution.corrDF(corr_distribution,
plot_param = 'batch_replicate', 
filename = 'test_sampleCorr.png', 
width = 28, height = 28, units = 'cm')

## End(Not run)

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