R: Create violin plot of sample correlation distribution

plot_sample_corr_distribution {proBatch}

R Documentation

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"
)

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

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)