plot_sample_corr_distribution {proBatch} | R Documentation |
Useful to visualize within batch vs within replicate vs non-related sample correlation
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" )
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 |
sample_annotation |
data frame with:
.
See |
repeated_samples |
if |
sample_id_col |
name of the column in |
batch_col |
column in |
biospecimen_id_col |
column in |
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
|
theme |
ggplot theme, by default |
corr_distribution |
data frame with correlation distribution,
as returned by |
ggplot
type object with violin plot
for each plot_param
calculate_sample_corr_distr
,
ggplot
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)