plot_sample_mean_or_boxplot {proBatch} | R Documentation |
Plot per-sample mean or boxplot (showing median and quantiles) vs order (if the real running order available)
plot_sample_mean(data_matrix, sample_annotation = NULL, sample_id_col = "FullRunName", order_col = "order", batch_col = "MS_batch", facet_col = NULL, color_by_batch = FALSE, color_scheme = "brewer", theme = "classic", plot_title = NULL, order_per_facet = FALSE, vline_color = "grey", ylimits = NULL) plot_boxplot(df_long, sample_annotation = NULL, sample_id_col = "FullRunName", measure_col = "Intensity", order_col = "order", batch_col = "MS_batch", facet_col = NULL, color_by_batch = TRUE, color_scheme = "brewer", theme = "classic", plot_title = NULL, order_per_facet = FALSE)
data_matrix |
features (in rows) vs samples (in columns) matrix, with feature IDs in rownames and file/sample names as colnames. in most function, |
sample_annotation |
data matrix with 1) |
sample_id_col |
name of the column in sample_annotation file, where the filenames (colnames of the data matrix are found) |
order_col |
column where running order is specified. |
batch_col |
column in |
facet_col |
recommended if more than one batch covariate is present. Faceting is most suited to examine instruments separately |
color_by_batch |
should the each batch be represented with its own color? |
color_scheme |
named vector, names corresponding to unique batch values
as specified in |
theme |
ggplot theme, by default |
plot_title |
Title of the plot (usually, processing step + representation level (fragments, transitions, proteins)) |
order_per_facet |
if order is defined ignoring facets (usually instrument), re-define order per-batch |
vline_color |
color of vertical lines, typically denoting
different MS batches in ordered runs; should be |
ylimits |
range of y-axis to plot feature-level trends |
df_long |
data frame where each row is a single feature in a single
sample, thus it has minimally, |
measure_col |
if |
functions for quick visual assessment of trends associated, overall
or specific covariate-associated (see batch_col
and facet_col
)
ggplot2 class object. Thus, all aesthetics can be overriden
mean_plot <- plot_sample_mean(example_proteome_matrix, example_sample_annotation, order_col = 'order', batch_col = "MS_batch") boxplot <- plot_boxplot(example_proteome, example_sample_annotation, batch_col = "MS_batch")