Plot histogram for multiOmicDataSet

Plot histogram for multiOmicDataSet

Arguments

count_type

Required if moo_counts is a multiOmicDataSet: the type of counts to use – must be a name in the counts slot (moo@counts).

sub_count_type

Used if moo_counts is a multiOmicDataSet AND if count_type is a list, specify the sub count type within the list

group_colname

The column from the sample metadata containing the sample group information. This is usually a column showing to which experimental treatments each sample belongs (e.g. WildType, Knockout, Tumor, Normal, Before, After, etc.).

color_values

vector of colors as hex values or names recognized by R. Unnamed colors are assigned by factor level order when the grouping column is a factor; otherwise, they follow the order in which groups first appear in the metadata column. Defaults to NULL; when NULL, mosuite_palette is used for data.frame dispatch and stored colors are used for multiOmicDataSet dispatch.

See also

plot_histogram() generic

Other plotters for multiOmicDataSets: plot_corr_heatmap,MOSuite::multiOmicDataSet-method, plot_pca,MOSuite::multiOmicDataSet-method, plot_read_depth,MOSuite::multiOmicDataSet-method

Examples

# plot histogram for a counts slot in a multiOmicDataset Object
moo <- multiOmicDataSet(
  sample_metadata = nidap_sample_metadata,
  anno_dat = data.frame(),
  counts_lst = list("raw" = nidap_raw_counts)
)
p <- plot_histogram(moo, count_type = "raw")
#> color_values contains 3 colors for 9 values in column Sample. Generating 6 additional colors.

# customize the plot
plot_histogram(moo,
  count_type = "raw",
  group_colname = "Group", color_by_group = TRUE
)