annotation_exposures_list_barplot: Plot the exposures of a cohort with different layers of...
In YAPSA: Yet Another Package for Signature Analysis

Description Usage Arguments Details Value See Also Examples

The exposures H, determined by NMF or by LCD, are displayed as a stacked barplot by calling Heatmap. The x-axis displays the PIDs (patient identifier or sample), the y-axis the counts attributed to the different signatures with their respective colours per PID. It is analogous to plot_exposures. As many layers of information as desired can be added via an annotation data frame. The annotation data is handled in a way similar to annotation_heatmap_exposures. In comparison to annotation_exposures_barplot allows this function to deal with a list of differn signature and mutation types. This function calls:

rowAnnotation,
HeatmapAnnotation and
Heatmap

annotation_exposures_list_barplot(
  in_exposures_list,
  in_signatures_ind_list,
  in_subgroups_list,
  in_annotation_list,
  ylab = NULL,
  title = "",
  in_indel_sigs = FALSE,
  in_labels = FALSE,
  in_barplot_borders = TRUE,
  in_column_anno_borders = FALSE,
  in_annotation_legend_side = "right",
  in_padding = unit(c(2, 20, 2, 2), "mm"),
  in_annotation = NULL
)

`in_exposures_list`	A list of numerical data frame encoding the exposures `H` of different signature types, i.e. which signature contributes how much to which PID (patient identifier or sample).
`in_signatures_ind_list`	A list of data frame containing meta information about the each signature type individually
`in_subgroups_list`	A list of data frame indicating of each siganture type which PID (patient or sample identifyier) belongs to which subgroup
`in_annotation_list`	A list data frame indicating which PID (patient or sample identifyier) belongs to which subgroup for all layers of annotation and a list indicating colour attributions for all layers of annotation for each siganture type individually
`ylab`	String indicating the column name in `in_subgroups_df` to take the subgroup information from.
`title`	Title for the plot to be created.
`in_indel_sigs`	Tag which is default FALSE when whole genome data are analysed the tag will be TRUE
`in_labels`	Whether or not to show the names of the samples.
`in_barplot_borders`	Whether or not to show border lines in barplot
`in_column_anno_borders`	Whether or not to draw separating lines between the fields in the annotation
`in_annotation_legend_side`	Where to put the legends of the annotation df, default is right.
`in_padding`	Parameter passed on to function `draw`
`in_annotation`	A full annotation object may also be provided by the educated user.

It might be necessary to install the newest version of the development branch of the packages circlize and ComplexHeatmap by Zuguang Gu: devtools::install_github("jokergoo/circlize") and devtools::install_github("jokergoo/ComplexHeatmap")

The function doesn't return any value.

HeatmapAnnotation

Heatmap

decorate_heatmap_body

annotation_heatmap_exposures

plot_exposures