Plot functions

Source: R/0docs.R, R/plot_clinvar.R, R/plot_ggnetwork.R, and 9 more

Functions to plot data.

plot_clinvar(
  hits,
  x = "region",
  y = "N",
  fill = "Type",
  rows = "ClinSigSimple",
  by = c("build", x, fill, rows)
)

plot_ggnetwork(
  g,
  colour_var = "x",
  size_var = colour_var,
  label_var = "name",
  hoverbox_column = "hover",
  interactive = TRUE,
  show_plot = TRUE,
  ...
)

plot_graph_3d(
  g,
  layout_func = igraph::layout.fruchterman.reingold,
  id_var = "name",
  node_color_var = "ancestor_name",
  edge_color_var = "zend",
  text_color_var = node_color_var,
  node_symbol_var = "ancestor_name",
  node_palette = pals::kovesi.cyclic_mrybm_35_75_c68_s25,
  edge_palette = pals::kovesi.cyclic_mrybm_35_75_c68_s25,
  node_opacity = 0.75,
  edge_opacity = 0.5,
  kde_palette = pals::gnuplot,
  add_kde = TRUE,
  extend_kde = 1.5,
  bg_color = kde_palette(6)[1],
  add_labels = FALSE,
  keep_grid = FALSE,
  aspectmode = "cube",
  hover_width = 100,
  label_width = 100,
  seed = 2023,
  showlegend = TRUE,
  show_plot = TRUE,
  save_path = tempfile(fileext = "plot_graph_3d.html"),
  verbose = TRUE
)

plot_ontology(
  ont,
  terms = NULL,
  types = c("circular", "graphviz", "tidygraph", "visnetwork"),
  ...
)

plot_ontology_circular(ont, ...)

plot_ontology_graphviz(ont, ...)

plot_ontology_heatmap(
  ont,
  annot = data.table::data.table(as.data.frame(ont@elementMetadata)),
  X = ontology_to(ont, to = "similarity"),
  fontsize = ont@n_terms * 4e-04,
  row_labels = ont@terms,
  column_labels = row_labels,
  name = NULL,
  row_side_vars = c("ancestor_name"),
  col_side_vars = c("IC", "depth", "n_children", "n_offspring", "n_connected_leaves"),
  col = pals::gnuplot(),
  show_plot = TRUE,
  save_path = tempfile(fileext = "plot_ontology_heatmap.pdf"),
  height = 12,
  width = height * 1.1,
  seed = 2023,
  types = c("heatmaply", "ComplexHeatmap")[2],
  ...
)

plot_ontology_tidygraph(ont, ...)

plot_ontology_visnetwork(ont, ...)

plot_save(plt, save_path = save_path, width = NULL, height = width)

plot_upheno_heatmap(
  plot_dat,
  lvl = 10,
  ont = get_ontology("upheno", lvl = lvl),
  hpo_ids = NULL,
  value.var = c("phenotype_genotype_score", "prop_intersect", "equivalence_score",
    "subclass_score"),
  name = value.var[1],
  min_rowsums = NULL,
  cluster_from_ontology = FALSE,
  save_dir = tempdir(),
  height = 15,
  width = 10
)

Arguments

g

ggnetwork object (or an igraph/tbl_graph to be converted to ggnetwork format).

colour_var

Column to color nodes by.

size_var

Column to scale node size by.

label_var

Column containing the label for each node in a graph (e.g. "hpo_name").

interactive

Make the plot interactive.

show_plot

Print the plot after it's been generated.

...

Arguments passed on to ggplot2::aes, simona::dag_circular_viz, simona::dag_graphviz, base::plot, simona::dag_graphviz

dag

An ontology_Dag object.

highlight

A vector of terms to be highlighted on the DAG.

start

Start of the circle, measured in degree.

end

End of the circle, measured in degree.

partition_by_level

If node_col is not set, users can cut the DAG into clusters with different node colors. The partitioning is applied by partition_by_level().

partition_by_size

Similar as partition_by_level, but the partitioning is applied by partition_by_size().

node_col

Colors of nodes. If the value is a vector, the order should correspond to terms in dag_all_terms().

node_transparency

Transparency of nodes. The same format as node_col.

node_size

Size of nodes. The same format as node_col.

edge_col

A named vector where names correspond to relation types.

edge_transparency

A named vector where names correspond to relation types.

legend_labels_from

If partitioning is applied on the DAG, a legend is generated showing different top terms. By default, the legend labels are the term IDs. If there are additionally column stored in the meta data frame of the DAG object, the column name can be set here to replace the term IDs as legend labels.

legend_labels_max_width

Maximal width of legend labels measured by the number of characters per line. Labels are wrapped into multiple lines if the widths exceed it.

other_legends

A list of legends generated by ComplexHeatmap::Legend().

use_raster

Whether to first write the circular image into a temporary png file, then add to the plot as a raster object?

newpage

Whether call grid::grid.newpage() to create a new plot?

node_param

A list of parameters. Each parameter has the same format. The value can be a single scalar, a full length vector with the same order as in dag_all_terms(), or a named vector that contains a subset of terms that need to be customized. The full set of parameters can be found at https://graphviz.org/docs/nodes/.

edge_param

A list of parameters. Each parameter has the same format. The value can be a single scalar, or a named vector that contains a subset of terms that need to be customized. The full set of parameters can be found at https://graphviz.org/docs/edges/. If the parameter is set to a named vector, it can be named by relation types c("is_a" = ...), or directly relations c("a -> b" = ...). Please see the vignette for details.

x

the coordinates of points in the plot. Alternatively, a single plotting structure, function or any R object with a plot method can be provided.

y

the y coordinates of points in the plot, optional if x is an appropriate structure.

layout_func

Layout function for the graph.

node_color_var

Variable in the vertex metadata to color nodes by.

edge_color_var

Variable in the edge metadata to color edges by.

text_color_var

Variable in the node metadata to color text by.

node_symbol_var

Variable in the vertex metadata to shape nodes by.

node_palette

Color palette function for the nodes/points.

edge_palette

Color palette function for the edges/lines.

node_opacity

Node opacity.

edge_opacity

Edge opacity.

kde_palette

Color palette function for the KDE plot.

add_kde

Add a kernel density estimation (KDE) plot below the 3D scatter plot (i.e. the "mountains" beneath the points).

extend_kde

Extend the area that the KDE plot covers.

bg_color

Plot background color.

add_labels

Add phenotype name labels to each point.

keep_grid

Keep all grid lines and axis labels.

aspectmode

The proportions of the 3D plot. See the plotly documentation site for details.

hover_width

Maximum width of the hover text.

label_width

Maximum width of the label text.

seed

Set the seed for reproducible clustering.

showlegend

Show node fill legend.

save_path

Path to save interactive plot to as a self-contained HTML file.

verbose

Print messages.

ont

An ontology of class ontology_DAG.

terms

A vector of ontology term IDs.

types

Types of graph to produce. Can be one or more.

fontsize

Axis labels font size.

row_labels

Optional row labels which are put as row names in the heatmap.

column_labels

Optional column labels which are put as column names in the heatmap.

name

Name of the heatmap. By default the heatmap name is used as the title of the heatmap legend.

row_side_vars

Variables to include in row-side metadata annotations.

col_side_vars

Variables to include in column-side metadata annotations.

col

A vector of colors if the color mapping is discrete or a color mapping function if the matrix is continuous numbers (should be generated by colorRamp2). If the matrix is continuous, the value can also be a vector of colors so that colors can be interpolated. Pass to ColorMapping. For more details and examples, please refer to https://jokergoo.github.io/ComplexHeatmap-reference/book/a-single-heatmap.html#colors .

height

Height of the heatmap body.

width

Width of the heatmap body.

save_dir

Directory to save a file to.

id_col

Column containing the unique identifier for each node in a graph (e.g. "name").

top_targets

data.table of prioritised targets generated by prioritise_targets.

Value

A named list containing the plot and the data.

A 3D interactive plotly object.

Null

Null

Plot

Null

Null

Functions

  • plot_clinvar(): plot_ Plot mapped variant annotations.

  • plot_ggnetwork(): plot_ Plot a ggnetwork.

  • plot_graph_3d(): plot_ 3D network

    Plot a subset of the HPO as a 3D network.

  • plot_ontology(): plot_

  • plot_ontology_circular(): plot_

  • plot_ontology_graphviz(): plot_ Plot ontology: graphviz

    Make a circular plot of an ontology.

  • plot_ontology_heatmap(): plot_ Plot heatmap

    Plot a phenotype x phenotype correlation matrix based on genetic overlap.

  • plot_ontology_tidygraph(): plot_

  • plot_ontology_visnetwork(): plot_

  • plot_save(): plot_ Save a plot using ggsave, grDevices, or visSave.

  • plot_upheno_heatmap(): plot_

Examples

ont <- get_ontology(terms=10)
#> Loading cached ontology: /github/home/.cache/R/KGExplorer/mondo.rds
#> Randomly sampling 10 term(s).
g <- ontology_to(ont, to="tbl_graph")
#> Translating ontology terms to ids.
#> Converted ontology to: tbl_graph 
g <- add_hoverboxes(g)
#> Making hoverboxes from: 'name', 'short_id', 'label', 'namespace', 'definition', 'IC', 'depth', 'n_children', 'n_ancestors', 'n_parents', 'n_offspring', 'n_connected_leaves', 'ancestor', 'ancestor_name', 'n_edges', 'ontLvl'
#> Adding hoverboxes to data.table.
out <- plot_ggnetwork(g, label_var="label")
#> Loading required namespace: ggnetwork
#> Registered S3 method overwritten by 'ggnetwork':
#>   method         from  
#>   fortify.igraph ggtree
#> Creating ggnetwork plot.
#> Converting graph to ggnetwork.
ont <- get_ontology("hp", terms=10, add_ancestors=TRUE)
#> Loading cached ontology: /github/home/.cache/R/KGExplorer/hp.rds
#> Randomly sampling 10 term(s).
g <- ontology_to(ont, to="tbl_graph")
#> Translating ontology terms to ids.
#> Converted ontology to: tbl_graph 
plt <- plot_graph_3d(g=g, show_plot=FALSE)
#> Converting igraph to plotly data.
#> Translating ontology terms to names.
#> Loading cached ontology: /github/home/.cache/R/KGExplorer/hpo.rds
#> Warning: 'surface' objects don't have these attributes: 'marker'
#> Valid attributes include:
#> '_deprecated', 'autocolorscale', 'cauto', 'cmax', 'cmid', 'cmin', 'coloraxis', 'colorbar', 'colorscale', 'connectgaps', 'contours', 'customdata', 'customdatasrc', 'hidesurface', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'legendgroup', 'legendgrouptitle', 'legendrank', 'lighting', 'lightposition', 'meta', 'metasrc', 'name', 'opacity', 'opacityscale', 'reversescale', 'scene', 'showlegend', 'showscale', 'stream', 'surfacecolor', 'surfacecolorsrc', 'text', 'textsrc', 'type', 'uid', 'uirevision', 'visible', 'x', 'xcalendar', 'xhoverformat', 'xsrc', 'y', 'ycalendar', 'yhoverformat', 'ysrc', 'z', 'zcalendar', 'zhoverformat', 'zsrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
#> Saving interactive plot --> /tmp/RtmptP89wX/file14ca47e9c987eplot_graph_3d.html
#> Warning: 'surface' objects don't have these attributes: 'marker'
#> Valid attributes include:
#> '_deprecated', 'autocolorscale', 'cauto', 'cmax', 'cmid', 'cmin', 'coloraxis', 'colorbar', 'colorscale', 'connectgaps', 'contours', 'customdata', 'customdatasrc', 'hidesurface', 'hoverinfo', 'hoverinfosrc', 'hoverlabel', 'hovertemplate', 'hovertemplatesrc', 'hovertext', 'hovertextsrc', 'ids', 'idssrc', 'legendgroup', 'legendgrouptitle', 'legendrank', 'lighting', 'lightposition', 'meta', 'metasrc', 'name', 'opacity', 'opacityscale', 'reversescale', 'scene', 'showlegend', 'showscale', 'stream', 'surfacecolor', 'surfacecolorsrc', 'text', 'textsrc', 'type', 'uid', 'uirevision', 'visible', 'x', 'xcalendar', 'xhoverformat', 'xsrc', 'y', 'ycalendar', 'yhoverformat', 'ysrc', 'z', 'zcalendar', 'zhoverformat', 'zsrc', 'key', 'set', 'frame', 'transforms', '_isNestedKey', '_isSimpleKey', '_isGraticule', '_bbox'
ont <- get_ontology("hp")
#> Loading cached ontology: /github/home/.cache/R/KGExplorer/hp.rds
res <- plot_ontology(ont, 
                     terms=100,
                     types="circular",
                     partition_by_level=2,
                     edge_transparency=.9)
#> Randomly sampling 100 term(s).
#> Loading required namespace: DiagrammeR
#> converting DAG to a tree...
#> 
#> going through 504 / 504 nodes ... Done.
#> calculating term positions on the DAG...
#> 
#> going through 504 / 504 nodes ... Done.
#> making plot...
#> adding links...
#> adding terms...

#> Best device size: 10.18 x 7 inches.
ont <- get_ontology("hp", terms=2)
#> Loading cached ontology: /github/home/.cache/R/KGExplorer/hp.rds
#> Randomly sampling 2 term(s).
hm <- plot_ontology_heatmap(ont)
#> Adding ancestor metadata.
#> Ancestor metadata already present. Use force_new=TRUE to overwrite.
#> Creating heatmap: ComplexHeatmap
#> Using palette: okabe
#> Using palette: stepped2
#> Using palette: tol
#> Using palette: watlington
#> Using palette: stepped3
#> Using palette: tableau20
#> Translating ontology terms to ids.
#> term_sim_method: Sim_WP_1994
#> collecting all ancestors of input terms ...
#> 
#> going through 0 / 18 ancestors ...
#> 
#> going through 18 / 18 ancestors ... Done.
#> collecting all ancestors of input terms ...
#> 
#> going through 0 / 18 ancestors ...
#> 
#> going through 18 / 18 ancestors ... Done.
#> Converted ontology to: similarity 
#> Saving plot --> /tmp/RtmptP89wX/file14ca47c53b842plot_ontology_heatmap.pdf