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3. Extras

Source: vignettes/extra.Rmd
extra.Rmd

Lines and Bars

EpiViz allows you to visualize data using different plot types across tracks. This is particularly powerful when you want to show different aspects of your data simultaneously.

You can combine points, lines, and bars in a single plot.

circos_plot(
  track_number = 3,
  track1_data = EpiViz_data1,
  track2_data = EpiViz_data2,
  track3_data = EpiViz_data3,
  track1_type = "points",
  track2_type = "lines",
  track3_type = "bar",
  label_column = "label",
  section_column = "class",
  estimate_column = "beta",
  pvalue_column = "pvalue",
  lower_ci = "lower_confidence_interval",
  upper_ci = "upper_confidence_interval",
  lines_column = "beta",
  bar_column = "beta",
  circle_size = 25
)

Legends

A key feature of EpiViz is its ability to automatically generate comprehensive legends using ComplexHeatmap. There are two types of legends:

1. Track Legend (legend_track)

This legend summarizes the tracks and significance indicators (significant vs. non-significant points). It is positioned at the bottom of the plot.

The legend_track parameter accepts: - FALSE - No legend (default) - TRUE - Horizontal legend at the default distance (0.05) from the bottom. - A numeric value (e.g., 0.1) - Distance from the bottom of the plot in NPC units (0-1).

2. Section Legend (legend_section)

This legend provides a numbered key for the categories defined in section_column. This is particularly useful if your category names are long or if you have many sectors.

The legend_section parameter accepts: - FALSE - No legend (default) - TRUE - Horizontal legend at the default distance (0.05) from the bottom. - A numeric value (e.g., 0.03) - Distance from the bottom of the plot in NPC units.

circos_plot(
  track_number = 3,
  track1_data = EpiViz_data1,
  track2_data = EpiViz_data2,
  track3_data = EpiViz_data3,
  track1_type = "points",
  track2_type = "lines",
  track3_type = "bar",
  label_column = "label",
  section_column = "class",
  estimate_column = "beta",
  pvalue_column = "pvalue",
  lower_ci = "lower_confidence_interval",
  upper_ci = "upper_confidence_interval",
  lines_column = "beta",
  bar_column = "beta",
  legend_track = 0.08,
  legend_section = 0.03,
  track1_label = "Points",
  track2_label = "Lines",
  track3_label = "Bars",
  pvalue_label = "P < 0.05",
  circle_size = 25
)