Package 'EpiViz'

Title: EpiViz
Description: An implementation of Circos plots for epidemiologists in R. It takes the Circlize package and adapts it for use by epidemiologists. Circos plots provide an informative way of plotting greater than 50 plotting points. A legend can be plotted automatically and customised.
Authors: Matthew Lee [aut, cre]
Maintainer: Matthew Lee <[email protected]>
License: CC0
Version: 0.2.0
Built: 2026-06-03 08:52:37 UTC
Source: https://github.com/mattlee821/EpiViz

Help Index

Create a Circos plot with up to 3 tracks using points, lines or bars

Description

Create a Circos plot with up to 3 tracks using points, lines or bars

Usage

circos_plot(
  track_number,
  track1_data,
  track2_data = NULL,
  track3_data = NULL,
  track1_type = "points",
  track2_type = "points",
  track3_type = "points",
  label_column,
  section_column,
  order = TRUE,
  order_column = NULL,
  estimate_column = NULL,
  pvalue_column = NULL,
  pvalue_adjustment = 0.05,
  lower_ci = NULL,
  upper_ci = NULL,
  lines_column = NULL,
  lines_type = "o",
  bar_column = NULL,
  histogram_column = NULL,
  histogram_binsize = 0.01,
  histogram_densityplot = FALSE,
  legend_track = FALSE,
  legend_section = FALSE,
  track1_label = NA,
  track2_label = NA,
  track3_label = NA,
  pvalue_label = NA,
  circle_size = 25,
  track1_height = 0.2,
  track2_height = 0.2,
  track3_height = 0.2,
  equal_axis = FALSE,
  origin = 0,
  colours = c("#00378f", "#ffc067", "#894300")
)

Arguments

track_number

The number of tracks you wnat your circos plot to have. Maximum number of tracks is 3.
track1_data

The data frame of your first track.
track2_data

The data frame of your second track.
track3_data

The data frame of your third track.
track1_type

The type of plot for the first track. One of "scatter", "lines", "bar" and "histogram".
track2_type

The type of plot for the second track. One of "scatter", "lines", "bar" and "histogram".
track3_type

The type of plot for the third track. One of "scatter", "lines", "bar" and "histogram".
label_column

The column in your data frames that you will use as the labels for the circos plot. This will likely be the column with your exposure/outcome name in. Labels go on the outside of the plot.
section_column

The column in your data frames that you will use to group/section your data/plot by.
order

Do you want MR Viz to organise your columns alphabetically. Default is TRUE
order_column

If order = FALSE what column do you want to order your sections by
estimate_column

The column in your data frames with the estimates in.
pvalue_column

The column in your data frames with the p-values in.
pvalue_adjustment

The threshold you want to set your p-value 'significance' threshold too. This can be in the format of a single value or a function e.g. 0.05/22. The p-value thrshold is only used for scatter plots.
lower_ci

The column in your data frames with the lower confidence intervals in.
upper_ci

The column in your data frames with the upper confidence intervals in.
lines_column

The column in your data frames that you want to plot as lines.
lines_type

The type of line plot you want. "l" = straight lines; "o" = straight lines with points; "s" = boxed lines; "h" = vertical lines. Default is "o".
bar_column

The column in your data frames that you want to plot as bars.
histogram_column

The column in your data frames that you want to plot as histograms.
histogram_binsize

The binsize of the histogram. Default is 0.01.
histogram_densityplot

Do you want your histogram to be a density plot or not. Default is FALSE.
legend_track

Track legend control. Set to FALSE for no legend (default), or provide a numeric value (0-1) representing the distance from the bottom of the plot (NPC units). Default when TRUE is 0.05. The legend is centered horizontally and items are arranged in a horizontal row.
legend_section

Section legend control. Set to FALSE for no legend (default), or provide a numeric value (0-1) representing the distance from the bottom of the plot (NPC units). The section legend creates a numbered key for the categories defined in section_column.
track1_label

What do you want the label for the first track to be e.g. "Body Mass Index"
track2_label

What do you want the label for the first track to be e.g. "Corondary Heart Disease"
track3_label

What do you want the label for the first track to be e.g. "Breast Cancer"
pvalue_label

What do you want the label for the p-value to read e.g. "p-value <= 0.05"
circle_size

The size of the circos plot. Smaller numbers make larger circos plots. Default is 25. You will need to adjust this number a few times to get the perfect size for your specific circos plot requirements. If you have long labels then try ≥ 25. If your labels are short try 1-10.
track1_height

Size of the track as a percent of the whole circle. Default is 20 percent (0.20)
track2_height

Size of the track as a percent of the whole circle. Default is 20 percent (0.20)
track3_height

Size of the track as a percent of the whole circle. Default is 20 percent (0.20). It is sometimes worth increasing the size of track 3 to 30 percent
equal_axis

Do you want your tracks to share the same axis (Defalut = FALSE), if TRUE it will use the minimmum and maximum from the upper and lower confidence intervals to calculate the axis for each track. This ONLY applies to 'points' all other plot types are independent of each track.
origin

Where do you want your X axis line drawn, e.g. 0 for continuous outcomes and 1 for binary outcomes when using beta and odds ratios respectively. Default is 0
colours

list of colours for each track. Use "".

Example data: Simulated epidemiology results for track 1

Description

A simulated dataset of effect estimates and confidence intervals for 120 variables.

Usage

EpiViz_data1

Format

A data frame with 120 rows and 8 variables.

label

Variable names

class

Greater category/grouping

subgroup

Minor category/grouping

beta

Effect estimate

se

Standard error

pvalue

P-value

lower_confidence_interval

Lower 95% confidence interval bound

upper_confidence_interval

Upper 95% confidence interval bound

Example data: Simulated epidemiology results for track 2

Description

A simulated dataset of effect estimates and confidence intervals for 120 variables.

Usage

EpiViz_data2

Format

A data frame with 120 rows and 8 variables.

label

Variable names

class

Greater category/grouping

subgroup

Minor category/grouping

beta

Effect estimate

se

Standard error

pvalue

P-value

lower_confidence_interval

Lower 95% confidence interval bound

upper_confidence_interval

Upper 95% confidence interval bound

Example data: Simulated epidemiology results for track 3

Description

A simulated dataset of effect estimates and confidence intervals for 120 variables.

Usage

EpiViz_data3

Format

A data frame with 120 rows and 8 variables.

label

Variable names

class

Greater category/grouping

subgroup

Minor category/grouping

beta

Effect estimate

se

Standard error

pvalue

P-value

lower_confidence_interval

Lower 95% confidence interval bound

upper_confidence_interval

Upper 95% confidence interval bound