Plot Circular Network of Exposure Relationships — plot_circos

Generates a circular network plot to visualize relationships between exposures, either based on correlation ("exposures") or shared features ("degs", "factors").

Usage

plot_circos_correlation(
  expomicset,
  feature_type = c("degs", "omics", "factors", "factor_features", "exposures", "pcs"),
  exposure_cols = NULL,
  corr_threshold = NULL,
  shared_cutoff = 10,
  annotation_colors = NULL,
  low = "#006666",
  mid = "white",
  high = "#8E0152",
  midpoint = NULL
)

Arguments

expomicset: A MultiAssayExperiment object.
feature_type: One of "exposures", "degs", or "factors".
exposure_cols: Character vector of exposures to include (only for "exposures").
corr_threshold: Minimum |correlation| (only for "exposures").
shared_cutoff: Minimum number of shared features (only for "degs" or "factors"). Default = 10.
annotation_colors: Optional named vector of colors for categories.
low: low value color for edges.
mid: middle value color for edges.
high: high value color for edges.
midpoint: Midpoint for edge color gradient. Defaults to 0 (for correlations) or mean shared features.

Value

A ggplot object (ggraph circular plot).

Examples


# create example data
mae <- make_example_data(
    n_samples = 10,
    return_mae = TRUE
)
#> Ensuring all omics datasets are matrices with column names.
#> Creating SummarizedExperiment objects.
#> Creating MultiAssayExperiment object.
#> MultiAssayExperiment created successfully.

# run correlation analysis
mae <- mae |>
    run_correlation(
        feature_type = "exposures",
        exposure_cols = c("exposure_pm25", "exposure_no2", "age", "bmi")
    )

# create the circos plot
circos_plot <- mae |>
    plot_circos_correlation(
        feature_type = "exposures"
    )