| analyze | R Documentation |
Compute the Venn region map for a ['VennDataset-class'] and bind it to a model.
analyze(dataset, model = "auto")
dataset |
A ['VennDataset-class'] (from one of the 'load_*' functions). |
model |
Model identifier. '"auto"' picks the canonical model for the dataset's set count (alphabetical first match), e.g. 4 sets -> 'venn-4-set'. '"proportional"' requests an area-proportional layout (only supports 2-3 sets, added in Phase 3). Otherwise pass an explicit name from [list_models()]. |
A ['RegionResult-class'] with the per-region item membership, set sizes, and (lazily) 'statistics(result)'.
ds <- methods::new("VennDataset",
set_names = c("A", "B"),
items = list(A = c("x", "y"), B = c("y", "z")),
item_order = c("x", "y", "z"),
universe_size = 10L, source_path = NULL, format = "csv")
result <- analyze(ds)
result@model
ds <- load_sample("dataset_real_cancer_drivers_4")
result <- analyze(ds, model = "auto")
result@model
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