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Plot clone-level viability (lollipop plot)

Source: R/plot.R
plot_clone_viability.Rd

Visualizes predicted drug sensitivity for each clone within patients. Each clone is represented as a point with a stem (lollipop style). Useful for identifying resistant clones within heterogeneous tumors.

Usage

plot_clone_viability(
  clone_viability,
  viability_var = "comb_viability",
  weights_var = NULL,
  response_var = NULL,
  drug = NULL,
  base_size = 11,
  y_limits = c(-3, 1.2),
  viridis_scale = FALSE,
  tooltip = TRUE,
  tooltip_col = NULL
)

Arguments

clone_viability

Data frame with columns: patient, clone_id, and the viability column named by viability_var. Optionally also weights_var (clone proportion) and response_var (clinical response) columns.

viability_var

Character. Column name for viability values. Default = "comb_viability".

weights_var

Character. Optional column name for clone weights (point size). Default = NULL.

response_var

Character. Optional column for response annotation. Default = NULL.

drug

Character. Drug name, used as plot title. Default = NULL.

base_size

Numeric. Base font size. Default = 11.

y_limits

Numeric vector. Y-axis limits. Default = c(-3, 1.2).

viridis_scale

Logical. If TRUE, uses a viridis sequential scale (dark = low/sensitive, yellow = high/resistant). If FALSE (default), uses the diverging red-blue scale (blue = low/sensitive, white = neutral, red = high/resistant) with data-driven limits, so every value keeps a real color – nothing clips to grey/NA outside a fixed window.

tooltip

Logical. If TRUE (default) and ggiraph is installed, points get hover tooltips (clone + viability + proportion).

tooltip_col

Character. Optional existing column used as the tooltip text. Default = NULL (auto-builds a rich tooltip).

Value

A ggplot object.

Details

Facet strategy is adaptive:

  • <= 12 patients: single-row grid, strips on the bottom (45 deg).

  • > 12 patients: facet_wrap grid, one compact panel per patient.

Examples

if (FALSE) { # \dontrun{
  clone_kill <- data.frame(
    patient = c("P1", "P1", "P2", "P2"),
    clone_id = c("c1", "c2", "c1", "c2"),
    comb_viability = c(-0.5, 0.8, -1.2, 0.3)
  )
  plot_clone_viability(clone_kill, viability_var = "comb_viability")
} # }