Complete patient response visualization pipeline

Generates a comprehensive visualization panel for patient drug response prediction, including clone distribution, clone-level viability, response boxplot, and ROC curve. This is a convenience function that combines multiple plot functions.

Usage

plot_patient_response_panel(
  clone_distribution,
  clone_viability,
  exp_vs_pred,
  response_col = "response",
  viability_col = "comb_viability",
  predicted_col = "predicted_viability",
  weights_col = "weights",
  layout_matrix = NULL
)

Arguments

clone_distribution

Data frame. Clone weights per patient.

clone_viability

Data frame. Viability scores per clone.

exp_vs_pred

Data frame. Predicted vs observed response.

response_col

Character. Response column name. Default = "response".

viability_col

Character. Viability column name. Default = "comb_viability".

predicted_col

Character. Predicted values column name. Default = "predicted_viability".

weights_col

Character. Weights column name. Default = "weights".

layout_matrix

Matrix. Layout for grid.arrange. Default = NULL (auto).

Value

A gtable object from grid.arrange.

Examples

if (FALSE) { # \dontrun{
  # After running prediction pipeline
  panel <- plot_patient_response_panel(
    clone_distribution = clone_dist_df,
    clone_viability = clone_kill_df,
    exp_vs_pred = response_df
  )
  ggsave(panel, filename = "patient_response.pdf", height = 15, width = 10)
} # }