get_predictions: Produce Predictions on an Unseen Dataset

In ICBioMark: Data-Driven Design of Targeted Gene Panels for Estimating Immunotherapy Biomarkers

Description

A function taking a predictive model(s) and new observations, and applying the predictive model to them to return predicted biomarker values.

Usage

get_predictions(pred_model, new_data, s = NULL, max_panel_length = NULL)

Arguments

pred_model	(list) A predictive model as fitted by pred_first_fit(), pred_refit_panel() or pred_refit_range().
new_data	(list) A new dataset, containing a matrix of observations and a list of sample IDs. Likely comes from the 'train', 'val' or 'test' argument of a call to get_mutation_tables().
s	(numeric) If producing predictions for a single panel, s chooses which panel (column in a pred_fit object) to produce predictions for.
max_panel_length	(numeric) If producing predictions for a single panel, maximum panel length to specify that panel.

Value

A list with two elements:

• predictions, a matrix containing a row for each sample and a column for each panel.

• panel_lengths, a vector containing the length of each panel.

Examples

example_predictions <- get_predictions(example_refit_range, new_data =
example_tables$val)

ICBioMark documentation built on Nov. 15, 2021, 5:09 p.m.