timmaCategoryWeighted: Predicting drug sensitivity with multi-class drug-target...

In timma: Target Inhibition Interaction using Maximization and Minimization Averaging

Description

A function to predict the drug sensitivity with multi-class drug-target interaction data using the one.sided and weighted TIMMA model

Usage

timmaCategoryWeighted(drug_target_profile, sens, loo = TRUE, class)

Arguments

drug_target_profile	the drug-target interaction data. See timma.
sens	a drug sensitivity vector.
loo	a logical value indicating whether to use the leave-one-out cross-validation in the model selection process. By default, loo = TRUE.
class	the number of classes in the drug-target interaction data

Value

A list containing the following components:

dummy	the predicted efficacy for target combinations that can be found from the training data
error	the prediction errors
prediction	predicted drug sensitivity

Author(s)

Liye He [e-mail]

Examples

## Not run: 
profile<-data(tyner_interaction_multiclass)
sensitivity<-data(tyner_sensitivity)
results<-timmaCategoryWeighted(profile[, 1:6], sensitivity[,1], class = 6)

## End(Not run)

timma documentation built on May 2, 2019, 1:10 p.m.