drugRank: Generate the list of ranked drug combinations

In timma: Target Inhibition Interaction using Maximization and Minimization Averaging

Description

A function to provide a list of drug combinations ranked by their synergy scores

Usage

drugRank(profile_select, predicted_matrix, sens)

Arguments

profile_select	the selected drug-target interaction data
predicted_matrix	the predicted efficacy matrix
sens	the drug sensitivity vector.

Value

a matrix contains the information about the list of drug combinations ranked by their synergy scores.

Author(s)

Jing Tang [e-mail]

References

Tang J, Karhinen L, Xu T, Szwajda A, Yadav B, Wennerberg K, Aittokallio T. Target inhibition networks: predicting selective combinations of druggable targets to block cancer survival pathways. PLOS Computational Biology 2013; 9: e1003226.

Examples

## Not run: 
data(tyner_interaction_binary)
data(tyner_sensitivity)
float<-sffsBinary(tyner_interaction_binary, tyner_sensitivity[, 1], max_k = 8)
k_select<-float$k_sel
x<-data.frame(tyner_interaction_binary)
kinase_names <- dimnames(x)[[2]]
select_kinase_names <- findSameSet(x, k_select, kinase_names)
gc_timma <- graycode3(length(k_select))
gc_names <- graycodeNames(length(k_select), select_kinase_names, gc_timma$gc_row, gc_timma$gc_col)
nr <- gc_names$nr
nc <- t(gc_names$nc)
timma_row <- nrow(nr) + nrow(nc)
timma_col <- ncol(nr) + ncol(nc)
timma <- array("", dim = c(timma_row, timma_col))
timma[(nrow(nc) + 1):timma_row, 1:ncol(nr)] <- nr
timma[1:nrow(nc), (ncol(nr) + 1):timma_col] <- nc
timma[(nrow(nc) + 1):timma_row, (ncol(nr) + 1):timma_col] <- float$timma$dummy
profile_select<-data.frame(tyner_interaction_binary)[, k_select]
drug_combo_rank<-drugRank(profile_select, timma, tyner_sensitivity[, 1])

## End(Not run)

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