timma (version 1.2.0)

drugRank: Generate the list of ranked drug combinations

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.

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

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])