Composite scores for consensus clustering in R

Question

I am using ConsensusClusterPlus package in R for clustering my omic data. I want to use my clusters for regression.Is there a way to create composite scores if say i reduce 1000 genes to 7 clusters and use those 7 clusters for regression.

I tried to look at structure of cluster in R.

results = ConsensusClusterPlus(d1,maxK=maxK,reps=1000,pItem=0.8,pFeature=1, title=title,clusterAlg="hc",distance="pearson",seed=1262118388.71279,plot="png")

icl = calcICL(results,title=title,plot="png")

str(results[[7]])

List of 5
 $ consensusMatrix: num [1:40, 1:40] 1 0.689 0.976 1 1 ...
 $ consensusTree  :List of 7
  ..$ merge      : int [1:39, 1:2] -1 -5 -7 -8 -9 -10 -11 -12 -13 -14 ...
  ..$ height     : num [1:39] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ order      : int [1:40] 40 34 35 28 6 32 22 18 21 19 ...
  ..$ labels     : NULL
  ..$ method     : chr "average"
  ..$ call       : language hclust(d = as.dist(1 - fm), method = finalLinkage)
  ..$ dist.method: NULL
  ..- attr(*, "class")= chr "hclust"
 $ consensusClass : Named int [1:40] 1 1 1 1 1 2 1 1 1 1 ...
  ..- attr(*, "names")= chr [1:40] "CAR 12:0" "CAR 12:1" "CAR 13:0" "CAR 14:0" ...
 $ ml             : num [1:40, 1:40] 1 0.689 0.976 1 1 ...
 $ clrs           :List of 3
  ..$ : chr [1:40] "#A6CEE3" "#A6CEE3" "#A6CEE3" "#A6CEE3" ...
  ..$ : num 8
  ..$ : chr [1:7] "#A6CEE3" "#FB9A99" "#FF7F00" "#FDBF6F" ...

How to find composite scores ?