| cn_trainNorm | R Documentation | 
Exactly that.
cn_trainNorm(expTrain, stTrain, subNets, classList = NULL,
  dLevel = "description1", tVals = NULL, classWeight = FALSE,
  exprWeight = TRUE, sidCol = "sample_id", xmax = 1000,
  predSD = FALSE)
expTrain | 
 expression matrix  | 
stTrain | 
 sample table  | 
subNets | 
 named list of genes, one list per CTT, tct=>gene vector  | 
classList | 
 list of classifiers  | 
dLevel | 
 column name to group on  | 
tVals | 
 seful when debugging  | 
classWeight | 
 weight GRN status by importance of gene to classifier  | 
exprWeight | 
 weight GRN status by expression level of gene?  | 
sidCol | 
 sample id colname  | 
list of trainingScores, normVals, raw_scores, minVals, tVals=tVals
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