ccn_trainNorm: Figure out normalization factors for GRNs, and norm training...

In pcahan1/cancerCellNet: CellNet, for cancer

Figure out normalization factors for GRNs, and norm training data

Description

Exactly that.

Usage

ccn_trainNorm(
  expTrain,
  stTrain,
  subNets,
  classList = NULL,
  dLevel = "description1",
  tVals = NULL,
  classWeight = TRUE,
  exprWeight = FALSE,
  sidCol = "sample_id",
  xmax = 1000,
  meanNorm = FALSE
)

Arguments

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
xmax	the maximum raw score that a sample could receive per gene
meanNorm	normalize raw scores based on the lowest mean in a category

Value

list of trainingScores, normVals, raw_scores, minVals, tVals=tVals

pcahan1/cancerCellNet documentation built on July 16, 2022, 12:12 a.m.