get.npci.distance.matrix: generate the divergence estimation based of fold change...
In fCI: f-divergence Cutoff Index for Differential Expression Analysis in Transcriptomics and Proteomics

Description Usage Arguments Details Value Note Author(s) References See Also Examples

generate the divergence estimation based of fold change cutoff values

get.npci.distance.matrix(npci.data, null.data.start, diff.data.start, choice = 2, rank.index.to.be.removed, expr.by.fold, ctr.indexes, trt.indexes, use.intersect = FALSE, symmetric.fold = TRUE, fold.cutoff.list)

`npci.data`
`null.data.start`
`diff.data.start`
`choice`
`rank.index.to.be.removed`
`expr.by.fold`
`ctr.indexes`
`trt.indexes`
`use.intersect`
`symmetric.fold`
`fold.cutoff.list`

TBD

divergence

A matrix of computed divergences

TBD

Shaojun Tang

http://software.steenlab.org/fCI/

TBD

data.file=data.frame(matrix(sample(3:100, 100*4, replace=TRUE), 100,4))
wt.index=c(1,2)
df.index=c(1,3)
npci=new("NPCI")
npci@wt.index=wt.index
npci@df.index=df.index
npci@sample.data.normalized=data.file
npci=initialize(npci)
npci=normalization(npci)
npci=populate(npci)

null.data.start=npci@null.data.start
diff.data.start=npci@diff.data.start
choice=2
rank.index.to.be.removed=npci@rank.index.to.be.removed
expr.by.fold=npci@expr.by.fold
ctr.indexes=npci@wt.index
trt.indexes=npci@df.index
use.intersect=FALSE
symmetric.fold=TRUE
fold.cutoff.list=npci@fold.cutoff.list

get.npci.distance.matrix(npci.data, null.data.start, diff.data.start, 
  choice = 2, rank.index.to.be.removed, expr.by.fold, ctr.indexes, trt.indexes, 
  use.intersect, symmetric.fold, fold.cutoff.list)