get.npci.distance.matrix {fCI}R Documentation

generate the divergence estimation based of fold change cutoff values

Description

generate the divergence estimation based of fold change cutoff values

Usage

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)

Arguments

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

Details

TBD

Value

divergence

A matrix of computed divergences

Note

TBD

Author(s)

Shaojun Tang

References

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

See Also

TBD

Examples



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)
[Package fCI version 1.12.0 Index]