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 1.10.0 Index]