get.npci.distance.matrix {fCI} | R Documentation |
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 |
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null.data.start |
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diff.data.start |
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choice |
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rank.index.to.be.removed |
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expr.by.fold |
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ctr.indexes |
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trt.indexes |
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use.intersect |
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symmetric.fold |
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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)