npci.gene.by.pvalues: find most signficantly change fCI targets
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

identify the genes that change most significantly using inverse of log ratio the smaller the results, the more signficant the changes.

1	npci.gene.by.pvalues(npci.data, gene.indexes, ctr.indexes, trt.indexes)

`npci.data`	a data frame containing non-zero numeric values (the data frame must contain more than one row and one column)
`gene.indexes`	the row ids of genes used for p-value calculation
`ctr.indexes`	The wild type sample column indexes in the matrix, i.e. 1,2
`trt.indexes`	The experimental sample column indexes in the matrix, i.e. 1,2

TBD

pvalues

a vector of pvalues

TBD

Shaojun Tang

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

TBD

  npci.data=data.frame(matrix(sample(3:100, 100*4, replace=TRUE), 100,4))
  gene.indexes=sample(1:97, 25)
  ctr.indexes=c(1,2)
  trt.indexes=c(3,4)
  npci.gene.by.pvalues(npci.data, gene.indexes, ctr.indexes, trt.indexes)