divergence.multivariate.distributions: estimate fCI divergence for given samples of aritrary...
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

estimate fCI divergence for given samples of aritrary dimensions

1	divergence.multivariate.distributions(null.data, diff.data, choice = 2)

`null.data`	the empirical null dataset (a dataframe of none-zero ratio values)
`diff.data`	the case-control dataset (a dataframe of none-zero ratio values)
`choice`	choice=1 => cross entropy choice=2 => Helligan distance choice=3 => KL distance

TBD

divergences

The estimated divergence given control-control and case- control expression ratios

TBD

Shaojun Tang

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

TBD

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null.data=data.frame(matrix(sample(seq(from=0.1,to=10, by=0.01), 100), 100,1))
diff.data=data.frame(matrix(sample(seq(from=0.1,to=10, by=0.01), 100), 100,1))
divergence.multivariate.distributions(null.data, diff.data, choice = 2)