nem.discretize: Discretize perturbation data according to control experiments
In cbg-ethz/pcNEM: Probabilistic combinatorial nested effects model

Description Usage Arguments Details Value Note Author(s) References See Also Examples

discretizes raw data to define effects of interventions with respect to wildtype/control measurements

1	nem.discretize(D,neg.control=NULL,pos.control=NULL,nfold=2,cutoff=0:10/10, pCounts=20, empPval=.05, verbose=TRUE)

`D`	matrix with experiments as columns and effect reporters as rows
`neg.control`	either indices of columns in `D` or a matrix with the same number of rows as `D`
`pos.control`	either indices of columns in `D` or a matrix with the same number of rows as `D`
`nfold`	fold-change between neg. and pos. controls for selecting effect reporters. Default: 2
`cutoff`	a (vector of) cutoff value(s) weighting the pos. controls versus the neg. controls. Default: 0:10/10
`pCounts`	pseudo-counts to guard against unreasonable low error estimates
`empPval`	empirical p-value cutoff for effects if only one control is available
`verbose`	Default: TRUE

Chooses cutoff such that separation between negative and positive controls becomes optimal.

`dat`	discretized data matrix
`pos`	discretized positive controls [in the two-controls setting]
`neg`	discretized negative controls [in the two-controls setting]
`sel`	effect reporters selected [in the two-controls setting]
`cutoff`	error rates for different cutoff values [in the two-controls setting]
`para`	estimated error rates [in the two-controls setting]

preliminary! will be developed to be more generally applicable

Florian Markowetz

Markowetz F, Bloch J, Spang R, Non-transcriptional pathway features reconstructed from secondary effects of RNA interference, Bioinformatics, 2005

BoutrosRNAi2002

   # discretize Boutros data as in
   # Markowetz et al, 2005
   data("BoutrosRNAi2002")
   disc <- nem.discretize(BoutrosRNAiExpression,neg.control=1:4,pos.control=5:8,cutoff=.7)
   stopifnot(disc$dat==BoutrosRNAiDiscrete[,9:16])