Description Usage Arguments Details Value Note Author(s) References See Also Examples
Calculates probabilities of data to define effects of interventions with respect to wildtype/control measurements
1  | 
D | 
 matrix with experiments as columns and effect reporters as rows  | 
neg.control | 
 either indices of columns in   | 
pos.control | 
 either indices of columns in   | 
nfold | 
 fold-change between neg. and pos. controls for selecting effect reporters. Default: 2  | 
influencefactor | 
 factor multiplied onto the probabilities, so that all negative control genes are treated as influenced, usually automatically determined  | 
empPval | 
 empirical p-value cutoff for effects if only one control is available  | 
verbose | 
 Default: TRUE  | 
Determines the empirical distributions of the controls and calculates the probabilities of pertubartion data to belong to the control distribution(s).
dat | 
 data matrix  | 
pos | 
 positive controls [in the two-controls setting]  | 
neg | 
 negative controls [in the two-controls setting]  | 
sel | 
 effect reporters selected [in the two-controls setting]  | 
prob.influenced | 
 probability of a reporter to be influenced  | 
influencefactor | 
 factor multiplied onto the probabilities, so that all negative control genes are treated as influenced  | 
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
1 2  |    data("BoutrosRNAi2002")
   preprocessed <- nem.cont.preprocess(BoutrosRNAiExpression,neg.control=1:4,pos.control=5:8)
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