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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