nem.cont.preprocess {nem} | R Documentation |
Calculates probabilities of data to define effects of interventions with respect to wildtype/control measurements
nem.cont.preprocess(D,neg.control=NULL,pos.control=NULL,nfold=2, influencefactor=NULL, 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 |
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 <URL: http://genomics.princeton.edu/~florian>
Markowetz F, Bloch J, Spang R, Non-transcriptional pathway features reconstructed from secondary effects of RNA interference, Bioinformatics, 2005
data("BoutrosRNAi2002") preprocessed <- nem.cont.preprocess(BoutrosRNAiExpression,neg.control=1:4,pos.control=5:8)