nem.cont.preprocess {nem}R Documentation

Calculate classification probabilities of perturbation data according to control experiments

Description

Calculates probabilities of data to define effects of interventions with respect to wildtype/control measurements

Usage

nem.cont.preprocess(D,neg.control=NULL,pos.control=NULL,nfold=2, influencefactor=NULL, empPval=.05, verbose=TRUE)

Arguments

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

Details

Determines the empirical distributions of the controls and calculates the probabilities of pertubartion data to belong to the control distribution(s).

Value

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

Note

preliminary! will be developed to be more generally applicable

Author(s)

Florian Markowetz <URL: http://genomics.princeton.edu/~florian>

References

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

See Also

BoutrosRNAi2002

Examples

   data("BoutrosRNAi2002")
   preprocessed <- nem.cont.preprocess(BoutrosRNAiExpression,neg.control=1:4,pos.control=5:8)

[Package nem version 2.2.1 Index]