nem.cont.preprocess: Calculate classification probabilities of perturbation data...

In cbg-ethz/pcNEM: Probabilistic combinatorial nested effects model

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

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)

cbg-ethz/pcNEM documentation built on Sept. 27, 2019, 8:58 a.m.