tni.dpi.filter: Data Processing Inequality (DPI) filter.

Description Usage Arguments Value Author(s) See Also Examples

Description

This function takes a TNI object and returns the transcriptional network filtered by the data processing inequality algorithm.

Usage

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tni.dpi.filter(object, eps = 0, sizeThreshold = TRUE, minRegulonSize = 15, verbose = TRUE)

Arguments

object

a preprocessed object of class 'TNI' TNI-class evaluated by the methods tni.permutation and tni.bootstrap.

eps

a single numeric value (>= 0) specifying the threshold under which ARACNe algorithm should apply the dpi filter. If not available (i.e. 'eps = NA'), then the threshold is estimated from the empirical null distribution computed in the permutation and bootstrap steps. For additional details see aracne.

sizeThreshold

a logical value specifying if the 'minRegulonSize' argument should be used (when 'sizeThreshold = TRUE') or not (when 'sizeThreshold = FALSE'). It will have no effect when 'eps = NA'.

minRegulonSize

a single integer or numeric value. This argument prevents the DPI algorithm from removing additional targets from large unbalanced regulons, when the subset of either positive or negative targets is below the 'minRegulonSize'.

verbose

a single logical value specifying to display detailed messages (when 'verbose = TRUE') or not (when 'verbose = FALSE').

Value

a mutual information matrix in the slot "results" containing a dpi-filtered transcriptional network, see 'tn.dpi' option in tni.get.

Author(s)

Mauro Castro

See Also

TNI-class

Examples

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data(tniData)

## Not run: 

# preprocessing
rtni <- tni.constructor(expData=tniData$expData, 
        regulatoryElements=c("PTTG1","E2F2","FOXM1","E2F3","RUNX2"), 
        rowAnnotation=tniData$rowAnnotation)
        
# permutation analysis (infers the reference/relevance network)
rtni <- tni.permutation(rtni)

# dpi filter (infers the transcriptional network)
rtni <- tni.dpi.filter(rtni)


## End(Not run)

RTN documentation built on Nov. 12, 2020, 2:02 a.m.