buildFeederObjectDynamic: Building Feeder-Object for the integration to the PKN

Description Usage Arguments Details Value Author(s) Examples

View source: R/buildFeederObjectDynamic.R

Description

This function estimates the possible mechanisms of interactions to be added to the PKN from a database of interactions for improving the fitting cost.

Usage

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buildFeederObjectDynamic(model = model, cnolist = cnolist, indices = indices, database = database, pathLength = 2, DDN = TRUE, k = 2, measErr = c(0.1, 0))

Arguments

cnolist

a cnolist structure, as produced by makeCNOlist

model

a model as returned by readSIF. Alternatively, the filename can also be provided

indices

a list of indices of poorly fitted measurements as returned from identifyMisfitIndices

database

a database of interactions which can be optionally provided as an interaction matrix with 3 or 4 colums (source of interaction, sign of interaction, target of interaction and optionally a weight value from 0 to 1 indicating the significance of that interaction in the database). Default: database=NULL

pathLength

a path length parameter for the maximal path length of additional interactions to search for in the database. Default: pathLength = 3

DDN

a parameter indicating whether integrating links inferred from the Data-Driven FEED approach. Default: DDN = TRUE

k

a parameter that determine the threshold of significancy of the effect of stimuli and inhibitors, default to 2

measErr

a 2 value vector (err1, err2) defining the error model of the data as sd^2 = err1^2 + (err2*data)^2, default to c(0.1, 0)

Details

The function identifies and proposes the new links to integrate in the PKN either either by means of the data-driven method from the FEED algorithm or from the provided database of interactions or from both of them.

Value

this function returns a list with fields:

Original PKN

the original PKN

Feed mechanisms

the list of proposed interactions to integrate to the PKN (if both the database and the data-driven method are considered by the user, the last mechanism corresponds to the data-driven approach)

Author(s)

E.Gjerga

Examples

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data(ToyModel_Gene, package="CNORfeeder")
data(CNOlistToy_Gene, package="CNORfeeder")
data(simData_toy,package="CNORfeeder")


feederObject = buildFeederObjectDynamic(model = model, cnolist = cnolist,
                                        indices = indices, database = database,
                                        DDN = TRUE, pathLength = 2)

saezlab/CellNOpt-Feeder documentation built on Jan. 23, 2020, 2:36 p.m.