runDynamicFeeder: Modelling the integrated PKN with CNORode

Description Usage Arguments Details Value Author(s) Examples

View source: R/runDynamicFeeder.R

Description

This function evaluates the effects of possible feeder mechanisms which are added to the PKN.

Usage

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runDynamicFeeder(cnolist = cnolist, integratedModel = integratedModel, ode_parameters = ode_parameters, paramsSSm = paramsSSm, penFactor_k = 2)

Arguments

cnolist

a cnolist structure, as produced by makeCNOlist

integratedModel

the integrated model as returned from integrateLinks

ode_parameters

a list with the ODEs parameter information. Obtained with createLBodeContPars

penFactor_k

a penalty factor for the new integrated links obtained from the FEED algorithm and which are not present in the database (if the database was given). Default: penFactor_k = 100

penFactor_tau

a penalty factor for all the new nodes integrated in the PKN. Default: penFactor_tau = 1

penFactorPIN_k

a penalty factor for the new integrated links and which are present in the database (for the cases when the database was given). Default: penFactorPIN_k = 10

paramsSSm

a list of SSm parameters. default is the list returned by defaultParametersSSm

Details

This function evaluates the effects of possible feeder mechanisms which are added to the PKN. The analysis performed is a simple CNORode analysis over the integrated network where the newly integrated links are supposed to be penalised more than the links present in the original PKN. If a database of interactions is also provided by the user, than normally the links inferred from the FEED mechanism and which re not present in the database should be more penalised than the ones that are. There is also the opportunity to weight database interactions based on their relevance (i.e. number of resources, etc.).

Value

this function returns a list with fields:

Parameters

the inferred optimal ODE parameters

Integrated-Model

the integrated model which was optimised

CNOlist

the CNOlist object containing the data

Author(s)

E.Gjerga

Examples

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

paramsSSm=defaultParametersSSm()

ode_parameters=createLBodeContPars(integratedModel$model, LB_n = 1, LB_k = 0,
                                   LB_tau = 0, UB_n = 3, UB_k = 1, UB_tau = 1, default_n = 3,
                                   default_k = 0.5, default_tau = 0.01, opt_n = FALSE, opt_k = TRUE,
                                   opt_tau = TRUE, random = TRUE)
                                   
result = runDynamicFeeder(cnolist = cnolist, integratedModel = integratedModel,
                          ode_parameters = ode_parameters, paramsSSm = paramsSSm,
                          penFactor_k = 2, penFactorPIN_k = 0.1, penFactor_tau = 1)
                                  

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