insilicosystemargs: Constructor function for the 'insilicosystemsargs' class.

Description Usage Arguments Details Value Examples

View source: R/args_classes.R

Description

Constructor function for the insilicosystemsargs class, with default values for the parameters if not provided by the user.

Usage

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insilicosystemargs(
  G = 10,
  ploidy = 2,
  PC.p = 0.7,
  PC.TC.p = NULL,
  PC.TL.p = NULL,
  PC.RD.p = NULL,
  PC.PD.p = NULL,
  PC.PTM.p = NULL,
  PC.MR.p = NULL,
  NC.TC.p = NULL,
  NC.TL.p = NULL,
  NC.RD.p = NULL,
  NC.PD.p = NULL,
  NC.PTM.p = NULL,
  TC.pos.p = 0.5,
  TL.pos.p = 0.5,
  PTM.pos.p = 0.5,
  basal_transcription_rate_samplingfct = NULL,
  basal_translation_rate_samplingfct = NULL,
  basal_RNAlifetime_samplingfct = NULL,
  basal_protlifetime_samplingfct = NULL,
  TC.PC.outdeg.distr = "powerlaw",
  TC.NC.outdeg.distr = "powerlaw",
  TC.PC.outdeg.exp = 3,
  TC.NC.outdeg.exp = 5,
  TC.PC.indeg.distr = "powerlaw",
  TC.NC.indeg.distr = "powerlaw",
  TC.PC.autoregproba = 0.2,
  TC.NC.autoregproba = 0,
  TC.PC.twonodesloop = FALSE,
  TC.NC.twonodesloop = FALSE,
  TCbindingrate_samplingfct = NULL,
  TCunbindingrate_samplingfct = NULL,
  TCfoldchange_samplingfct = NULL,
  TL.PC.outdeg.distr = "powerlaw",
  TL.NC.outdeg.distr = "powerlaw",
  TL.PC.outdeg.exp = 4,
  TL.NC.outdeg.exp = 6,
  TL.PC.indeg.distr = "powerlaw",
  TL.NC.indeg.distr = "powerlaw",
  TL.PC.autoregproba = 0.2,
  TL.NC.autoregproba = 0,
  TL.PC.twonodesloop = FALSE,
  TL.NC.twonodesloop = FALSE,
  TLbindingrate_samplingfct = NULL,
  TLunbindingrate_samplingfct = NULL,
  TLfoldchange_samplingfct = NULL,
  RD.PC.outdeg.distr = "powerlaw",
  RD.NC.outdeg.distr = "powerlaw",
  RD.PC.outdeg.exp = 4,
  RD.NC.outdeg.exp = 6,
  RD.PC.indeg.distr = "powerlaw",
  RD.NC.indeg.distr = "powerlaw",
  RD.PC.autoregproba = 0.2,
  RD.NC.autoregproba = 0,
  RD.PC.twonodesloop = FALSE,
  RD.NC.twonodesloop = FALSE,
  RDregrate_samplingfct = NULL,
  PD.PC.outdeg.distr = "powerlaw",
  PD.NC.outdeg.distr = "powerlaw",
  PD.PC.outdeg.exp = 4,
  PD.NC.outdeg.exp = 6,
  PD.PC.indeg.distr = "powerlaw",
  PD.NC.indeg.distr = "powerlaw",
  PD.PC.autoregproba = 0.2,
  PD.NC.autoregproba = 0,
  PD.PC.twonodesloop = FALSE,
  PD.NC.twonodesloop = FALSE,
  PDregrate_samplingfct = NULL,
  PTM.PC.outdeg.distr = "powerlaw",
  PTM.NC.outdeg.distr = "powerlaw",
  PTM.PC.outdeg.exp = 4,
  PTM.NC.outdeg.exp = 6,
  PTM.PC.indeg.distr = "powerlaw",
  PTM.NC.indeg.distr = "powerlaw",
  PTM.PC.autoregproba = 0.2,
  PTM.NC.autoregproba = 0,
  PTM.PC.twonodesloop = FALSE,
  PTM.NC.twonodesloop = FALSE,
  PTMregrate_samplingfct = NULL,
  regcomplexes = "prot",
  regcomplexes.p = 0.3,
  regcomplexes.size = 2,
  complexesformationrate_samplingfct = NULL,
  complexesdissociationrate_samplingfct = NULL
)

Arguments

G

Integer. Number of genes in the system. Default value is 10.

ploidy

Numeric. The ploidy of the system, i.e. how many copies of each gene are present in the system. Default value is 2.

PC.p

Numeric. Probability of each gene to be a protein-coding gene. Default value is 0.7.

PC.TC.p

Numeric. Probability of a protein-coding gene to be a regulator of transcription. Default value is 0.4 (see details).

PC.TL.p

Numeric. Probability of a protein-coding gene to be a regulator of translation. Default value is 0.3 (see details).

PC.RD.p

Numeric. Probability of a protein-coding gene to be a regulator of RNA decay. Default value is 0.1 (see details).

PC.PD.p

Numeric. Probability of a protein-coding gene to be a regulator of protein decay. Default value is 0.1 (see details).

PC.PTM.p

Numeric. Probability of a protein-coding gene to be a regulator of protein post-translational modification. Default value is 0.05 (see details).

PC.MR.p

Numeric. Probability of a protein-coding gene to be a metabolic enzyme. Default value is 0.05 (see details).

NC.TC.p

Numeric. Probability of a noncoding gene to be a regulator of transcription. Default value is 0.3 (see details).

NC.TL.p

Numeric. Probability of a noncoding gene to be a regulator of translation. Default value is 0.3 (see details).

NC.RD.p

Numeric. Probability of a noncoding gene to be a regulator of RNA decay. Default value is 0.3 (see details).

NC.PD.p

Numeric. Probability of a noncoding gene to be a regulator of protein decay. Default value is 0.05 (see details).

NC.PTM.p

Numeric. Probability of a noncoding gene to be a regulator of protein post-translational modification. Default value is 0.05 (see details).

TC.pos.p

Numeric. Probability of a regulation targeting gene transcription to be positive. Default value is 0.5.

TL.pos.p

Numeric. Probability of a regulation targeting gene translation to be positive. Default value is 0.5.

PTM.pos.p

Numeric. Probability of a regulation targeting protein post-translational modification to be positive (i.e the targeted protein is transformed into its modified form, as opposed to the modified protein being transformed back into its original form). Default value is 0.5.

basal_transcription_rate_samplingfct

Function from which the transcription rates of genes are sampled (input x is the required sample size). Default value is a function returning (10^v)/3600, with v a vector of size x sampled from a normal distribution with mean of 3 and sd of 0.5.

basal_translation_rate_samplingfct

Function from which the translation rates of genes are sampled (input x is the required sample size). Default value is a function returning (10^v)/3600, with v a vector of size x sampled from a normal distribution with mean of 2.146 and sd of 0.7.

basal_RNAlifetime_samplingfct

Function from which the transcript lifetimes are sampled (input x is the required sample size). Default value is a function returning (10^v)*3600, with v a vector of size x sampled from a normal distribution with mean of 0.95 and sd of 0.2.

basal_protlifetime_samplingfct

Function from which the protein lifetime are sampled (input x is the required sample size). Default value is a function returning (10^v)*3600, with v a vector of size x sampled from a normal distribution with mean of 1.3 and sd of 0.4.

TC.PC.outdeg.distr

Form of the distribution of the number of targets (out-degree) of protein regulators in the transcription regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

TC.NC.outdeg.distr

Form of the distribution of the number of targets (out-degree) of noncoding regulators in the transcription regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

TC.PC.outdeg.exp

Numeric. Exponent of the distribution for the out-degree of the protein regulators in the transcription regulation graph. Default value is 3.

TC.NC.outdeg.exp

Numeric. Exponent of the distribution for the out-degree of the noncoding regulators in the transcription regulation graph. Default value is 5.

TC.PC.indeg.distr

Type of preferential attachment for the targets of protein regulators in the transcription regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

TC.NC.indeg.distr

Type of preferential attachment for the targets of noncoding regulators in the transcription regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

TC.PC.autoregproba

Numeric. Probability of protein regulators to perform autoregulation in the transcription regulation graph. Default value is 0.2.

TC.NC.autoregproba

Numeric. Probability of noncoding regulators to perform autoregulation in the transcription regulation graph. Default value is 0.

TC.PC.twonodesloop

Logical. Are 2-nodes loops authorised in the transcription regulation graph with protein regulators? Default value is FALSE.

TC.NC.twonodesloop

Logical. Are 2-nodes loops authorised in the transcription regulation graph with noncoding regulators? Default value is FALSE.

TCbindingrate_samplingfct

Function from which the binding rates of transcription regulators on their targets are sampled (input means is a vector of length equal to the required sample size, giving for each edge (regulatory interaction) for which a binding rate is being sampled the value of the sampled unbinding rate divided by the steady-state abundance of the regulator in absence of any regulation in the system). Default value is a function returning 10^v, where v is a vector with the same length as means whose elements are sampled from a truncated normal distribution with mean equal to the log10 of the corresponding element in means, and sd = 0.1, the minimum authorised value being the log10 of the corresponding element in means.

TCunbindingrate_samplingfct

Function from which the unbinding rates of transcription regulators from their target are sampled (input x is the required sample size). Default value is a function returning 10^v, with v a vector of size x sampled from a normal distribution with mean of -3 and sd of 0.2.

TCfoldchange_samplingfct

Function from which the transcription fold change induced by a bound regulator is sampled (input x is the required sample size). Default value is a truncated normal distribution with a mean of 3, sd of 10 and minimum authorised value of 1.5.

TL.PC.outdeg.distr

Form of the distribution of the number of targets (out-degree) of protein regulators in the translation regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

TL.NC.outdeg.distr

Form of the the distribution of the number of targets (out-degree) of noncoding regulators in the translation regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

TL.PC.outdeg.exp

Numeric. Exponent of the distribution for the out-degree of the protein regulators in the translation regulation graph. Default value is 4.

TL.NC.outdeg.exp

Numeric. Exponent of the distribution for the out-degree of the noncoding regulators in the translation regulation graph. Default value is 6.

TL.PC.indeg.distr

Type of preferential attachment for the targets of protein regulators in the translation regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

TL.NC.indeg.distr

Type of preferential attachment for the targets of noncoding regulators in the translation regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

TL.PC.autoregproba

Numeric. Probability of protein regulators to perform autoregulation in the translation regulation graph. Default value is 0.2.

TL.NC.autoregproba

Numeric. Probability of noncoding regulators to perform autoregulation in the translation regulation graph. Default value is 0.

TL.PC.twonodesloop

Logical. Are 2-nodes loops authorised in the translation regulation graph with protein regulators? Default value is FALSE.

TL.NC.twonodesloop

Logical. Are 2-nodes loops authorised in the translation regulation graph with noncoding regulators? Default value is FALSE.

TLbindingrate_samplingfct

Function from which the binding rate of translation regulators on target are sampled (input means is a vector of length equal to the required sample size, giving for each edge (regulatory interaction) for which a binding rate is being sampled the value of the sampled unbinding rate divided by the steady-state abundance of the regulator in absence of any regulation in the system). Default value is a function returning 10^v, where v is a vector with the same length as means whose elements are sampled from a truncated normal distribution with mean equal to the log10 of the corresponding element in means, and sd = 0.1, the minimum authorised value being the log10 of the corresponding element in means.

TLunbindingrate_samplingfct

Function from which the unbinding rate of translation regulators from target are sampled (input x is the required sample size). Default value is a function returning 10^v, with v a vector of size x sampled from a normal distribution with mean of -3 and sd of 0.2.

TLfoldchange_samplingfct

Function from which the translation fold change induced by a bound regulator are sampled (input x is the required sample size). Default value is a truncated normal distribution with a mean of 3, sd of 10 and minimum authorised value of 1.5.

RD.PC.outdeg.distr

Form of the distribution of the number of targets (out-degree) of protein regulators in the RNA decay regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

RD.NC.outdeg.distr

Form of the the distribution of the number of targets (out-degree) of noncoding regulators in the RNA decay regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

RD.PC.outdeg.exp

Numeric. Exponent of the distribution for the out-degree of the protein regulators in the RNA decay regulation graph. Default value is 4.

RD.NC.outdeg.exp

Numeric. Exponent of the distribution for the out-degree of the noncoding regulators in the RNA decay regulation graph. Default value is 6.

RD.PC.indeg.distr

Type of preferential attachment for the targets of protein regulators in the RNA decay graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

RD.NC.indeg.distr

Type of preferential attachment for the targets of noncoding regulators in the RNA decay graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

RD.PC.autoregproba

Numeric. Probability of protein regulators to perform autoregulation in the RNA decay regulation graph. Default value is 0.2.

RD.NC.autoregproba

Numeric. Probability of noncoding regulators to perform autoregulation in the RNA decay regulation graph. Default value is 0.

RD.PC.twonodesloop

Logical. Are 2-nodes loops authorised in the RNA decay regulation graph with protein regulators? Default value is FALSE.

RD.NC.twonodesloop

Logical. Are 2-nodes loops authorised in the RNA decay regulation graph with noncoding regulators? Default value is FALSE.

RDregrate_samplingfct

Function from which the RNA decay rates of targets of RNA decay regulators are sampled (input x is the required sample size). Default value is a function returning 10^v, with v a vector of size x sampled from a normal distribution with mean of -5 and sd of 1.5.

PD.PC.outdeg.distr

Form of the distribution of the number of targets (out-degree) of protein regulators in the protein decay regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

PD.NC.outdeg.distr

Form of the the distribution of the number of targets (out-degree) of noncoding regulators in the protein decay regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

PD.PC.outdeg.exp

Numeric. Exponent of the distribution for the out-degree of the protein regulators in the protein decay regulation graph. Default value is 4.

PD.NC.outdeg.exp

Numeric. Exponent of the distribution for the out-degree of the noncoding regulators in the protein decay regulation graph. Default value is 6.

PD.PC.indeg.distr

Type of preferential attachment for the targets of protein regulators in the protein decay regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

PD.NC.indeg.distr

Type of preferential attachment for the targets of noncoding regulators in the protein decay graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

PD.PC.autoregproba

Numeric. Probability of protein regulators to perform autoregulation in the protein decay regulation graph. Default value is 0.2.

PD.NC.autoregproba

Numeric. Probability of noncoding regulators to perform autoregulation in the protein decay regulation graph. Default value is 0.

PD.PC.twonodesloop

Logical. Are 2-nodes loops authorised in the protein decay graph with protein regulators in the protein decay regulation graph? Default value is FALSE.

PD.NC.twonodesloop

Logical. Are 2-nodes loops authorised in the protein decay graph with noncoding regulators in the protein decay regulation graph? Default value is FALSE.

PDregrate_samplingfct

Function from which the protein decay rates of targets of protein decay regulators are sampled (input x is the required sample size). Default value is a function returning 10^v, with v a vector of size x sampled from a normal distribution with mean of -5 and sd of 1.5.

PTM.PC.outdeg.distr

Form of the distribution of the number of targets (out-degree) of protein regulators in the post-translational modification regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

PTM.NC.outdeg.distr

Form of the the distribution of the number of targets (out-degree) of noncoding regulators in the post-translational modification regulation graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

PTM.PC.outdeg.exp

Numeric. Exponent of the distribution for the out-degree of the protein regulators in the protein post-translational modification graph. Default value is 4.

PTM.NC.outdeg.exp

Numeric. Exponent of the distribution for the out-degree of the noncoding regulators in the protein post-translational modification graph. Default value is 6.

PTM.PC.indeg.distr

Type of preferential attachment for the targets of protein regulators in the protein post-translational modification graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

PTM.NC.indeg.distr

Type of preferential attachment for the targets of noncoding regulators in the protein post-translational modification graph; can be either "powerlaw" or "exponential". Default value is "powerlaw".

PTM.PC.autoregproba

Numeric. Probability of protein regulators to perform autoregulation. Default value is 0.2.

PTM.NC.autoregproba

Numeric. Probability of noncoding regulators to perform autoregulation. Default value is 0.

PTM.PC.twonodesloop

Logical. Are 2-nodes loops authorised in the protein post-translational modification graph with protein regulators? Default value is FALSE.

PTM.NC.twonodesloop

Logical. Are 2-nodes loops authorised in the protein post-translational modification graph with noncoding regulators? Default value is FALSE.

PTMregrate_samplingfct

Function from which the protein transformation rates of targets of post-translational modification regulators are sampled (input x is the required sample size). Default value is a function returning 10^v, with v a vector of size x sampled from a normal distribution with mean of -5 and sd of 1.5.

regcomplexes

Can the regulators controlling a common target form regulatory complexes in the different regulatory graphs? Can be 'none', 'prot' (only protein can form regulatory complexes) or 'both' (both regulatory RNAs and proteins can form regulatory complexes). Default value is "prot".

regcomplexes.p

Numeric. Probability that regulators controlling a common target form regulatory complexes; ignore if regcomplexes = 'none'. Default value is 0.3.

regcomplexes.size

Integer. Number of components of a regulatory complex; ignore if regcomplexes = 'none'. Default value is 2.

complexesformationrate_samplingfct

Function from which the formation rate of regulatory complexes are sampled (input x is the required sample size). Default value is a function returning 10^v, with v a vector of size x sampled from a normal distribution with mean of -3 and sd of 0.7.

complexesdissociationrate_samplingfct

Function from which the dissociation rate of regulatory complexes are sampled (input x is the required sample size). Default value is a function returning 10^v, with v a vector of size x sampled from a normal distribution with mean of 3 and sd of 0.9.

Details

For the protein-coding (and non-coding) biological function ratios (i.e. PC.TC.p, PC.TL.p, etc): if none of the ratios are provided, then they are set to their default values. Otherwise, if at least one value among the 6 (5 for noncoding genes) is set by the user:

Example: if the user sets PC.TC.p to 1 and PC.TL.p to 0.6, but does not provide any values for the other ratios, then PC.TC.p is set to 1/(1+0.6)=0.625, PC.TL.p to 0.6/(1+0.6)=0.375, and PC.RD.p, PC.PD.p, PC.PTM.p and PC.MR.p are all set to 0. Accordingly, if the user only sets NC.TC.p to 0.6, then NC.TL.p, NC.RD.p, NC.PD.p and NC.PTM.p are all set to 0.1.

Value

An object of the class insilicosystemargs, that is a named list of the different parameters.

Examples

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sysargs = insilicosystemargs(G = 15, PC.p = 0.2,
 basal_transcription_rate_samplingfct = function(x){runif(x, 0.1, 0.2)})

sismonr documentation built on Feb. 11, 2020, 9:07 a.m.