simulateGRC: Simulate a gene regulatory circuit using RACIPE

In TheJacksonLaboratory/sRACIPE_dev: Systems biology tool to simulate gene regulatory circuits

Description

Simulate a gene regulatory circuit using its topology as the only input. It will generate an ensemble of random models.

Usage

simulateGRC(circuit = "inputs/test.tpo", config = "inputs/sRACIPE.cfg",
  anneal = FALSE, knockOut = NA_character_, numModels = 500,
  paramRange = 100, prodRateMin = 1, prodRateMax = 100,
  degRateMin = 0.1, degRateMax = 1, foldChangeMin = 1,
  foldChangeMax = 100, hillCoeffMin = 1L, hillCoeffMax = 6L,
  integrateStepSize = 0.02, simulationTime = 50, nIC = 1L,
  nNoise = 0L, initialNoise = 50, noiseScalingFactor = 0.5,
  shotNoise = 0, scaledNoise = FALSE, outputPrecision = 12L,
  printStart = 50, printInterval = 10, stepper = "RK4",
  thresholdModels = 10000, plots = FALSE, plotToFile = TRUE,
  genIC = TRUE, genParams = TRUE, integrate = TRUE,
  rkTolerance = 0.01)

Arguments

circuit	List or character. The file containing the circuit or the list returned by the function loadCircuit
config	(optional) data.frame or character. The file containing the configuration or the dataframe returned by the function loadConfig
anneal	(optional) Logical. Default FALSE. Whether to use annealing for stochastic simulations. If TRUE, the gene expressions at higher noise are used as initial conditions for simulations at lower noise.
knockOut	(optional) List of character or vector of characters. Simulation after knocking out one or more genes. To knock out all the genes in the circuit, use knockOut = "all". If it is a vector, then all the genes in the vector will be knocked out simultaneously.
numModels	(optional) Integer. Default 500. Number of random models to be simulated.
paramRange	(optional) numeric (0-100). Default 100. The relative range of parameters (production rate, degradation rate, fold change).
prodRateMin	(optional) numeric. Default 1. Minimum production rate.
prodRateMax	(optional) numeric. Default 100. Maximum production rate.
degRateMin	(optional) numeric. Default 0.1. Minimum degradation rate.
degRateMax	(optional) numeric. Default 1. Maximum degradation rate.
foldChangeMin	(optional) numeric. Default 1. Minimum fold change for interactions.
foldChangeMax	(optional) numeric. Default 100. Maximum fold change for interactions.
hillCoeffMin	(optional) integer. Default 1. Minimum hill coefficient.
hillCoeffMax	(optional) integer. Default 6. Maximum hill coefficient.
integrateStepSize	(optional) numeric. Default 0.02. step size for integration using "EM" and "RK4" steppers.
simulationTime	(optional) numeric. Total simulation time.
nIC	(optional) integer. Default 1. Number of initial conditions to be simulated for each model.
nNoise	(optional) integer. Default 0. Number of noise levels at which simulations are to be done. Use nNoise = 1 if simulations are to be carried out at a specific noise. If nNoise > 0, simulations will be carried out at nNoise levels as well as for zero noise. "EM" stepper will be used for simulations and any argument for stepper will be ignoired.
initialNoise	(optional) numeric. Default 50/sqrt(number of genes in the circuit). The initial value of noise for simulations. The noise value will decrease by a factor noiseScalingFactor at subsequent noise levels.
noiseScalingFactor	(optional) numeric (0-1) Default 0.5. The factor by which noise will be decreased when nNoise > 1.
shotNoise	(optional) numeric. Default 0. The ratio of shot noise to additive noise.
scaledNoise	(optional) logical. Default FALSE. Whether to scale the noise in each gene by its expected median expression across all models. If TRUE the noise in each gene will be proportional to its expression levels.
printStart	(optional) numeric (0-simulationTime). Default simulationTime The time from which the output should be recorded. Useful for time series analysis and studying the dynamics of a model for a particular initial condition.
printInterval	(optional) numeric (integrateStepSize- simulationTime - printStart). Default 10. The separation between two recorded time points.
stepper	(optional) Character. Stepper to be used for integrating the differential equations. The options include "EM" for Euler-Maruyama O(1), "RK4" for fourth order Runge-Kutta O(4) and "DP" for adaptive stepper based Dormand-Prince algorithm. The default method is "RK4" for deterministic simulations and the method defaults to "EM" for stochastic simulations.
thresholdModels	(optional) integer. Default 10000. The number of models to be used for calculating the thresholds for genes.
plots	(optional) logical Default TRUE. Whether to plot the simuated data.
plotToFile	(optional) Default FALSE. Whether to save the plots to a file.
genIC	(optional) logical. Default TRUE. Whether to generate the initial conditions. If FALSE, the initial conditions must be supplied as a dataframe to circuit$ic.
genParams	(optional) logical. Default TRUE. Whether to generate the parameters. If FALSE, the parameters must be supplied as a dataframe to circuit$params.
integrate	(optional) logical. Default TRUE. Whether to integrate the differential equations or not. If FALSE, the function will only generate the parameters and initial conditions. This can be used iteratively as one can fist generate the parameters and initial conditions and then modify these before using these modified values for integration. For example, this can be used to knockOut genes by changing the production rate and initial condition to zero.
rkTolerance	(optional) numeric. Default 0.01. Error tolerance for adaptive integration method.
outputPrecison	(optional) integer. Default 12. The decimal point precison of the output to be printed in the tmp folder.

Value

List. A list containing the circuit, parameters, initial conditions, simulated gene expressions, and simulation configuration.

Related Functions

simulateGRC, knockdownAnalysis, overExprAnalysis, plotData, calcHeatmapSimilarity

TheJacksonLaboratory/sRACIPE_dev documentation built on May 7, 2019, 8:16 a.m.