Function reference • pulseR

All functions
`MeanFormulas()`	Create list of formulas for expected read numbers
`PulseData()`	Create an object for pulse-change count data
`addDefault()`	Add default options if unset.
`addKnownToFormulas()`	Evaluate formulas in the environment of known params from the conditions
`amount()`	Create a formula object for the initial RNA level.
`amount_()`	Create a formula object for the initial RNA level.
`ciGene()` `ci()`	Estimate confidence intervals
`constructFormulas()`	Evaluate formulas according to parameters, given in the condition `data.frame`
`contaminate()`	Generate a new formula as a mixture of two
`degrade()`	Create a formula for RNA degradation
`degrade_()`	Create a formula for RNA degradation
`evaluateLikelihood()`	Computes logarithm of the likelihood function
`fitParams()` `fitParamsSeparately()` `fitNormFactors()` `fitModel()`	Fit model parameters
`generateTestDataFrom()`	Create a test count data
`grow()`	Creates a formula which describe evolution of RNA concentration
`growFrom0()`	Creates a formula which describe evolution of RNA concentration if the initial amount is 0.
`grow_()`	Creates a formula which describe evolution of RNA concentration
`guessMeans()`	Estimate initial guess for the mean expression level
`initParameters()`	Initialize first guess for the parameters
`ll()`	Creates a likelihood function for given parameter names
`llnormFactors()`	Create a likelihood function for optimisation of normalisation factors
`multiplyList()`	A helper to generate named lists
`normaliseBoundaries()`	Shape boundaries for the parameters in formulas.
`normaliseNormFactorBoundaries()`	Shape boundaries for the normalisation factors Create lower and upper boundaries with the same structure as the list of normalisation coefficients `interSampleCoeffs` in the `PulseData` object.
`plotPL()`	Plot the profile likeliihood
`predictExpression()`	Calculates mean read number estimations
`profileGene()` `profile()`	Estimate profile likelihood for gene parameters (all other fixed)
`plGene()` `pl()`	Return a profile likelihood function for further use.
`pulseRFractionData`	An example of count data for an experiment without spike-ins
`pulseRSpikeinsData`	An example of count data for an experiment with spike-ins
`runPL()`	Compute profile likelihood on the interval
`setBoundaries()`	Set optimization boundaries for the model parameters.
`setFittingOptions()`	Specify fitting options
`setTolerance()`	Set the stopping criteria in a form of the absolute changes during fitting iterations.
`shrinkList()`	Leave only one item per name

Reference

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