Transcription factor Inference through Gaussian process Reconstruction of Expression

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Documentation for package ‘tigre’ version 1.62.0

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B C D E G I K L M O P R S T V W misc

tigre-package tigre - Transcription factor Inference through Gaussian process Reconstruction of Expression

-- B --

baseloglikelihoods Class "scoreList"
baseloglikelihoods-method Class "scoreList"
baseloglikelihoods<- Class "scoreList"
baseloglikelihoods<--method Class "scoreList"
boundedTransform Constrains a parameter.

-- C --

c-method Class "scoreList"
CGoptim Optimise the given function using (scaled) conjugate gradients.
cgpdisimExpandParam Update a model structure with new parameters or update the posterior processes.
cgpdisimExtractParam Extract the parameters of a model.
cgpdisimGradient Model log-likelihood/objective error function and its gradient.
cgpdisimLogLikeGradients Model log-likelihood/objective error function and its gradient.
cgpdisimLogLikelihood Model log-likelihood/objective error function and its gradient.
cgpdisimObjective Model log-likelihood/objective error function and its gradient.
cgpdisimUpdateProcesses Update a model structure with new parameters or update the posterior processes.
cgpsimExpandParam Update a model structure with new parameters or update the posterior processes.
cgpsimExtractParam Extract the parameters of a model.
cgpsimGradient Model log-likelihood/objective error function and its gradient.
cgpsimLogLikeGradients Model log-likelihood/objective error function and its gradient.
cgpsimLogLikelihood Model log-likelihood/objective error function and its gradient.
cgpsimObjective Model log-likelihood/objective error function and its gradient.
cgpsimOptimise Optimise the given function using (scaled) conjugate gradients.
cgpsimUpdateProcesses Update a model structure with new parameters or update the posterior processes.
cmpndKernCompute Compute the kernel given the parameters and X.
cmpndKernDiagCompute Compute the kernel given the parameters and X.
cmpndKernDiagGradX Compute the gradient of the kernel wrt X.
cmpndKernDisplay Display a model.
cmpndKernExpandParam Update a model structure with new parameters or update the posterior processes.
cmpndKernExtractParam Extract the parameters of a model.
cmpndKernGradient Compute the gradient wrt the kernel parameters.
cmpndKernGradX Compute the gradient of the kernel wrt X.
cmpndKernParamInit Initialise a kernel structure.

-- D --

datasetName Class "scoreList"
datasetName-method Class "scoreList"
datasetName<- Class "scoreList"
datasetName<--method Class "scoreList"
disimKernCompute Compute the kernel given the parameters and X.
disimKernDiagCompute Compute the kernel given the parameters and X.
disimKernDisplay Display a model.
disimKernExpandParam Update a model structure with new parameters or update the posterior processes.
disimKernExtractParam Extract the parameters of a model.
disimKernGradient Compute the gradient wrt the kernel parameters.
disimKernParamInit Initialise a kernel structure.
disimXdisimKernCompute Compute the kernel given the parameters and X.
disimXdisimKernGradient Compute the gradient wrt the kernel parameters.
disimXrbfKernCompute Compute the kernel given the parameters and X.
disimXrbfKernGradient Compute the gradient wrt the kernel parameters.
disimXsimKernCompute Compute the kernel given the parameters and X.
disimXsimKernGradient Compute the gradient wrt the kernel parameters.
drosophila_gpsim_fragment Fragment of 12 time point Drosophila embryonic development microarray gene expression time series
drosophila_mmgmos_fragment Fragment of 12 time point Drosophila embryonic development microarray gene expression time series

-- E --

experimentSet Class "scoreList"
experimentSet-method Class "scoreList"
experimentSet<- Class "scoreList"
experimentSet<--method Class "scoreList"
export.scores Export results to an SQLite database
ExpressionTimeSeries Class to contain time series expression assays
ExpressionTimeSeries-class Class to contain time series expression assays
expTransform Constrains a parameter.

-- G --

gammaPriorExpandParam Update a model structure with new parameters or update the posterior processes.
gammaPriorExtractParam Extract the parameters of a model.
gammaPriorGradient Model log-likelihood/objective error function and its gradient.
gammaPriorLogProb Model log-likelihood/objective error function and its gradient.
gammaPriorParamInit Initialise a kernel structure.
generateModels Generating models with the given data
genes Class "scoreList"
genes-method Class "scoreList"
genes<- Class "scoreList"
genes<--method Class "scoreList"
gpdisimCreate Create a GPSIM/GPDISIM model.
gpdisimDisplay Display a model.
gpdisimExpandParam Update a model structure with new parameters or update the posterior processes.
gpdisimExtractParam Extract the parameters of a model.
gpdisimGradient Model log-likelihood/objective error function and its gradient.
gpdisimLogLikeGradients Model log-likelihood/objective error function and its gradient.
gpdisimLogLikelihood Model log-likelihood/objective error function and its gradient.
gpdisimObjective Model log-likelihood/objective error function and its gradient.
gpdisimUpdateProcesses Update a model structure with new parameters or update the posterior processes.
GPLearn Fit a GP model
GPModel A container for gpsim models
GPModel-class A container for gpsim models
GPPlot Plot GP(DI)SIM models
GPRankTargets Ranking possible target genes or regulators
GPRankTFs Ranking possible target genes or regulators
gpsimCreate Create a GPSIM/GPDISIM model.
gpsimDisplay Display a model.
gpsimExpandParam Update a model structure with new parameters or update the posterior processes.
gpsimExtractParam Extract the parameters of a model.
gpsimGradient Model log-likelihood/objective error function and its gradient.
gpsimLogLikeGradients Model log-likelihood/objective error function and its gradient.
gpsimLogLikelihood Model log-likelihood/objective error function and its gradient.
gpsimObjective Model log-likelihood/objective error function and its gradient.
gpsimUpdateProcesses Update a model structure with new parameters or update the posterior processes.

-- I --

initialize-method Class to contain time series expression assays
initialize-method A container for gpsim models
invgammaPriorExpandParam Update a model structure with new parameters or update the posterior processes.
invgammaPriorExtractParam Extract the parameters of a model.
invgammaPriorGradient Model log-likelihood/objective error function and its gradient.
invgammaPriorLogProb Model log-likelihood/objective error function and its gradient.
invgammaPriorParamInit Initialise a kernel structure.
is.GPModel A container for gpsim models
is.GPModel-method A container for gpsim models

-- K --

kernCompute Compute the kernel given the parameters and X.
kernCreate Initialise a kernel structure.
kernDiagCompute Compute the kernel given the parameters and X.
kernDiagGradX Compute the gradient of the kernel wrt X.
kernDisplay Display a model.
kernExpandParam Update a model structure with new parameters or update the posterior processes.
kernExtractParam Extract the parameters of a model.
kernGradient Compute the gradient wrt the kernel parameters.
kernGradX Compute the gradient of the kernel wrt X.
kernParamInit Initialise a kernel structure.
kernPriorGradient Model log-likelihood/objective error function and its gradient.
kernPriorLogProb Model log-likelihood/objective error function and its gradient.
knownTargets Class "scoreList"
knownTargets-method Class "scoreList"
knownTargets<- Class "scoreList"
knownTargets<--method Class "scoreList"

-- L --

length-method Class "scoreList"
lnDiffErfs Helper function for computing the log of difference
loglikelihoods Class "scoreList"
loglikelihoods-method Class "scoreList"
loglikelihoods<- Class "scoreList"
loglikelihoods<--method Class "scoreList"

-- M --

mlpKernCompute Compute the kernel given the parameters and X.
mlpKernDiagGradX Compute the gradient of the kernel wrt X.
mlpKernExpandParam Update a model structure with new parameters or update the posterior processes.
mlpKernExtractParam Extract the parameters of a model.
mlpKernGradient Compute the gradient wrt the kernel parameters.
mlpKernGradX Compute the gradient of the kernel wrt X.
mlpKernParamInit Initialise a kernel structure.
modelArgs Class "scoreList"
modelArgs-method Class "scoreList"
modelArgs<- Class "scoreList"
modelArgs<--method Class "scoreList"
modelDisplay Display a model.
modelExpandParam Update a model structure with new parameters or update the posterior processes.
modelExtractParam Extract the parameters of a model.
modelGradient Model log-likelihood/objective error function and its gradient.
modelLogLikelihood Model log-likelihood/objective error function and its gradient.
modelObjective Model log-likelihood/objective error function and its gradient.
modelOptimise Optimise the given function using (scaled) conjugate gradients.
modelStruct A container for gpsim models
modelStruct-method A container for gpsim models
modelStruct<- A container for gpsim models
modelStruct<--method A container for gpsim models
modelTieParam Tie parameters of a model together.
modelType A container for gpsim models
modelType-method A container for gpsim models
modelUpdateProcesses Update a model structure with new parameters or update the posterior processes.
multiKernCompute Compute the kernel given the parameters and X.
multiKernDiagCompute Compute the kernel given the parameters and X.
multiKernDisplay Display a model.
multiKernExpandParam Update a model structure with new parameters or update the posterior processes.
multiKernExtractParam Extract the parameters of a model.
multiKernGradient Compute the gradient wrt the kernel parameters.
multiKernParamInit Initialise a kernel structure.

-- O --

optimiDefaultConstraint Returns function for parameter constraint.
optimiDefaultOptions Optimise the given function using (scaled) conjugate gradients.

-- P --

params Class "scoreList"
params-method Class "scoreList"
params<- Class "scoreList"
params<--method Class "scoreList"
plotTimeseries Plot ExpressionTimeSeries data
priorCreate Initialise a kernel structure.
priorExpandParam Update a model structure with new parameters or update the posterior processes.
priorExtractParam Extract the parameters of a model.
priorGradient Model log-likelihood/objective error function and its gradient.
priorLogProb Model log-likelihood/objective error function and its gradient.
priorParamInit Initialise a kernel structure.
processData Processing expression time series
processRawData Processing expression time series

-- R --

rbfKernCompute Compute the kernel given the parameters and X.
rbfKernDiagCompute Compute the kernel given the parameters and X.
rbfKernDisplay Display a model.
rbfKernExpandParam Update a model structure with new parameters or update the posterior processes.
rbfKernExtractParam Extract the parameters of a model.
rbfKernGradient Compute the gradient wrt the kernel parameters.
rbfKernParamInit Initialise a kernel structure.

-- S --

SCGoptim Optimise the given function using (scaled) conjugate gradients.
scoreList Class "scoreList"
scoreList-class Class "scoreList"
sharedModel Class "scoreList"
sharedModel-method Class "scoreList"
sharedModel<- Class "scoreList"
sharedModel<--method Class "scoreList"
show-method A container for gpsim models
show-method Class "scoreList"
sigmoidTransform Constrains a parameter.
simKernCompute Compute the kernel given the parameters and X.
simKernDiagCompute Compute the kernel given the parameters and X.
simKernDisplay Display a model.
simKernExpandParam Update a model structure with new parameters or update the posterior processes.
simKernExtractParam Extract the parameters of a model.
simKernGradient Compute the gradient wrt the kernel parameters.
simKernParamInit Initialise a kernel structure.
simXrbfKernCompute Compute the kernel given the parameters and X.
simXrbfKernGradient Compute the gradient wrt the kernel parameters.
simXsimKernCompute Compute the kernel given the parameters and X.
simXsimKernGradient Compute the gradient wrt the kernel parameters.
sort-method Class "scoreList"

-- T --

TF Class "scoreList"
TF-method Class "scoreList"
TF<- Class "scoreList"
TF<--method Class "scoreList"
tigre tigre - Transcription factor Inference through Gaussian process Reconstruction of Expression
translateKernCompute Compute the kernel given the parameters and X.
translateKernDiagCompute Compute the kernel given the parameters and X.
translateKernExpandParam Update a model structure with new parameters or update the posterior processes.
translateKernExtractParam Extract the parameters of a model.
translateKernGradient Compute the gradient wrt the kernel parameters.
translateKernParamInit Initialise a kernel structure.

-- V --

var.exprs Class to contain time series expression assays
var.exprs-method Class to contain time series expression assays
var.exprs<- Class to contain time series expression assays
var.exprs<--method Class to contain time series expression assays

-- W --

whiteKernCompute Compute the kernel given the parameters and X.
whiteKernDiagCompute Compute the kernel given the parameters and X.
whiteKernDisplay Display a model.
whiteKernExpandParam Update a model structure with new parameters or update the posterior processes.
whiteKernExtractParam Extract the parameters of a model.
whiteKernGradient Compute the gradient wrt the kernel parameters.
whiteKernParamInit Initialise a kernel structure.
whiteXwhiteKernCompute Compute the kernel given the parameters and X.
whiteXwhiteKernGradient Compute the gradient wrt the kernel parameters.
write.scores Class "scoreList"
write.scores-method Class "scoreList"

-- misc --

[-method Class "scoreList"