R: Transcription factor Inference through Gaussian process Reconstruction of Expression

# Transcription factor Inference through Gaussian process Reconstruction of Expression

## Documentation for package ‘tigre’ version 1.66.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

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"