Package: tigre 1.67.0

Antti Honkela

tigre: Transcription factor Inference through Gaussian process Reconstruction of Expression

The tigre package implements our methodology of Gaussian process differential equation models for analysis of gene expression time series from single input motif networks. The package can be used for inferring unobserved transcription factor (TF) protein concentrations from expression measurements of known target genes, or for ranking candidate targets of a TF.

Authors:Antti Honkela, Pei Gao, Jonatan Ropponen, Miika-Petteri Matikainen, Magnus Rattray, Neil D. Lawrence

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tigre/json (API)

# Install 'tigre' in R:

install.packages('tigre', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ahonkela/tigre/issues

Datasets:

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

On BioConductor:tigre-1.67.0(bioc 3.24)tigre-1.66.0(bioc 3.23)

microarray timecourse geneexpression transcription generegulation networkinference bayesian

4.38 score 7 scripts 2 mentions 183 exports 43 dependencies

Last updated from:247a9c1047. Checks:1 ERROR, 11 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	310
linux-devel-arm64	NOTE	326
linux-devel-x86_64	NOTE	406
source / vignettes	OK	518
linux-release-arm64	NOTE	344
linux-release-x86_64	NOTE	444
macos-release-arm64	NOTE	211
macos-release-x86_64	NOTE	499
macos-oldrel-arm64	NOTE	202
macos-oldrel-x86_64	NOTE	476
windows-devel	NOTE	294
windows-release	NOTE	272
windows-oldrel	NOTE	279
wasm-release	OK	291

Exports:baseloglikelihoods baseloglikelihoods<-boundedTransform CGoptim cgpdisimExpandParam cgpdisimExtractParam cgpdisimGradient cgpdisimLogLikeGradients cgpdisimLogLikelihood cgpdisimObjective cgpdisimUpdateProcesses cgpsimExpandParam cgpsimExtractParam cgpsimGradient cgpsimLogLikeGradients cgpsimLogLikelihood cgpsimObjective cgpsimOptimise cgpsimUpdateProcesses cmpndKernCompute cmpndKernDiagCompute cmpndKernDiagGradX cmpndKernDisplay cmpndKernExpandParam cmpndKernExtractParam cmpndKernGradient cmpndKernGradX cmpndKernParamInit datasetName datasetName<-disimKernCompute disimKernDiagCompute disimKernDisplay disimKernExpandParam disimKernExtractParam disimKernGradient disimKernParamInit disimXdisimKernCompute disimXdisimKernGradient disimXrbfKernCompute disimXrbfKernGradient disimXsimKernCompute disimXsimKernGradient experimentSet experimentSet<-export.scores expTransform gammaPriorExpandParam gammaPriorExtractParam gammaPriorGradient gammaPriorLogProb gammaPriorParamInit generateModels genes genes<-gpdisimCreate gpdisimDisplay gpdisimExpandParam gpdisimExtractParam gpdisimGradient gpdisimLogLikeGradients gpdisimLogLikelihood gpdisimObjective gpdisimUpdateProcesses GPLearn GPPlot GPRankTargets GPRankTFs gpsimCreate gpsimDisplay gpsimExpandParam gpsimExtractParam gpsimGradient gpsimLogLikeGradients gpsimLogLikelihood gpsimObjective gpsimUpdateProcesses invgammaPriorExpandParam invgammaPriorExtractParam invgammaPriorGradient invgammaPriorLogProb invgammaPriorParamInit is.GPModel kernCompute kernCreate kernDiagCompute kernDiagGradX kernDisplay kernExpandParam kernExtractParam kernGradient kernGradX kernParamInit kernPriorGradient kernPriorLogProb knownTargets knownTargets<-lnDiffErfs loglikelihoods loglikelihoods<-mlpKernCompute mlpKernDiagGradX mlpKernExpandParam mlpKernExtractParam mlpKernGradient mlpKernGradX mlpKernParamInit modelArgs modelArgs<-modelDisplay modelExpandParam modelExtractParam modelGradient modelLogLikelihood modelObjective modelOptimise modelStruct modelStruct<-modelTieParam modelType modelUpdateProcesses multiKernCompute multiKernDiagCompute multiKernDisplay multiKernExpandParam multiKernExtractParam multiKernGradient multiKernParamInit optimiDefaultConstraint optimiDefaultOptions params params<-plotTimeseries priorCreate priorExpandParam priorExtractParam priorGradient priorLogProb priorParamInit processData processRawData rbfKernCompute rbfKernDiagCompute rbfKernDisplay rbfKernExpandParam rbfKernExtractParam rbfKernGradient rbfKernParamInit SCGoptim sharedModel sharedModel<-sigmoidTransform simKernCompute simKernDiagCompute simKernDisplay simKernExpandParam simKernExtractParam simKernGradient simKernParamInit simXrbfKernCompute simXrbfKernGradient simXsimKernCompute simXsimKernGradient TF TF<-translateKernCompute translateKernDiagCompute translateKernExpandParam translateKernExtractParam translateKernGradient translateKernParamInit var.exprs var.exprs<-whiteKernCompute whiteKernDiagCompute whiteKernDisplay whiteKernExpandParam whiteKernExtractParam whiteKernGradient whiteKernParamInit whiteXwhiteKernCompute whiteXwhiteKernGradient write.scores

Dependencies:annotate AnnotationDbi askpass Biobase BiocGenerics Biostrings bit bit64 bitops blob cachem caTools cli cpp11 crayon curl DBI fastmap generics glue gplots gtools httr IRanges jsonlite KEGGREST KernSmooth lifecycle memoise mime openssl pkgconfig png R6 rlang RSQLite S4Vectors Seqinfo sys vctrs XML xtable XVector

tigre User Guide

Rendered fromtigre.Rnwusingutils::Sweave

Last update: 2020-03-01
Started: 2012-09-25

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
tigre - Transcription factor Inference through Gaussian process Reconstruction of Expression	tigre-package tigre
Fragment of 12 time point Drosophila embryonic development microarray gene expression time series	drosophila_gpsim_fragment
Fragment of 12 time point Drosophila embryonic development microarray gene expression time series	drosophila_mmgmos_fragment
Export results to an SQLite database	export.scores
Class to contain time series expression assays	ExpressionTimeSeries ExpressionTimeSeries-class initialize,ExpressionTimeSeries-method var.exprs var.exprs,ExpressionTimeSeries-method var.exprs<- var.exprs<-,ExpressionTimeSeries-method
Constrains a parameter.	boundedTransform expTransform sigmoidTransform
Generating models with the given data	generateModels
Fit a GP model	GPLearn
A container for gpsim models	GPModel GPModel-class initialize,GPModel-method is.GPModel is.GPModel,GPModel-method modelStruct modelStruct,GPModel-method modelStruct<- modelStruct<-,GPModel,list-method modelType modelType,GPModel-method show,GPModel-method
Plot GP(DI)SIM models	GPPlot
Ranking possible target genes or regulators	GPRankTargets GPRankTFs
Create a GPSIM/GPDISIM model.	gpdisimCreate gpsimCreate
Compute the kernel given the parameters and X.	cmpndKernCompute cmpndKernDiagCompute disimKernCompute disimKernDiagCompute disimXdisimKernCompute disimXrbfKernCompute disimXsimKernCompute kernCompute kernDiagCompute mlpKernCompute multiKernCompute multiKernDiagCompute rbfKernCompute rbfKernDiagCompute simKernCompute simKernDiagCompute simXrbfKernCompute simXsimKernCompute translateKernCompute translateKernDiagCompute whiteKernCompute whiteKernDiagCompute whiteXwhiteKernCompute
Initialise a kernel structure.	cmpndKernParamInit disimKernParamInit gammaPriorParamInit invgammaPriorParamInit kernCreate kernParamInit mlpKernParamInit multiKernParamInit priorCreate priorParamInit rbfKernParamInit simKernParamInit translateKernParamInit whiteKernParamInit
Compute the gradient of the kernel wrt X.	cmpndKernDiagGradX cmpndKernGradX kernDiagGradX kernGradX mlpKernDiagGradX mlpKernGradX
Compute the gradient wrt the kernel parameters.	cmpndKernGradient disimKernGradient disimXdisimKernGradient disimXrbfKernGradient disimXsimKernGradient kernGradient mlpKernGradient multiKernGradient rbfKernGradient simKernGradient simXrbfKernGradient simXsimKernGradient translateKernGradient whiteKernGradient whiteXwhiteKernGradient
Helper function for computing the log of difference	lnDiffErfs
Display a model.	cmpndKernDisplay disimKernDisplay gpdisimDisplay gpsimDisplay kernDisplay modelDisplay multiKernDisplay rbfKernDisplay simKernDisplay whiteKernDisplay
Update a model structure with new parameters or update the posterior processes.	cgpdisimExpandParam cgpdisimUpdateProcesses cgpsimExpandParam cgpsimUpdateProcesses cmpndKernExpandParam disimKernExpandParam gammaPriorExpandParam gpdisimExpandParam gpdisimUpdateProcesses gpsimExpandParam gpsimUpdateProcesses invgammaPriorExpandParam kernExpandParam mlpKernExpandParam modelExpandParam modelUpdateProcesses multiKernExpandParam priorExpandParam rbfKernExpandParam simKernExpandParam translateKernExpandParam whiteKernExpandParam
Extract the parameters of a model.	cgpdisimExtractParam cgpsimExtractParam cmpndKernExtractParam disimKernExtractParam gammaPriorExtractParam gpdisimExtractParam gpsimExtractParam invgammaPriorExtractParam kernExtractParam mlpKernExtractParam modelExtractParam multiKernExtractParam priorExtractParam rbfKernExtractParam simKernExtractParam translateKernExtractParam whiteKernExtractParam
Model log-likelihood/objective error function and its gradient.	cgpdisimGradient cgpdisimLogLikeGradients cgpdisimLogLikelihood cgpdisimObjective cgpsimGradient cgpsimLogLikeGradients cgpsimLogLikelihood cgpsimObjective gammaPriorGradient gammaPriorLogProb gpdisimGradient gpdisimLogLikeGradients gpdisimLogLikelihood gpdisimObjective gpsimGradient gpsimLogLikeGradients gpsimLogLikelihood gpsimObjective invgammaPriorGradient invgammaPriorLogProb kernPriorGradient kernPriorLogProb modelGradient modelLogLikelihood modelObjective priorGradient priorLogProb
Tie parameters of a model together.	modelTieParam
Returns function for parameter constraint.	optimiDefaultConstraint
Plot ExpressionTimeSeries data	plotTimeseries
Processing expression time series	processData processRawData
Optimise the given function using (scaled) conjugate gradients.	CGoptim cgpsimOptimise modelOptimise optimiDefaultOptions SCGoptim
Class "scoreList"	baseloglikelihoods baseloglikelihoods,scoreList-method baseloglikelihoods<- baseloglikelihoods<-,scoreList,numeric-method c,scoreList-method datasetName datasetName,scoreList-method datasetName<- datasetName<-,scoreList,character-method experimentSet experimentSet,scoreList-method experimentSet<- experimentSet<-,scoreList,character-method genes genes,scoreList-method genes<- genes<-,scoreList,list-method knownTargets knownTargets,scoreList-method knownTargets<- knownTargets<-,scoreList,character-method length,scoreList-method loglikelihoods loglikelihoods,scoreList-method loglikelihoods<- loglikelihoods<-,scoreList,numeric-method modelArgs modelArgs,scoreList-method modelArgs<- modelArgs<-,scoreList,list-method params params,scoreList-method params<- params<-,scoreList,list-method scoreList scoreList-class sharedModel sharedModel,scoreList-method sharedModel<- sharedModel<-,scoreList,list-method show,scoreList-method sort,scoreList-method TF TF,scoreList-method TF<- TF<-,scoreList,character-method write.scores write.scores,scoreList-method [,scoreList,ANY-method [,scoreList-method