Package: RTN 2.29.0

Mauro Castro

RTN: RTN: Reconstruction of Transcriptional regulatory Networks and analysis of regulons

A transcriptional regulatory network (TRN) consists of a collection of transcription factors (TFs) and the regulated target genes. TFs are regulators that recognize specific DNA sequences and guide the expression of the genome, either activating or repressing the expression the target genes. The set of genes controlled by the same TF forms a regulon. This package provides classes and methods for the reconstruction of TRNs and analysis of regulons.

Authors:Clarice Groeneveld [ctb], Gordon Robertson [ctb], Xin Wang [aut], Michael Fletcher [aut], Florian Markowetz [aut], Kerstin Meyer [aut], and Mauro Castro [aut]

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NEWS

# Install 'RTN' in R:
install.packages('RTN', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • pksData - Pre-processed datasets for the RTN package.
  • stni - A pre-processed TNI for demonstration purposes only.
  • tfsData - Pre-processed datasets for the RTN package.
  • tnaData - Pre-processed datasets for the RTN package.
  • tniData - Pre-processed datasets for the RTN package.

On BioConductor:RTN-2.29.0(bioc 3.20)RTN-2.28.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

bioconductor-package

36 exports 1.45 score 126 dependencies 2 dependents 17 mentions

Last updated 2 months agofrom:11f2811716

Exports:avs.evseavs.getavs.pevseavs.plot1avs.plot2avs.rvseavs.vsetna.gettna.gsea1tna.gsea2tna.mratna.plot.gsea1tna.plot.gsea2tni.alpha.adjusttni.annotate.regulonstni.annotate.samplestni.area3tni.bootstraptni.conditionaltni.constructortni.dpi.filtertni.gettni.graphtni.gsea2tni.overlap.genesetstni.permutationtni.plot.checkstni.plot.sretni.preprocesstni.prunetni.regulon.summarytni.replace.samplestni.sretni2tna.preprocessupgradeTNAupgradeTNI

Dependencies:abindaskpassbackportsbase64encBiobaseBiocGenericsbootbroombslibcachemcarcarDataclassclicolorspacecowplotcpp11crayoncrosstalkcurldata.tableDelayedArrayDerivdigestdoBydplyre1071evaluatefansifarverfastmapfontawesomefsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehighrhtmltoolshtmlwidgetshttrigraphinfotheoIRangesisobandjquerylibjsonlitekernlabKernSmoothknitrlabelinglaterlatticelazyevallifecyclelimmalme4magrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmemoisemgcvmicrobenchmarkmimeminetminqamixtoolsmodelrmunsellnlmenloptrnnetnumDerivopensslpbkrtestpheatmappillarpkgconfigplotlypromisesproxypurrrpwrquantregR6rappdirsRColorBrewerRcppRcppEigenRedeRrlangrmarkdownS4ArraysS4VectorssassscalessegmentedsnowSparseArraySparseMstatmodstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselecttinytexUCSC.utilsutf8vctrsviperviridisLitewithrxfunXVectoryamlzlibbioc

RTN: Reconstruction of Transcriptional regulatory Networks and analysis of regulons.

Clarice Groeneveld [ctb], Gordon Robertson [ctb], Xin Wang [aut], Michael Fletcher [aut], Florian Markowetz [aut], Kerstin Meyer [aut], and Mauro Castro [aut].

Rendered fromRTN.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2023-11-23
Started: 2017-09-29

Readme and manuals

Help Manual

Help pageTopics
Reconstruction and Analysis of Transcriptional Networks.RTN-package RTN
Class '"AVS"': an S4 class for variant set enrichment analysis.AVS-class avs.evse,AVS-method avs.get,AVS-method avs.pevse,AVS-method avs.rvse,AVS-method avs.vse,AVS-method
An eQTL/VSE pipeline for variant set enrichment analysis.avs.evse
Get information from individual slots in an AVS object.avs.get
An EVSE pipeline using precomputed eQTLs.avs.pevse
Plot results from AVS methods, single plots.avs.plot1
Plot results from AVS methods, multiple plots.avs.plot2
An rQTL/VSE pipeline for variant set enrichment analysis.avs.rvse
Variant set enrichment (VSE) analysis.avs.vse
Pre-processed datasets for the RTN package.pksData tfsData tnaData tniData
Class '"TNA"': an S4 class for Transcriptional Network Analysis.TNA-class tna.get,TNA-method tna.gsea1,TNA-method tna.gsea2,TNA-method tna.mra,TNA-method
Get information from individual slots in a TNA object.tna.get
One-tailed Gene Set Enrichment Analysis (GSEA) over a list of regulons.tna.gsea1
Two-tailed Gene Set Enrichment Analysis (GSEA) over a list of regulons.tna.gsea2
Master Regulator Analysis (MRA) over a list of regulons.tna.mra
Plot enrichment analyses from TNA objects.tna.plot.gsea1
Plot enrichment analyses from TNA objects.tna.plot.gsea2
Class '"TNI"': an S4 class for Transcriptional Network Inference.TNI-class tni.annotate.regulons,TNI-method tni.annotate.samples,TNI-method tni.area3,TNI-method tni.bootstrap,TNI-method tni.conditional,TNI-method tni.dpi.filter,TNI-method tni.get,TNI-method tni.graph,TNI-method tni.gsea2,TNI-method tni.overlap.genesets,TNI-method tni.permutation,TNI-method tni.preprocess,TNI-method tni.prune,TNI-method tni.regulon.summary,TNI-method tni.replace.samples,TNI-method tni.sre,TNI-method tni2tna.preprocess,TNI-method
Adjust the significance level for two datasets.tni.alpha.adjust
Annotate regulons with external gene set collections.tni.annotate.regulons
Annotate samples with external gene set collections.tni.annotate.samples
Compute regulon activity by calling aREA (analytic Rank-based Enrichment Analysis) algorithmtni.area3
Inference of consensus transcriptional networks.tni.bootstrap
Modulators of transcription factor (TF) activity assessed by conditional mutual information analysis.tni.conditional
A constructor for objects of class TNI.tni.constructor
A pre-processed TNI for demonstration purposes only.stni
Data Processing Inequality (DPI) filter.tni.dpi.filter
Get information from individual slots in a TNI object.tni.get
Compute a graph from TNI objects (Deprecated).tni.graph
Compute regulon activity by calling GSEA2 (two-tailed Gene Set Enrichment Analysis) algorithmtni.gsea2
Associate regulons with external gene set collections.tni.overlap.genesets
Inference of transcriptional networks.tni.permutation
Plot regulon target counts.tni.plot.checks
Plot Subgroup Regulon Enrichment for TNI-class objects.tni.plot.sre
A preprocessing function for objects of class TNI.tni.preprocess
Prune regulons to remove redundant targets for regulon activity analysistni.prune
Summary of regulon characteristics.tni.regulon.summary
Entry point to assess new samples with previously calculated regulons.tni.replace.samples
Subgroup Regulon Enrichment for TNI-class objects.tni.sre
A preprocessing function for objects of class TNI.tni2tna.preprocess
Upgrade objects of class TNI.upgradeTNA
Upgrade objects of class TNI.upgradeTNI