Package: RcisTarget 1.23.1

Gert Hulselmans

RcisTarget: RcisTarget Identify transcription factor binding motifs enriched on a list of genes or genomic regions

RcisTarget identifies transcription factor binding motifs (TFBS) over-represented on a gene list. In a first step, RcisTarget selects DNA motifs that are significantly over-represented in the surroundings of the transcription start site (TSS) of the genes in the gene-set. This is achieved by using a database that contains genome-wide cross-species rankings for each motif. The motifs that are then annotated to TFs and those that have a high Normalized Enrichment Score (NES) are retained. Finally, for each motif and gene-set, RcisTarget predicts the candidate target genes (i.e. genes in the gene-set that are ranked above the leading edge).

Authors:Sara Aibar, Gert Hulselmans, Stein Aerts. Laboratory of Computational Biology. VIB-KU Leuven Center for Brain & Disease Research. Leuven, Belgium

RcisTarget_1.23.1.tar.gz
RcisTarget_1.23.1.zip(r-4.7-any)RcisTarget_1.23.1.zip(r-4.6-any)RcisTarget_1.23.1.zip(r-4.5-any)
RcisTarget_1.23.1.tgz(r-4.6-any)RcisTarget_1.23.1.tgz(r-4.5-any)
RcisTarget_1.23.1.tar.gz(r-4.7-any)RcisTarget_1.23.1.tar.gz(r-4.6-any)
RcisTarget_1.23.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RcisTarget/json (API)

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

Bug tracker:https://github.com/aertslab/rcistarget/issues

Datasets:

On CRAN:

Conda:

generegulationmotifannotationtranscriptomicstranscriptiongenesetenrichmentgenetarget

6.92 score 50 stars 278 scripts 26 exports 113 dependencies

Last updated from:cddbff8ccb. Checks:7 ERROR, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develERROR376
source / vignettesOK335
linux-releaseERROR374
macos-releaseERROR280
macos-oldrelERROR283
windows-develERROR326
windows-releaseERROR271
windows-oldrelERROR293
wasm-releaseOK167

Exports:addLogoaddMotifAnnotationaddSignificantGenesaucScorescalcAUCcisTargetcolnamesconvertToTargetRegionsgetAUCgetColumnNamesgetDbRegionsLocgetMaxRankgetMotifAnnotationgetNumColsInDBgetRankinggetRowNamesgetSignificantGenesimportAnnotationsimportRankingsncolnrowrankingRcisTargetreRankrownamesshowshowLogo

Dependencies:abindannotateAnnotationDbiarrowaskpassassertthatAUCellbase64encBiobaseBiocBaseUtilsBiocGenericsBiostringsbitbit64blobbslibcachemclicpp11crayoncrosstalkcurldata.tableDBIDelayedArrayDelayedMatrixStatsdigestdplyrevaluatefarverfastmapfontawesomefsgenericsGenomeInfoDbGenomicRangesggplot2gluegraphGSEABasegtablehighrhtmltoolshtmlwidgetshttrIRangesisobandjquerylibjsonliteKEGGRESTkernlabknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimemixtoolsnlmeopensslotelpillarpkgconfigplotlypngpromisespurrrR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcpprlangrmarkdownRSQLiteS4ArraysS4VectorsS7sassscalessegmentedSeqinfoSparseArraysparseMatrixStatsstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselecttinytexUCSC.utilsutf8vctrsviridisLitewithrxfunXMLxtableXVectoryamlzoo

Motif enrichment in genomic regions
1. Prepare/download the input regions | 2. Load the RcisTarget databases | 3. Run the analysis

Last update: 2024-03-04
Started: 2021-03-24

RcisTarget: Transcription factor binding motif enrichment
What is RcisTarget? | Overview of the workflow | Before starting | Setup | Some tips... | Help | Reports | Running RcisTarget | Input: Gene sets | Required databases | Gene-motif rankings | Motif annotations | Database example (subset) | Running the analysis | Advanced: Execute step by step | 1. Calculate enrichment | 2. Select significant motifs and/or annotate to TFs | 3. Identify the genes with the best enrichment for each Motif | Output | Follow up examples | TFs annotated to the enriched motifs | Building a network | sessionInfo()

Last update: 2022-10-31
Started: 2021-03-24

Motif enrichment with background
1. Select the gene/region set to analyze & the "background" | 2. Create the background-ranking | 3. Run RcisTarget with this new ranking

Last update: 2022-04-05
Started: 2021-03-24

Readme and manuals

Help Manual

Help pageTopics
Add motif logo to RcisTarget results tableaddLogo
Add motif annotationaddMotifAnnotation
Add significant genesaddSignificantGenes addSignificantGenes,character-method addSignificantGenes,GeneSet-method addSignificantGenes,GeneSetCollection-method addSignificantGenes,list-method getSignificantGenes getSignificantGenes,character-method getSignificantGenes,factor-method getSignificantGenes,GeneSet-method getSignificantGenes,GeneSetCollection-method getSignificantGenes,list-method
Class to store the AUC scores for RcisTarget.aucScores aucScores-class getAUC getAUC,aucScores-method show,aucScores-method
Calculate AUCcalcAUC calcAUC,character-method calcAUC,GeneSet-method calcAUC,GeneSetCollection-method calcAUC,list-method
cisTargetcisTarget
convertToTargetRegionsconvertToTargetRegions
Genomic location for the database regionsdbRegionsLoc dbRegionsLoc_hg19_v9 dbRegionsLoc_mm9_v9
Gets the region location for the given database IDs.getDbRegionsLoc
Get motif annotationgetMotifAnnotation
Imports the annotations of motifs to transcription factorsimportAnnotations
Import the motif databases for RcisTarget.getColumnNames getRowNames importRankings
Annotations of Motifs to TFsmotifAnnotations motifAnnotations_dmel motifAnnotations_dmel_v8 motifAnnotations_dmel_v9 motifAnnotations_hgnc motifAnnotations_hgnc_v8 motifAnnotations_hgnc_v9 motifAnnotations_mgi motifAnnotations_mgi_v8 motifAnnotations_mgi_v9
Class to store the motif databases for RcisTarget.colnames,rankingRcisTarget-method getMaxRank getMaxRank,rankingRcisTarget-method getNumColsInDB getNumColsInDB,rankingRcisTarget-method getRanking getRanking,rankingRcisTarget-method ncol,rankingRcisTarget-method nrow,rankingRcisTarget-method rankingRcisTarget rankingRcisTarget-class rownames,rankingRcisTarget-method show,rankingRcisTarget-method
Re-rank RcisTarget rankingreRank
Show RcisTarget as HTMLshowLogo