Package: RCAS 1.39.0

Bora Uyar

RCAS: RNA Centric Annotation System

RCAS is an R/Bioconductor package designed as a generic reporting tool for the functional analysis of transcriptome-wide regions of interest detected by high-throughput experiments. Such transcriptomic regions could be, for instance, signal peaks detected by CLIP-Seq analysis for protein-RNA interaction sites, RNA modification sites (alias the epitranscriptome), CAGE-tag locations, or any other collection of query regions at the level of the transcriptome. RCAS produces in-depth annotation summaries and coverage profiles based on the distribution of the query regions with respect to transcript features (exons, introns, 5'/3' UTR regions, exon-intron boundaries, promoter regions). Moreover, RCAS can carry out functional enrichment analyses and discriminative motif discovery.

Authors:Bora Uyar [aut, cre], Dilmurat Yusuf [aut], Ricardo Wurmus [aut], Altuna Akalin [aut]

RCAS_1.39.0.tar.gz
RCAS_1.39.0.zip(r-4.7)RCAS_1.39.0.zip(r-4.6)RCAS_1.39.0.zip(r-4.5)
RCAS_1.39.0.tgz(r-4.6-any)RCAS_1.39.0.tgz(r-4.5-any)
RCAS_1.39.0.tar.gz(r-4.7-any)RCAS_1.39.0.tar.gz(r-4.6-any)
RCAS_1.39.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
RCAS/json (API)
NEWS

# Install 'RCAS' in R:
install.packages('RCAS', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • gff - Sample GFF file imported as a GRanges object
  • queryRegions - Sample BED file imported as a GRanges object

On BioConductor:RCAS-1.39.0(bioc 3.24)RCAS-1.38.0(bioc 3.23)

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

softwaregenetargetmotifannotationmotifdiscoverygotranscriptomicsgenomeannotationgenesetenrichmentcoverage

6.14 score 1 packages 29 scripts 591 downloads 8 mentions 40 exports 147 dependencies

Last updated from:966bdcbeaf. Checks:1 ERROR, 9 OK. Indexed: yes.

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Exports:calculateCoverageProfilecalculateCoverageProfileFromTxdbcalculateCoverageProfileListcalculateCoverageProfileListFromTxdbcheckSeqDbcreateControlRegionscreateDBcreateOrthologousGeneSetListdeleteSampleDataFromDBdiscoverFeatureSpecificMotifsextractSequencesfindDifferentialMotifsfindEnrichedFunctionsgenerateKmersgetFeatureBoundaryCoveragegetFeatureBoundaryCoverageBingetFeatureBoundaryCoverageMultigetIntervalOverlapMatrixgetMotifSummaryTablegetPWMgetTargetedGenesTablegetTxdbFeaturesgetTxdbFeaturesFromGRangesimportBedimportBedFilesimportGtfparseMsigdbplotFeatureBoundaryCoverageprintMsigdbDatasetqueryGffretrieveOrthologsrunGSEArunMotifDiscoveryrunMotifRGrunReportrunReportMetaAnalysisrunTopGOsummarizeDatabaseContentsummarizeQueryRegionssummarizeQueryRegionsMulti

Dependencies:abindAnnotationDbiaskpassbase64encBHBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocIOBiocParallelbiomaRtBiostringsbitbit64bitopsblobBSgenomeBSgenome.Hsapiens.UCSC.hg19bslibcachemcigarilloclicliprcodetoolscowplotcpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArraydigestdplyrDTevaluatefarverfastmapfilelockfontawesomeformatRfsfutile.loggerfutile.optionsgenericsgenomationGenomeInfoDbGenomicAlignmentsGenomicFeaturesGenomicRangesggplot2gluegprofiler2gridBasegridExtragtablehighrhmshtmltoolshtmlwidgetshttrhttr2imputeIRangesisobandjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglambda.rlaterlatticelazyevallifecyclemagrittrMatrixMatrixGenericsmatrixStatsmemoisemimeopensslotelpbapplypheatmappillarpkgconfigplotlyplotrixplyrpngprettyunitsprogresspromisesproxypurrrR6rangerrappdirsRColorBrewerRcppRcppEigenRCurlreadrreshape2restfulrRhtslibrjsonrlangrmarkdownRsamtoolsRSQLitertracklayerS4ArraysS4VectorsS7sassscalesSeqinfoseqLogoseqPatternsnowSparseArraystringistringrSummarizedExperimentsystibbletidyrtidyselecttinytextxdbmakertzdbUCSC.utilsutf8vctrsviridisLitevroomwithrxfunXMLxml2XVectoryaml

How to do meta-analysis of CLIP-seq peaks from multiple samples with RCAS

Rendered fromRCAS.metaAnalysis.vignette.Rmdusingknitr::rmarkdownon May 31 2026.

Last update: 2024-02-04
Started: 2018-02-26

The RNA Centric Analysis System Report

Rendered fromRCAS.vignette.Rmdusingknitr::rmarkdownon May 31 2026.

Last update: 2024-03-20
Started: 2016-04-19

Readme and manuals

Help Manual

Help pageTopics
calculateCoverageProfilecalculateCoverageProfile
calculateCoverageProfileFromTxdbcalculateCoverageProfileFromTxdb
calculateCoverageProfileListcalculateCoverageProfileList
calculateCoverageProfileListFromTxdbcalculateCoverageProfileListFromTxdb
checkSeqDbcheckSeqDb
createControlRegionscreateControlRegions
createDBcreateDB
createOrthologousMsigdbDataset This function is deprecated. For functional enrichment analysis, use findEnrichedFunctions.createOrthologousGeneSetList
deleteSampleDataFromDBdeleteSampleDataFromDB
discoverFeatureSpecificMotifsdiscoverFeatureSpecificMotifs
extractSequencesextractSequences
Find Differential MotifsfindDifferentialMotifs
findEnrichedFunctionsfindEnrichedFunctions
Generate K-mersgenerateKmers
getFeatureBoundaryCoveragegetFeatureBoundaryCoverage
getFeatureBoundaryCoverageBingetFeatureBoundaryCoverageBin
getFeatureBoundaryCoverageMultigetFeatureBoundaryCoverageMulti
getIntervalOverlapMatrixgetIntervalOverlapMatrix
getMotifSummaryTablegetMotifSummaryTable
getPWMgetPWM
getTargetedGenesTablegetTargetedGenesTable
getTxdbFeaturesgetTxdbFeatures
getTxdbFeaturesFromGRangesgetTxdbFeaturesFromGRanges
Sample GFF file imported as a GRanges objectgff
importBedimportBed
importBedFilesimportBedFiles
importGtfimportGtf
parseMsigdbparseMsigdb
plotFeatureBoundaryCoverageplotFeatureBoundaryCoverage
Print MSIGDB Dataset to a fileprintMsigdbDataset
queryGffqueryGff
Sample BED file imported as a GRanges objectqueryRegions
retrieveOrthologsretrieveOrthologs
runGSEArunGSEA
runMotifDiscoveryrunMotifDiscovery
run motifRGrunMotifRG
Generate a RCAS Report for a list of transcriptome-level segmentsrunReport
runReportMetaAnalysisrunReportMetaAnalysis
runTopGOrunTopGO
summarizeDatabaseContentsummarizeDatabaseContent
summarizeQueryRegionssummarizeQueryRegions
summarizeQueryRegionsMultisummarizeQueryRegionsMulti