Introduction | Data input | Importing sample data | Importing custom data | Summarizing Overlaps of Query Regions with Genomic Annotation Features | Querying the annotation file | Finding targeted gene types | Extending the annotation feature space | Plotting overlap counts between query regions and transcript features | Obtaining a table of overlap counts between query regions and genes | Profiling the coverage of query regions across transcript features | Coverage profile of query regions at feature boundaries | Coverage profile of query regions for all transcript features | Discriminative Motif Discovery | Calculating enriched motifs | motif analysis: getting motif summary statistics | Functional enrichment analysis | Generating a full report | A test run for human | A custom run for human | To turn off certain modules of the report | To run the pipeline for species other than human | To turn off verbose output and progress bars | Printing raw data generated by the runReport function | Acknowledgements
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:
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✨
DESCRIPTION |NEWS
card.svg |card.png
RCAS/json (API)
| # 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
Last updated from:966bdcbeaf. Checks:1 ERROR, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 278 | ||
| linux-devel-x86_64 | OK | 748 | ||
| source / vignettes | OK | 479 | ||
| linux-release-x86_64 | OK | 749 | ||
| macos-release-arm64 | OK | 525 | ||
| macos-oldrel-arm64 | OK | 600 | ||
| windows-devel | OK | 789 | ||
| windows-release | OK | 802 | ||
| windows-oldrel | OK | 791 | ||
| wasm-release | OK | 255 |
Exports:calculateCoverageProfilecalculateCoverageProfileFromTxdbcalculateCoverageProfileListcalculateCoverageProfileListFromTxdbcheckSeqDbcreateControlRegionscreateDBcreateOrthologousGeneSetListdeleteSampleDataFromDBdiscoverFeatureSpecificMotifsextractSequencesfindDifferentialMotifsfindEnrichedFunctionsgenerateKmersgetFeatureBoundaryCoveragegetFeatureBoundaryCoverageBingetFeatureBoundaryCoverageMultigetIntervalOverlapMatrixgetMotifSummaryTablegetPWMgetTargetedGenesTablegetTxdbFeaturesgetTxdbFeaturesFromGRangesimportBedimportBedFilesimportGtfparseMsigdbplotFeatureBoundaryCoverageprintMsigdbDatasetqueryGffretrieveOrthologsrunGSEArunMotifDiscoveryrunMotifRGrunReportrunReportMetaAnalysisrunTopGOsummarizeDatabaseContentsummarizeQueryRegionssummarizeQueryRegionsMulti
Dependencies:abindAnnotationDbiaskpassbase64encBHBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocIOBiocParallelbiomaRtBiostringsbitbit64bitopsblobBSgenomeBSgenome.Hsapiens.UCSC.hg19bslibcachemcigarilloclicliprcodetoolscowplotcpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArraydigestdplyrDTevaluatefarverfastmapfilelockfontawesomeformatRfsfutile.loggerfutile.optionsgenericsgenomationGenomeInfoDbGenomicAlignmentsGenomicFeaturesGenomicRangesggplot2gluegprofiler2gridBasegridExtragtablehighrhmshtmltoolshtmlwidgetshttrhttr2imputeIRangesisobandjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglambda.rlaterlatticelazyevallifecyclemagrittrMatrixMatrixGenericsmatrixStatsmemoisemimeopensslotelpbapplypheatmappillarpkgconfigplotlyplotrixplyrpngprettyunitsprogresspromisesproxypurrrR6rangerrappdirsRColorBrewerRcppRcppEigenRCurlreadrreshape2restfulrRhtslibrjsonrlangrmarkdownRsamtoolsRSQLitertracklayerS4ArraysS4VectorsS7sassscalesSeqinfoseqLogoseqPatternsnowSparseArraystringistringrSummarizedExperimentsystibbletidyrtidyselecttinytextxdbmakertzdbUCSC.utilsutf8vctrsviridisLitevroomwithrxfunXMLxml2XVectoryaml
The RNA Centric Analysis System Report
Last update: 2024-03-20
Started: 2016-04-19
How to do meta-analysis of CLIP-seq peaks from multiple samples with RCAS
Introduction | Preparing the inputs | Project Data File | GTF File (genome annotations) | Creating a RSQLite database | Generating a meta-analysis report | Acknowledgements
Last update: 2024-02-04
Started: 2018-02-26
