Package: metaseqR2 1.25.0

Panagiotis Moulos

metaseqR2: An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms

Provides an interface to several normalization and statistical testing packages for RNA-Seq gene expression data. Additionally, it creates several diagnostic plots, performs meta-analysis by combinining the results of several statistical tests and reports the results in an interactive way.

Authors:Panagiotis Moulos [aut, cre]

metaseqR2_1.25.0.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
metaseqR2/json (API)

# Install 'metaseqR2' in R:
install.packages('metaseqR2', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pmoulos/metaseqr2/issues

Datasets:
  • hg19pvalues - P-values from human RNA-Seq data with two conditions, four samples
  • libsizeListMm9 - Mouse RNA-Seq data with two conditions, four samples
  • mm9GeneCounts - Mouse RNA-Seq data with two conditions, four samples
  • sampleListMm9 - Mouse RNA-Seq data with two conditions, four samples

On BioConductor:metaseqR2-1.25.0(bioc 3.24)metaseqR2-1.24.0(bioc 3.23)

softwaregeneexpressiondifferentialexpressionworkflowsteppreprocessingqualitycontrolnormalizationreportwritingrnaseqtranscriptionsequencingtranscriptomicsbayesianclusteringcellbiologybiomedicalinformaticsfunctionalgenomicssystemsbiologyimmunooncologyalternativesplicingdifferentialsplicingmultiplecomparisontimecoursedataimportatacseqepigeneticsregressionproprietaryplatformsgenesetenrichmentbatcheffectchipseq

6.38 score 8 stars 9 scripts 1 mentions 54 exports 230 dependencies

Last updated from:0bd17c42dc. Checks:1 FAILURE, 6 ERROR, 2 OK, 5 NOTE. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksFAILURE276
linux-devel-arm64ERROR503
linux-devel-x86_64ERROR655
source / vignettesOK568
linux-release-arm64ERROR530
linux-release-x86_64NOTE598
macos-release-arm64NOTE398
macos-release-x86_64NOTE610
macos-oldrel-arm64NOTE420
macos-oldrel-x86_64NOTE893
windows-develERROR522
windows-releaseERROR546
windows-oldrelERROR513
wasm-releaseOK249

Exports:buildAnnotationDatabasebuildCustomAnnotationcombineBonferronicombineHarmoniccombineMaxpcombineMinpcombineSimescombineWeightcreateSignalTracksdiagplotAvgFtddiagplotBoxplotdiagplotCordiagplotDeHeatmapdiagplotEdaseqdiagplotFiltereddiagplotFtddiagplotMdsdiagplotNoiseqdiagplotPairsdiagplotRocdiagplotVenndiagplotVolcanodownsampleCountsestimateAufcWeightsestimateSimParamsgetAnnotationgetDefaultsgetInstalledAnnotationsgetWeightsimportCustomAnnotationloadAnnotationmakeSimDataSdmakeSimDataTccmetaseqr2metaseqrPlotmetaTestnormalizeAbsseqnormalizeDeseqnormalizeDeseq2normalizeDssnormalizeEdaseqnormalizeEdgernormalizeNbpseqnormalizeNoiseqread2countreadTargetsstatAbsseqstatDeseqstatDeseq2statDssstatEdgerstatLimmastatNbpseqstatNoiseq

Dependencies:abindABSSeqaffyaffyioannotateAnnotationDbiaroma.lightaskpassassertthatassortheadbase64encbeachmatBHBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocIObiocmakeBiocManagerBiocParallelbiomaRtBiostringsbitbit64bitopsblobbookdownbootstrapBSgenomebslibbsseqcacachemcallrcaToolscigarilloclasscliclustercodetoolscolorspacecorrplotcpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArrayDelayedMatrixStatsdeldirdendextendDESeq2diagramdigestdir.expirydplyrDSSDTEDASeqedgeReggevaluatefarverfastmapfilelockFMStablefontawesomeforeachformatRfsfutile.loggerfutile.optionsfuturefuture.applygclusgenefiltergenericsGenomeInfoDbGenomicAlignmentsGenomicFeaturesGenomicRangesggplot2globalsgluegplotsgridExtragtablegtoolsh5mreadharmonicmeanpHDF5Arrayheatmaplyhighrhmshtmltoolshtmlwidgetshttrhttr2hwriterinterpipredIRangesisobanditeratorsjpegjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglambda.rlaterlatticelatticeExtralavalazyevallifecyclelimmalistenvlocfitlog4rmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeNBPSeqnlmennetnumDerivopensslotelpanderparallellypermutepillarpkgconfigplotlyplyrpngpreprocessCoreprettyunitsprocessxprodlimprogressprogressrpromisespspurrrpwalignqapqvalueR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRCurlregistryreshape2restfulrrhdf5rhdf5filtersRhdf5libRhtslibrjsonrlangrmarkdownrmdformatsrmetarpartRsamtoolsRSQLitertracklayerS4ArraysS4VectorsS7sassscalesSeqinfoseriationshapeShortReadsnowSparseArraysparseMatrixStatsSQUAREMstatmodstringistringrSummarizedExperimentSuppDistssurvcompsurvivalsurvivalROCsystibbletidyrtidyselecttinytexTSPtxdbmakerUCSC.utilsutf8vctrsveganVennDiagramviridisviridisLitevsnwebshotwithrxfunXMLxml2xtableXVectoryamlzoo

Building an annotation database for metaseqR2
Simple, flexible and reusable annotation for metaseqR2 pipeline | Supported organisms | Using the local database | Installation of metaseqR2 | Setup the database | Use the database | Add a custom annotation | A complete build | Annotations on-the-fly | Session Info
Rendered frommetaseqr2-annotation.Rmdusingknitr::rmarkdown

Last update: 2026-03-21
Started: 2019-09-23

Usage of the metaseqR2 package
RNA-Seq data analysis using mulitple statistical algorithms with metaseqR2 | Getting started | Installation | Introduction | Types of analyses performed with metaseqR2 | Data filtering | Running the metaseqr2 pipeline | Analysis at the gene level with gene counts | Analysis at the gene level with exon counts | Estimating p-value weights | Combining p-values from multiple tests | metaseqR2 components | Brief description | Backwards compatibility | The report | Summary | Quality control | Normalization | Statistics | Results | References | Genome browser tracks | List of required packages | Session Info
Rendered frommetaseqr2-statistics.Rmdusingknitr::rmarkdown

Last update: 2026-03-21
Started: 2019-09-23

Readme and manuals

Help Manual

Help pageTopics
Build a local annotation database for metaseqR2buildAnnotationDatabase
Import custom annotation to the metaseqR2 annotation database from GTF filebuildCustomAnnotation
Combine p-values with Bonferroni's methodcombineBonferroni
Combine p-values using weightscombineHarmonic
Combine p-values using the maximum p-valuecombineMaxp
Combine p-values using the minimum p-valuecombineMinp
Combine p-values with Simes' methodcombineSimes
Combine p-values using weightscombineWeight
Create bigWig signal trackscreateSignalTracks
Create average False (or True) Discovery curvesdiagplotAvgFtd
Boxplots wrapper for the metaseqR2 packagediagplotBoxplot
Summarized correlation plotsdiagplotCor
Diagnostic heatmap of differentially expressed genesdiagplotDeHeatmap
Diagnostic plots based on the EDASeq packagediagplotEdaseq
Diagnostic plot for filtered genesdiagplotFiltered
Create False (or True) Positive (or Negative) curvesdiagplotFtd
Multi-Dimensinal Scale plots or RNA-Seq samplesdiagplotMds
Diagnostic plots based on the NOISeq packagediagplotNoiseq
Massive X-Y, M-D correlation plotsdiagplotPairs
Create basic ROC curvesdiagplotRoc
Venn diagrams when performing meta-analysisdiagplotVenn
(Interactive) volcano plots of differentially expressed genesdiagplotVolcano
Downsample read countsdownsampleCounts
Estimate AUFC weightsestimateAufcWeights
Estimate negative binomial parameters from real dataestimateSimParams
Annotation downloadergetAnnotation
Default parameters for several metaseqr functionsgetDefaults
Load a metaseqR2 annotation elementgetInstalledAnnotations
Get precalculated statistical test weightsgetWeights
p-values from human RNA-Seq data with two conditions, four sampleshg19pvalues
Import a metaseqR2 custom annotation elementimportCustomAnnotation
Mouse RNA-Seq data with two conditions, four sampleslibsizeListMm9
Load a metaseqR2 annotation elementloadAnnotation
Create simulated counts using the Soneson-Delorenzi methodmakeSimDataSd
Create simulated counts using TCC packagemakeSimDataTcc
The main metaseqr2 pipelinemetaseqr2
Diagnostic plots for the metaseqR2 packagemetaseqrPlot
Meta-analysis using several RNA-Seq statisticsmetaTest
Mouse RNA-Seq data with two conditions, four samplesmm9GeneCounts
Normalization based on the ABSSeq packagenormalizeAbsseq
Normalization based on the DESeq packagenormalizeDeseq
Normalization based on the DESeq2 packagenormalizeDeseq2
Normalization based on the DSS packagenormalizeDss
Normalization based on the EDASeq packagenormalizeEdaseq
Normalization based on the edgeR packagenormalizeEdger
Normalization based on the NBPSeq packagenormalizeNbpseq
Normalization based on the NOISeq packagenormalizeNoiseq
SAM/BAM/BED file reader helper for the metaseqr2 pipelineread2count
Creates sample list and BAM/BED file list from filereadTargets
Mouse RNA-Seq data with two conditions, four samplessampleListMm9
Statistical testing with ABSSeqstatAbsseq
Statistical testing with DESeqstatDeseq
Statistical testing with DESeq2statDeseq2
Statistical testing with DSSstatDss
Statistical testing with edgeRstatEdger
Statistical testing with limmastatLimma
Statistical testing with NBPSeqstatNbpseq
Statistical testing with NOISeqstatNoiseq