Package: markeR 1.3.0

Rita Martins-Silva

markeR: An R Toolkit for Evaluating Gene Signatures as Phenotypic Markers

markeR is an R package that provides a modular and extensible framework for the systematic evaluation of gene sets as phenotypic markers using transcriptomic data. The package is designed to support both quantitative analyses and visual exploration of gene set behaviour across experimental and clinical phenotypes. It implements multiple methods, including score-based and enrichment approaches, and also allows the exploration of expression behaviour of individual genes. In addition, users can assess the similarity of their own gene sets against established collections (e.g., those from MSigDB), facilitating biological interpretation.

Authors:Rita Martins-Silva [aut, cre], Alexandre Kaizeler [aut, ctb], Nuno Luís Barbosa-Morais [aut, led, ths]

markeR_1.3.0.tar.gz
markeR_1.3.0.zip(r-4.7)markeR_1.3.0.zip(r-4.6)markeR_1.3.0.zip(r-4.5)
markeR_1.3.0.tgz(r-4.6-any)markeR_1.3.0.tgz(r-4.5-any)
markeR_1.3.0.tar.gz(r-4.7-any)markeR_1.3.0.tar.gz(r-4.6-any)
markeR_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
markeR/json (API)
NEWS

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

Bug tracker:https://github.com/diseasetranscriptomicslab/marker/issues

Pkgdown/docs site:https://diseasetranscriptomicslab.github.io

Datasets:

On BioConductor:markeR-1.3.0(bioc 3.24)markeR-1.2.0(bioc 3.23)

geneexpressiontranscriptomicsvisualizationsoftwaregenesetenrichmentclassificationgene-expressiongene-setsgene-signaturesphenotypesrna-seq-data

6.56 score 9 stars 21 scripts 190 downloads 20 exports 124 dependencies

Last updated from:ec844f3429. Checks:1 NOTE, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE203
linux-devel-x86_64OK365
source / vignettesOK472
linux-release-x86_64OK393
macos-release-arm64OK311
macos-oldrel-arm64OK231
windows-develOK343
windows-releaseOK342
windows-oldrelOK380
wasm-releaseOK173

Exports:AUC_ScorescalculateDECalculateScoresCohenD_IndividualGenesCorrelationHeatmapExpressionHeatmapFPR_Simulationgeneset_similarityIndividualGenes_ViolinsplotCombinedGSEAplotGSEAenrichmentplotNESlollipopplotPCAPlotScoresplotVolcanoROC_ScoresROCandAUCplotrunGSEAVariableAssociationVisualiseIndividualGenes

Dependencies:abindassertthatbabelgenebackportsbayestestRBHBiocGenericsBiocParallelbootbroomcarcarDatacirclizecliclueclustercodetoolscolorspaceComplexHeatmapcorrplotcowplotcpp11crayoncurldata.tabledatawizardDerivdigestdoBydoParalleldplyredgeReffectsizefarverfastmatchfgseaforeachforecastformatRFormulafracdifffutile.loggerfutile.optionsgenericsGetoptLongggh4xggplot2ggpubrggrepelggsciggsignifGlobalOptionsgluegridExtragtableinsightIRangesisobanditeratorslabelinglambda.rlatticelifecyclelimmalme4lmtestlocfitmagrittrMASSMatrixMatrixModelsmatrixStatsmgcvmicrobenchmarkminqamodelrmsigdbrnlmenloptrnnetnumDerivparameterspbkrtestperformancepillarpkgconfigplyrpngpolynompROCpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasreshape2rjsonrlangrstatixS4VectorsS7scalesshapesnowSparseMstatmodstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

Introduction to markeR

Rendered frommarkeR.Rmdusingknitr::rmarkdownon May 14 2026.

Last update: 2025-09-17
Started: 2025-08-18

Readme and manuals

Help Manual

Help pageTopics
Generate Heatmaps for AUC Scores using ggplot2AUC_Scores
Calculate Differential Gene Expression Statistics using limmacalculateDE
Calculate Gene Signature Scores using Score-Based ApproachesCalculateScores
Cohen's d Heatmap FunctionCohenD_IndividualGenes
CorrelationHeatmap: Generate correlation heatmaps with optional groupingCorrelationHeatmap
Gene Expression Counts for Marthandan et al. (2016) RNA-Seq Datacounts_example
ExpressionHeatmap: Generate an expression heatmap with customizable sample annotations and separate legend positionsExpressionHeatmap
FPR Simulation PlotFPR_Simulation
Plot Signature Similarity via Jaccard Index or Fisher's Odds Ratiogeneset_similarity
Example Gene Sets for Cellular Senescencegenesets_example
Generate Violin Plots for Individual GenesIndividualGenes_Violins
markeR: An R Toolkit for Evaluating Gene Signatures as Phenotypic MarkersmarkeR-package markeR
Metadata for Marthandan et al. (2016) RNA-Seq Studymetadata_example
Plot Combined GSEA ResultsplotCombinedGSEA
Plot GSEA Enrichment ResultsplotGSEAenrichment
Create a Lollipop Plot for GSEA ResultsplotNESlollipop
Principal Component Analysis (PCA) PlotplotPCA
Plot gene signature scores using various methods.PlotScores
Volcano Plots from Differential Expression ResultsplotVolcano
Plot ROC Curves for Gene Signature ScoresROC_Scores
ROC and AUC Plot FunctionROCandAUCplot
Run Gene Set Enrichment Analysis (GSEA) for Multiple ContrastsrunGSEA
Variable Association AnalysisVariableAssociation
VisualiseIndividualGenes: Wrapper for Visualising Individual Genes in Gene SetsVisualiseIndividualGenes