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
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markeR_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
markeR/json (API)

# 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:

counts_example - Gene Expression Counts for Marthandan et al. (2016) RNA-Seq Data
genesets_example - Example Gene Sets for Cellular Senescence
metadata_example - Metadata for Marthandan et al. (2016) RNA-Seq Study

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

geneexpression transcriptomics visualization software genesetenrichment classification gene-expression gene-sets gene-signatures phenotypes rna-seq-data

6.50 score 10 stars 21 scripts 187 downloads 20 exports 124 dependencies

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

Target	Result	Time
bioc-checks	NOTE	226
linux-devel-x86_64	OK	348
source / vignettes	OK	425
linux-release-x86_64	OK	358
macos-release-arm64	OK	242
macos-oldrel-arm64	OK	184
windows-devel	OK	300
windows-release	OK	337
windows-oldrel	OK	354
wasm-release	OK	173

Exports:AUC_Scores calculateDE CalculateScores CohenD_IndividualGenes CorrelationHeatmap ExpressionHeatmap FPR_Simulation geneset_similarity IndividualGenes_Violins plotCombinedGSEA plotGSEAenrichment plotNESlollipop plotPCA PlotScores plotVolcano ROC_Scores ROCandAUCplot runGSEA VariableAssociation VisualiseIndividualGenes

Dependencies:abind assertthat babelgene backports bayestestR BH BiocGenerics BiocParallel boot broom car carData circlize cli clue cluster codetools colorspace ComplexHeatmap corrplot cowplot cpp11 crayon curl data.table datawizard Deriv digest doBy doParallel dplyr edgeR effectsize farver fastmatch fgsea foreach forecast formatR Formula fracdiff futile.logger futile.options generics GetoptLong ggh4x ggplot2 ggpubr ggrepel ggsci ggsignif GlobalOptions glue gridExtra gtable insight IRanges isoband iterators labeling lambda.r lattice lifecycle limma lme4 lmtest locfit magrittr MASS Matrix MatrixModels matrixStats mgcv microbenchmark minqa modelr msigdbr nlme nloptr nnet numDeriv parameters pbkrtest performance pillar pkgconfig plyr png polynom pROC purrr quantreg R6 rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack reformulas reshape2 rjson rlang rstatix S4Vectors S7 scales shape snow SparseM statmod stringi stringr survival tibble tidyr tidyselect timeDate urca utf8 vctrs viridisLite withr zoo

Introduction to markeR

Rendered frommarkeR.Rmdusingknitr::rmarkdown

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

Help page	Topics
Generate Heatmaps for AUC Scores using ggplot2	AUC_Scores
Calculate Differential Gene Expression Statistics using limma	calculateDE
Calculate Gene Signature Scores using Score-Based Approaches	CalculateScores
Cohen's d Heatmap Function	CohenD_IndividualGenes
CorrelationHeatmap: Generate correlation heatmaps with optional grouping	CorrelationHeatmap
Gene Expression Counts for Marthandan et al. (2016) RNA-Seq Data	counts_example
ExpressionHeatmap: Generate an expression heatmap with customizable sample annotations and separate legend positions	ExpressionHeatmap
FPR Simulation Plot	FPR_Simulation
Plot Signature Similarity via Jaccard Index or Fisher's Odds Ratio	geneset_similarity
Example Gene Sets for Cellular Senescence	genesets_example
Generate Violin Plots for Individual Genes	IndividualGenes_Violins
markeR: An R Toolkit for Evaluating Gene Signatures as Phenotypic Markers	markeR-package markeR
Metadata for Marthandan et al. (2016) RNA-Seq Study	metadata_example
Plot Combined GSEA Results	plotCombinedGSEA
Plot GSEA Enrichment Results	plotGSEAenrichment
Create a Lollipop Plot for GSEA Results	plotNESlollipop
Principal Component Analysis (PCA) Plot	plotPCA
Plot gene signature scores using various methods.	PlotScores
Volcano Plots from Differential Expression Results	plotVolcano
Plot ROC Curves for Gene Signature Scores	ROC_Scores
ROC and AUC Plot Function	ROCandAUCplot
Run Gene Set Enrichment Analysis (GSEA) for Multiple Contrasts	runGSEA
Variable Association Analysis	VariableAssociation
VisualiseIndividualGenes: Wrapper for Visualising Individual Genes in Gene Sets	VisualiseIndividualGenes

Package: markeR 1.3.0

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

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Help Manual

Usage by other packages (reverse dependencies)