Ubigen: Interactive Ranking and Enrichment Test for Ubiquitously Expressed Genes
Abstract
We provide an interactive web service to score and rank human genes by their abundance and invariance of expression across all samples in the GTEx database. Users may provide a list of genes to have these scored and ranked accordingly. A one-sided Wilcoxon rank sum test determines a p-value to indicate if the genes from the list score higher than expected by chance. It is possible to interactively control the parameters and instantly observe the effects on the ranking for each of the submitted genes of interest. A genome-wide sliding-window analysis finds that the genes with both the highest and the lowest ranks feature more GO term annotations, indicating that the scoring carries biological relevance. Availability and Implementationhttps://ubigen.uni-rostock.de Contactelias.projahn@uni-rostock.de
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 1
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- PRRGO: A Tool for Visualizing and Mapping Globally Expressed Genes in Public Gene Expression Omnibus RNA-Sequencing Studies to PageRank-scored Gene Ontology Terms
Luis E. Solano, Nicholas D’Sa, Nikolas Nikolaidis·bioRxiv·Jan 21, 2024
- massiveGenesetsTest: a web tool to run enrichment analysis.
Luigi Cerulo, Stefano Maria Pagnotta·EntropyPeer-reviewed·May 23, 2022
- Uncertainty-Aware Gene Rankings Reveal Key Players in Coexpression Networks
Sugyani Mahapatra, Nilesh Anantha Subramanian, Manikandan Narayanan·bioRxiv·Jun 17, 2026
- GeneAutomate: A Browser-Based, Integer-Indexed Platform for Dual-Gene-List Functional Annotation and Interactive Network Visualization
Rudra Pratap Singh, Amrendra Kumar·bioRxiv·Jul 21, 2026
- GenRank: an R/Bioconductor package for prioritization of candidate genes
Chakravarthi Kanduri, Irma Jarvela·F1000ResearchPeer-reviewed·Apr 11, 2017
- GOAT: efficient and robust identification of geneset enrichment
Frank Koopmans·Communications BiologyPeer-reviewed·Jun 19, 2024