Bioinformatics AdvancesBioinformaticsPeer-reviewed journal article
cOmicsArt - a customizable Omics Analysis and reporting tool
Lea SeepiD, Paul Jonas JostiD, Clivia LisowskiiD, Hao HuangiD, Stephan GreiniD, Hildigunnur HermannsdóttiriD, Katharina KuellmeriD, Tobias FrommeiD, Martin KlingensporiD, Elvira MassiD, Christian KurtsiD, Jan HasenaueriD
Abstract
MotivationThe availability of bulk-omic data is steadily increasing, necessitating collaborative efforts between experimental and computational researchers. While software tools with graphical user interfaces (GUIs) enable rapid and interactive data assessment, they are limited to pre-implemented methods, often requiring transitions to custom code for further adjustments. However, most available tools lack GUI-independent reproducibility such as direct integration with R, resulting in very limited support for transition. ResultsWe introduce the customizable Omics Analysis and reporting tool - cOmicsArt. cOmicsArt aims to enhance collaboration through integration of GUI-based analysis with R. The GUI allows researchers to perform user-friendly exploratory and statistical analyses with interactive visualizations and automatic documentation. Downloadable R scripts and results ensure reproducibility and seamless integration with R, supporting both novice and experienced programmers by enabling easy customizations and serving as a foundation for more advanced analyses. This versatility also allows for usage in educational settings guiding students from GUI-based analysis to R Code. AvailabilitycOmicsArt is freely available at https://shiny.iaas.uni-bonn.de/cOmicsArt/ User documentation is available at https://icb-dcm.github.io/cOmicsArt/ Source code is available on GitHub https://github.com/ICB-DCM/cOmicsArt A docker image can be retrieved from https://hub.docker.com/r/pauljonasjost/comicsart/tags A snapshot upon publication can be found on Zenodo: https://zenodo.org/records/13740904 A screen recording of cOmicsArt is available at: https://www.youtube.com/watch?v=pTGjtIYQOakp Contactjan.hasenauer@uni-bonn.de Supplementary informationSupplementary data are available online.
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 30th percentile
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
- Quickomics: exploring omics data in an intuitive, interactive and informative manner
Benbo Gao, Jing Zhu, … Baohong Zhang·BioinformaticsPeer-reviewed·Apr 19, 2021
- Easyreporting simplifies the implementation of Reproducible Research Layers in R software
Dario Righelli, Claudia Angelini·PLoS ONEPeer-reviewed·May 10, 2021
- EasyPubPlot: a shiny web application for rapid omics data exploration and visualization
Nguyen Tran Nam Tien, Nguyen Quang Thu, … Nguyen Phuoc Long·Journal of Proteome ResearchPeer-reviewed·Mar 7, 2025
- Fast analyzing, exploring and sharing quantitative omics data using omicsViewer
Chen Meng·bioRxiv·Mar 10, 2022
- EasyOmics-A graphical interface for population-scale omics data association, integration and visualization
Yu Han, Qiao Du, … Yanjun Zan·Plant CommunicationsPeer-reviewed·Feb 26, 2025
- GraphBio: a shiny web app to easily perform popular visualization analysis for omics data
Tianxin Zhao, Zelin Wang·Frontiers in GeneticsPeer-reviewed·Sep 7, 2022