Lea Seep, Paul Jonas Jost, Clivia Lisowski, Hao Huang, Stephan Grein, Hildigunnur Hermannsdottir, Katharina Kuellmer, Tobias Fromme, Martin Klingenspor, Elvira Mass, Christian Kurts, Jan Hasenauer
{"title":"cOmicsArt-a customizable Omics Analysis and reporting tool.","authors":"Lea Seep, Paul Jonas Jost, Clivia Lisowski, Hao Huang, Stephan Grein, Hildigunnur Hermannsdottir, Katharina Kuellmer, Tobias Fromme, Martin Klingenspor, Elvira Mass, Christian Kurts, Jan Hasenauer","doi":"10.1093/bioadv/vbaf067","DOIUrl":null,"url":null,"abstract":"<p><strong>Motivation: </strong>The 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, the most available tools lack GUI-independent reproducibility such as direct integration with R, resulting in very limited support for transition.</p><p><strong>Results: </strong>We 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.</p><p><strong>Availability and implementation: </strong>cOmicsArt 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 at https://github.com/ICB-DCM/cOmicsArt. A docker available from https://hub.docker.com/r/pauljonasjost/comicsart/tags. A snapshot upon publication available from https://zenodo.org/records/14907620. A screen recording of cOmicsArt is available at: https://www.youtube.com/watch?v=pTGjtIYQOakp.</p>","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbaf067"},"PeriodicalIF":2.4000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12085238/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioadv/vbaf067","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Motivation: The 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, the most available tools lack GUI-independent reproducibility such as direct integration with R, resulting in very limited support for transition.
Results: We 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.
Availability and implementation: cOmicsArt 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 at https://github.com/ICB-DCM/cOmicsArt. A docker available from https://hub.docker.com/r/pauljonasjost/comicsart/tags. A snapshot upon publication available from https://zenodo.org/records/14907620. A screen recording of cOmicsArt is available at: https://www.youtube.com/watch?v=pTGjtIYQOakp.