ProteoArk: A One-Pot Proteomics Data Analysis and Visualization Tool for Biologists
ProteoArk is a web-based tool that offers a range of computational pipelines for comprehensive analysis and visualization of mass spectrometry-based proteomics data. The application comprises four primary sections designed to address various aspects of mass spectrometry data analysis in a single platform, including label-free and labeled samples (SILAC/iTRAQ/TMT), differential expression analysis, and data visualization. ProteoArk supports postprocessing of Proteome Discoverer, MaxQuant, and MSFragger search results. The tool also includes functional enrichment analyses such as gene ontology, protein-protein interactions, pathway analysis, and differential expression analysis, which incorporate various statistical tests. By streamlining workflows and developing user-friendly interfaces, we created a robust and accessible solution for users with basic bioinformatics skills in proteomic data analysis. Users can easily create manuscript-ready figures with a single click, including principal component analysis, heatmaps (K-means and hierarchical), MA plots, volcano plots, and circular bar plots. ProteoArk is developed using the Django framework and is freely available for users [https://ciods.in/proteoark/]. Users can also download and run the standalone version of ProteoArk using Docker as described in the instructions [https://ciods.in/proteoark/dockerpage]. The application code, input data, and documentation are available online at https://github.com/ArokiaRex/proteoark. A tutorial video is available on YouTube: https://www.youtube.com/watch?v=WFMKAZ9Slq4&ab_channel=RexD.A.B.
Authors
- Rex Devasahayam Arokia Balaya (ORCID: https://orcid.org/0000-0002-9556-3150)
- Rajesh Raju (ORCID: https://orcid.org/0000-0003-2319-121X)
- Saptami Kanekar (ORCID: https://orcid.org/0000-0002-1508-5305)
- Mahammad Nisar (ORCID: https://orcid.org/0000-0002-5223-2802)
- Sneha M. Pinto (ORCID: https://orcid.org/0000-0001-8541-8761)
- Thottethodi Subrahmanya Keshava Prasad (ORCID: https://orcid.org/0000-0002-6206-2384)
- Yashwanth Subbannayya (ORCID: https://orcid.org/0000-0002-3885-3514)
- Richard K. Kandasamy (ORCID: https://orcid.org/0000-0002-0894-1222)
- Sourav Sreelan (ORCID: https://orcid.org/0009-0009-4820-230X)
- Sreelakshmi Pathappillil Soman
- Levin John (ORCID: https://orcid.org/0000-0003-2335-9238)
Institutions
- Mayo Clinic (US)
- Yenepoya University (IN)
- WinnMed (US)
- University of Surrey (GB)
- Quantitative BioSciences (US)
- Integrative Medicine Institute (US)
- Mayo Clinic in Florida (US)
Publication Details
- Journal
- Journal of Proteome Research
- Published
- 2025-02-10
- DOI
- https://doi.org/10.1021/acs.jproteome.4c00556
- Citations
- 3
- Primary Topic
- Advanced Proteomics Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.27