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.

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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
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article

ProteoArk: A One-Pot Proteomics Data Analysis and Visualization Tool for Biologists

Rex Devasahayam Arokia Balaya, Rajesh Raju, Saptami Kanekar, Mahammad Nisar et al.
3 citations
Journal of Proteome Research
Advanced Proteomics Techniques and Applications
2.27
article

ProteoArk: A One-Pot Proteomics Data Analysis and Visualization Tool for Biologists

Rex Devasahayam Arokia Balaya, Rajesh Raju, Saptami Kanekar, Mahammad Nisar, Sneha M. Pinto, Thottethodi Subrahmanya Keshava Prasad, Yashwanth Subbannayya, Richard K. Kandasamy, Sourav Sreelan, Sreelakshmi Pathappillil Soman, Levin John
article en
3 citations

Abstract

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.

Journal of Proteome ResearchVol. 24(3)
Mayo Clinic (US), Yenepoya University (IN), WinnMed (US), University of Surrey (GB), Quantitative BioSciences (US), Integrative Medicine Institute (US), Mayo Clinic in Florida (US)
Openalex Percentile: Top 14%
Advanced Proteomics Techniques and Applications
2.27
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