ProFun: A web server for functional enrichment analysis of parasitic protozoan genes.

The initial step to interpreting putative biological functions from comparative multi-omics studies usually starts from a differential expressed gene list followed by functional enrichment analysis (FEA). However, most FEA packages are designed exclusively for humans and model organisms. Although parasitic protozoan is the most important pathogen in the tropics, no FEA package is available for protozoan functional (ProFun) enrichment analysis. To speed up comparative multi-omics research on parasitic protozoans, we constructed ProFun, a web-based, user-friendly platform for the research community. ProFun utilizes the Docker container, ShinyProxy, and R Shiny to construct a scalable web service with load-balancing infrastructure. We have integrated a series of visual analytic functions, in-house scripts, and custom-made annotation packages to create three analytical modules for 40 protozoan species: (1) Gene Overlaps; (2) Over-representation Analysis (ORA); (3) Gene Set Enrichment Analysis (GSEA). We have established ProFun, a web server for functional enrichment analysis of differentially expressed genes. FEA becomes as simple as pasting a list of gene IDs into the textbox of our website. Users can customize enrichment parameters and results with just one click. The intuitive web interface and publication-ready charts enable users to reveal meaningful biological events and pinpoint potential targets for further studies. ProFun is the first web application that enables gene functional enrichment analysis of parasitic protozoans. In addition to supporting FEA analysis, ProFun also allows the comparison of FEA results across complicated experimental designs. ProFun is freely available at http://dalek.cgu.edu.tw:8080/app/profun. Copyright © 2024. Published by Elsevier B.V.

Citation

Po-Jung Huang, Yi-Chen Weng, Kuo-Yang Huang, Chi-Ching Lee, Yuan-Ming Yeh, Yu-Tong Chen, Cheng-Hsun Chiu, Petrus Tang. ProFun: A web server for functional enrichment analysis of parasitic protozoan genes. Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi. 2024 Jun;57(3):509-517

Mesh Tags

PMID: 38311498

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