Hiplot: a comprehensive and easy-to-use web service for boosting publication-ready biomedical data visualization

TLDR

Complex biomedical data generated during clinical, omics, and mechanism-based experiments are increasingly mined through cloud- and visualization-based techniques, yet the scientific community still lacks an easy-to-use web service for comprehensive, high-quality, publication-ready biomedical data visualization that scales and updates per user demands. We propose Hiplot, a community-driven modern web service offering concise, top-quality data visualization applications for life sciences and biomedical fields. Hiplot provides over 240 specialized visualization functions—including basic statistics, multi‑omics, regression, clustering, dimensional reduction, meta‑analysis, survival analysis, and risk modelling—and features a spreadsheet-based importer, cross‑platform command‑line controller, multi‑user workers, JSON plugin system, and real‑time update mode to enable interactive, efficient use by researchers. Benchmark tests and real data analyses demonstrate Hiplot’s performance in exploring statistical parameters, cancer genomic landscapes, disease risk factors, and its growing user base indicates significant potential impact on biomedical research.

Abstract

Abstract Complex biomedical data generated during clinical, omics and mechanism-based experiments have increasingly been exploited through cloud- and visualization-based data mining techniques. However, the scientific community still lacks an easy-to-use web service for the comprehensive visualization of biomedical data, particularly high-quality and publication-ready graphics that allow easy scaling and updatability according to user demands. Therefore, we propose a community-driven modern web service, Hiplot (https://hiplot.org), with concise and top-quality data visualization applications for the life sciences and biomedical fields. This web service permits users to conveniently and interactively complete a few specialized visualization tasks that previously could only be conducted by senior bioinformatics or biostatistics researchers. It covers most of the daily demands of biomedical researchers with its equipped 240+ biomedical data visualization functions, involving basic statistics, multi-omics, regression, clustering, dimensional reduction, meta-analysis, survival analysis, risk modelling, etc. Moreover, to improve the efficiency in use and development of plugins, we introduced some core advantages on the client-/server-side of the website, such as spreadsheet-based data importing, cross-platform command-line controller (Hctl), multi-user plumber workers, JavaScript Object Notation-based plugin system, easy data/parameters, results and errors reproduction and real-time updates mode. Meanwhile, using demo/real data sets and benchmark tests, we explored statistical parameters, cancer genomic landscapes, disease risk factors and the performance of website based on selected native plugins. The statistics of visits and user numbers could further reflect the potential impact of this web service on relevant fields. Thus, researchers devoted to life and data sciences would benefit from this emerging and free web service.