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- Title
STENCIL: A web templating engine for visualizing and sharing life science datasets.
- Authors
Sun, Qi; Nematbakhsh, Ali; Kuntala, Prashant K.; Kellogg, Gretta; Pugh, B. Franklin; Lai, William K. M.
- Abstract
The ability to aggregate experimental data analysis and results into a concise and interpretable format is a key step in evaluating the success of an experiment. This critical step determines baselines for reproducibility and is a key requirement for data dissemination. However, in practice it can be difficult to consolidate data analyses that encapsulates the broad range of datatypes available in the life sciences. We present STENCIL, a web templating engine designed to organize, visualize, and enable the sharing of interactive data visualizations. STENCIL leverages a flexible web framework for creating templates to render highly customizable visual front ends. This flexibility enables researchers to render small or large sets of experimental outcomes, producing high-quality downloadable and editable figures that retain their original relationship to the source data. REST API based back ends provide programmatic data access and supports easy data sharing. STENCIL is a lightweight tool that can stream data from Galaxy, a popular bioinformatic analysis web platform. STENCIL has been used to support the analysis and dissemination of two large scale genomic projects containing the complete data analysis for over 2,400 distinct datasets. Code and implementation details are available on GitHub: https://github.com/CEGRcode/stencil Author summary: Efficient and scalable data visualization of analysis is a critical bottleneck in biological discovery within life sciences. The exponential growth of genomic projects, which can now generate thousands of unique datasets in a single paper, have produced organizational and logistical difficulties for biochemists and bioinformaticians. To address these challenges, we developed the STENCIL web platform to incorporate principles of project management with a strong emphasis on data reproducibility and FAIR data practices. We architected STENCIL to operate on minimal system requirements (i.e., 1 CPU, 8Gb RAM) while seamlessly organizing thousands of unique samples in an intuitive interface for data discovery. Data reproducibility is provided by the well-proven Galaxy bioinformatic web platform. The utility of the STENCIL platform has been demonstrated in two prior publications to date. Its capabilities have now been dramatically expanded to provide native support for Galaxy integration, Federated login, local hosting, custom domain usage, and improved security protocols for analyzing controlled de-identified biomedical patient data.
- Subjects
LIFE sciences; STENCIL work; INFORMATION sharing; DATA analysis; DATA visualization
- Publication
PLoS Computational Biology, 2022, Vol 18, Issue 2, p1
- ISSN
1553-734X
- Publication type
Article
- DOI
10.1371/journal.pcbi.1009859