STENCIL: A web templating engine for visualizing and sharing life science datasets.
STENCIL: A web templating engine for visualizing and sharing life science datasets.
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DOI：
10.1371/journal.pcbi.1009859
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发表时间：
2022-03
影响因子：
4.3
通讯作者：
Lai WKM
中科院分区：
文献类型：
--
作者：
Sun Q;Nematbakhsh A;Kuntala PK;Kellogg G;Pugh BF;Lai WKM
将实验数据分析和结果汇总为简洁和可解释的格式的能力是评估实验成功的关键步骤。这一关键步骤确定了可重复性的基线，也是数据传播的关键要求。然而，在实践中，可能难以整合包含生命科学中广泛数据库的数据分析。我们提出了STENCIL，一个Web模板引擎，旨在组织，可视化，并实现交互式数据可视化的共享。STENCIL利用一个灵活的Web框架来创建模板，以呈现高度可定制的可视化前端。这种灵活性使研究人员能够呈现小型或大型的实验结果集，生成高质量的可下载和可编辑的数字，这些数字保留了与源数据的原始关系。基于REST API的后端提供编程数据访问并支持轻松的数据共享。STENCIL是一个轻量级工具，可以从流行的生物信息学分析网络平台Galaxy传输数据。STENCIL已被用于支持两个大规模基因组项目的分析和传播，其中包含2，400多个不同数据集的完整数据分析。代码和实现细节可在GitHub上获得：https://github.com/CEGRcode/stencil高效和可扩展的分析数据可视化是生命科学中生物发现的关键瓶颈。基因组项目的指数级增长，现在可以在一篇论文中生成数千个独特的数据集，为生物化学家和生物信息学家带来了组织和后勤方面的困难。为了应对这些挑战，我们开发了STENCIL网络平台，将项目管理的原则与数据可重复性和公平数据实践相结合。我们将STENCIL架构为在最低系统要求下运行（即，1个CPU，8Gb RAM），同时在直观的界面中无缝组织数千个独特的样本，以进行数据发现。数据再现性由经过充分验证的Galaxy生物信息学网络平台提供。到目前为止，STENCIL平台的实用性已在之前的两篇出版物中得到证实。它的功能现在已经得到了极大的扩展，为Galaxy集成、联合登录、本地托管、自定义域使用提供了原生支持，并改进了用于分析受控的去识别生物医学患者数据的安全协议。
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 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.
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DOI：
10.1016/j.future.2014.10.008
发表时间：
2015-05-01
影响因子：
7.5
作者：
Deelman, Ewa;Vahi, Karan;Wenger, Kent
通讯作者：
Wenger, Kent
影响因子：
2.8
作者：
Stirling C;Andrews S;Croft T;Vickers J;Turner P;Robinson A
通讯作者：
Robinson A
影响因子：
7
作者：
Lai WKM;Mariani L;Rothschild G;Smith ER;Venters BJ;Blanda TR;Kuntala PK;Bocklund K;Mairose J;Dweikat SN;Mistretta K;Rossi MJ;James D;Anderson JT;Phanor SK;Zhang W;Zhao Z;Shah AP;Novitzky K;McAnarney E;Keogh MC;Shilatifard A;Basu U;Bulyk ML;Pugh BF
通讯作者：
Pugh BF
影响因子：
3.7
作者：
Costa-Silva J;Domingues D;Lopes FM
通讯作者：
Lopes FM
影响因子：
64.8
作者：
Roadmap Epigenomics Consortium;Kundaje A;Meuleman W;Ernst J;Bilenky M;Yen A;Heravi-Moussavi A;Kheradpour P;Zhang Z;Wang J;Ziller MJ;Amin V;Whitaker JW;Schultz MD;Ward LD;Sarkar A;Quon G;Sandstrom RS;Eaton ML;Wu YC;Pfenning AR;Wang X;Claussnitzer M;Liu Y;Coarfa C;Harris RA;Shoresh N;Epstein CB;Gjoneska E;Leung D;Xie W;Hawkins RD;Lister R;Hong C;Gascard P;Mungall AJ;Moore R;Chuah E;Tam A;Canfield TK;Hansen RS;Kaul R;Sabo PJ;Bansal MS;Carles A;Dixon JR;Farh KH;Feizi S;Karlic R;Kim AR;Kulkarni A;Li D;Lowdon R;Elliott G;Mercer TR;Neph SJ;Onuchic V;Polak P;Rajagopal N;Ray P;Sallari RC;Siebenthall KT;Sinnott-Armstrong NA;Stevens M;Thurman RE;Wu J;Zhang B;Zhou X;Beaudet AE;Boyer LA;De Jager PL;Farnham PJ;Fisher SJ;Haussler D;Jones SJ;Li W;Marra MA;McManus MT;Sunyaev S;Thomson JA;Tlsty TD;Tsai LH;Wang W;Waterland RA;Zhang MQ;Chadwick LH;Bernstein BE;Costello JF;Ecker JR;Hirst M;Meissner A;Milosavljevic A;Ren B;Stamatoyannopoulos JA;Wang T;Kellis M
通讯作者：
Kellis M