Milken Institute School of Public Health Poster Presentations (Marvin Center & Video)

Title

Make Big Data Alive: Interactive Data Visualization in Metabolomics Research

Poster Number

62

Document Type

Poster

Status

Graduate Student - Doctoral

Abstract Category

Epidemiology and Biostatistics

Keywords

metabolomics; data visualization; shiny

Publication Date

4-2017

Abstract

Metabolomics research has rapidly evolved in recent years. In this data-intensive field, effective and simple data visualization tools empower researchers to present the big data in a meaningful way that people can quickly understand and use. Compared with traditional static graphics and tables, interactive visualization takes the concept a step further by allowing self-service faceting, probing and drill down._x000D_

We developed several interactive data visualization applications for metabolomics research using Shiny by RStudio coupled with R packages ggvis and plotly. The applications present information including quality control and regression analysis of more than 3000 metabolites in thousands of different models. Results are conveyed both in data tables and statistical graphs. Data tables contain complete information and are downloadable. In statistical graphs, users are allowed to view pointwise values using mouse-over controls, to drill down for detail through zooming, to compare and contrast the models and to display subsets of results by filtering on p-values, treatment groups, model adjustments, metabolites classes or even selecting an individual metabolite. The application can be published on websites to allow public or secure (authenticated) access and share with others. The above features of these Shiny applications enable a self-service, meaningful and flexible way to review and communicate data.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Open Access

1

Comments

Poster to presented at GW Annual Research Days 2017.

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Make Big Data Alive: Interactive Data Visualization in Metabolomics Research

Metabolomics research has rapidly evolved in recent years. In this data-intensive field, effective and simple data visualization tools empower researchers to present the big data in a meaningful way that people can quickly understand and use. Compared with traditional static graphics and tables, interactive visualization takes the concept a step further by allowing self-service faceting, probing and drill down._x000D_

We developed several interactive data visualization applications for metabolomics research using Shiny by RStudio coupled with R packages ggvis and plotly. The applications present information including quality control and regression analysis of more than 3000 metabolites in thousands of different models. Results are conveyed both in data tables and statistical graphs. Data tables contain complete information and are downloadable. In statistical graphs, users are allowed to view pointwise values using mouse-over controls, to drill down for detail through zooming, to compare and contrast the models and to display subsets of results by filtering on p-values, treatment groups, model adjustments, metabolites classes or even selecting an individual metabolite. The application can be published on websites to allow public or secure (authenticated) access and share with others. The above features of these Shiny applications enable a self-service, meaningful and flexible way to review and communicate data.