Shiny - Epidemiology

What is Shiny?

Shiny is an R package developed by RStudio that allows users to build interactive web applications directly from R. These applications can be used to visualize data, perform analyses, and provide interactive reports. In the field of epidemiology, Shiny applications can be incredibly valuable for data exploration, visualization, and communication of findings.

Why Use Shiny in Epidemiology?

Epidemiologists deal with large and complex datasets that require sophisticated analysis and visualization tools. Shiny provides a platform for creating interactive dashboards that can help in the following ways:

Data Visualization: Allows real-time interaction with data, making it easier to identify trends and patterns.
Data Exploration: Users can filter, sort, and manipulate data to investigate different hypotheses.
Communication: Interactive dashboards can be shared with stakeholders to communicate findings effectively.
Reproducibility: Analysis scripts and visualizations can be saved and rerun, ensuring consistency and reproducibility.

How to Create a Shiny App?

Creating a Shiny app involves writing two main components:

UI (User Interface): Defines the layout and appearance of the app.
Server: Contains the logic and computations required to run the app.

Here is a simple example of a Shiny app that plots epidemiological data:

library(shiny)

# Define UI
ui

Relevant Publications

Evergene: an interactive webtool for large-scale gene-centric analysis of primary tumours.

Issue Release: 2024

Long-read RNA sequencing identifies region- and sex-specific C57BL/6J mouse brain mRNA isoform expression and usage.

Issue Release: 2024

RegionSizeR- A Novel App for Regional Sample Size Planning in MRCTs.

Issue Release: 2024

Dermoscopy and Confocal Microscopy Findings of Basal Cell Carcinomas in Xeroderma Pigmentosum Patients.

Issue Release: 2024

Importance of Both Clinical and Dermoscopic Findings in Predicting High-Risk Histopathological Subtype in Facial Basal Cell Carcinomas.

Issue Release: 2024

PROpwr: a Shiny R application to analyze patient-reported outcomes data and estimate power.

Issue Release: 2024

ggVennDiagram: Intuitive Venn diagram software extended.

Issue Release: 2024

Prediction for post-ERCP pancreatitis in non-elderly patients with common bile duct stones: a cross-sectional study at a major Chinese tertiary hospital (2015-2023).

Issue Release: 2024

VisualSphere: a Web-based Interactive Visualization System for Clinical Research Data.

Issue Release: 2024

Spatiotemporal proteomic profiling of cellular responses to NLRP3 agonists.

Issue Release: 2024

A new sample-size planning approach for person-specific VAR(1) studies: Predictive accuracy analysis.

Issue Release: 2024

WALIS dashboard: An online tool to explore a global paleo sea-level database.

Issue Release: 2024

Development of a Web Application for Simulating Plasma Drug Concentrations in Patients with Zolpidem Intoxication.

Issue Release: 2024

Decrypting the molecular basis of cellular drug phenotypes by dose-resolved expression proteomics.

Issue Release: 2024

Genetic markers associated with the widespread insecticide resistance in malaria vector Anopheles funestus populations across Tanzania.

Issue Release: 2024

[Skin reactions related to molluscum contagiosum infection].

Issue Release: 2024

Meta-analysis towards FSHD reveals misregulation of neuromuscular junction, nuclear envelope, and spliceosome.

Issue Release: 2024

A Systematic Review of Diagnoses with Rosettes Under Dermoscopy.

Issue Release: 2024

Conceptually Funded Usability Evaluation of an Application for Leveraging Descriptive Data Analysis Models for Cardiovascular Research.

Issue Release: 2024

K-Track-Covid: interactive web-based dashboard for analyzing geographical and temporal spread of COVID-19 in South Korea.

Issue Release: 2024

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