High-level, module-based R/Shiny apps with ‘Teal’ framework, with applications beyond the pharma data domain
Regular talk, 1:25-1:40
The Teal package(s) ecosystem is a recent framework for R/Shiny apps leveraging ‘modules’, designed for pharma clinical trials data domain. ‘Modules’ are pairs of UI and Server functions, designed to reuse code. It utilizes namespace for writing, analyzing, and testing individual components in isolation. The ‘Teal’ framework is ‘high level’, meaning that one can assemble the various shiny components as blocks, without worrying too much about what is going on underneath, which is referred to as ‘low-level’. This way, one can benefit from rich functionality that has already been developed for the framework, and add or modify ad-hoc special ‘touches’ as needed. The talk will review some of the pros and cons, and demonstrate a use-case with non-clinical data domain, and how to modify and customize an existing module to a new functionality.
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Pronouns: he/himSeattle, WADror Berel is a statistician with over 20 years of work experience in both academia and industry. He loves using R for (almost) everything. He works as an independent consultant, solving business problems and scale analytical tools for diverse data domains, leveraging both traditional Machine learning and Causal Inference along with modern approaches. Among the data domains he specialize in are: genomic biomarker discovery, clinical data reporting (CDISC, ADaM, TLGs). His services also include: Authoring Real World Evidence data analysis and documentation. Writing statistical plans, Power analysis, Design of experiments, and biomarker discovery. Developing R/Shiny apps, and REST APIs. Golem, Rhino, Teal and others. |