2021 Workshops

Register for workshops here.

Ellis Hughes & Marie Vendettuoli

Session: Morning and Afternoon

R Package Development and Validation

This tutorial aims to teach some basics of R package development while creating all the necessary documentation to support a validation. By the end of this tutorial, you will know how to apply the R Package Validation Framework to your internal R packages, and apply the {valtools} package.

This tutorial addresses a major knowledge gap in the R ecosystem: getting R accepted into highly regulated industries. This is an opportunity for those that work in these industries to be empowered to expand the use of R. We are taking an approach where some basic R knowledge is expected, such as writing scripts and functions, but teaching people to take the next steps.

Previous work presented to the community has shown a framework for developers to distribute validation-ready R packages, which has been met with enthusiasm among R users in pharma. In this tutorial participants will experience the process of creating R packages with validation resources in place and explore how addition of these materials perform in a variety of real-world scenarios, including validation-on-install and validation-post-install. Participants will have the opportunity to practice how validation affects subsequent package releases.

Ellis’ Bio: (he/him) I am a statistical Programmer at Fred Hutch Cancer Research Center where I work on a team that evaluates potential HIV vaccine candidates. Having graduated from Washington State University with a degree in Bioengineering, I found a passion for programming in R. I now organize the Seattle UseR group, and enjoy building packages to automate my workflows.

Marie's Bio: (she/her) I am a Senior Statistical Programmer at the Statistical Center for HIV/AIDS Research and Prevention (SCHARP) at Fred Hutch. I implement analytical systems in R that help scientists and researchers do their job more effectively, with regulatory experience both in industry and government.

Joe Korszun

Pronouns: he/him
Data Science Consultant at ProCogia

Session: Morning

Transitioning to R Workshop

Experienced SAS users looking for exposure to R? This workshop will introduce the R environment and help users discover how to wrangle, visualize, and model their data. Users will be provided a detailed mapping of R functions to SAS procedures.

Bio: I am a Data Science Consultant at ProCogia in Seattle, WA. I specialize in SAS to R conversion focusing on the biopharmaceutical sector. I have 4.5 years of experience working at a large biopharmaceutical company, aiding in anomaly detection for batch processing. I am passionate about getting the most out of your data.

Kate Hertweck

Pronouns: perceived pronouns
Seattle, WA

Session: Morning

Introduction to R

New to R statistical programming? Join this introductory R workshop in a whirlwind tour of R for data manipulation and visualization! We'll apply widely used tools from the Tidyverse collection of packages in the RStudio interface to jumpstart your data science work using R. At the end of this session, you will be able to:

  • recognize important features of R coding syntax
  • import, inspect, and manipulate spreadsheet-style data
  • create publication-quality visualizations of data
  • organize R coding within projects for reproducibility

Bio: Kate Hertweck is a scientist and educator with seven years of experience as an R educator, including certification as an instructor (and instructor trainer) for The Carpentries. Kate has taught R to hundreds of people with diverse backgrounds and interests: from high school students to experts with Ph.D.s, researchers and medical professionals to librarians and social scientists, and for people interested in applying R to an enormous array of problems in coding and data science. Kate specializes in training biomedical scientists to use coding and reproducible computational methods to improve the reproducibility, robustness, and openness of their science.

Mike Garcia

Pronouns: he/him
Data Scientist Consultant at ProCogia

Session: Afternoon

Reproducible Research with Targets Package

The targets package facilitates reproducible workflows and reduces unnecessary duplicate computation. In this workshop, we’ll cover how to structure your data analyses using function oriented workflows, set up and debug pipelines, and incorporate targets into your existing toolkit for reproducible data science. Participants should be comfortable with basic R programming including defining variables and functions.

Agenda:

  • Functional programming
  • Pipelines
  • Debugging
  • Integrating other tools for reproducible research

Bio: I’m a data scientist and biostatistician who has been programming in R long enough to remember thrill of abandoning the R GUI for the first RStudio release. I’m passionate about teaching statistics and coding in R, especially helping others learn to build and maintain reproducible workflows.

Ted Laderas

Pronouns: he/him
Oregon

Session: Afternoon

A gRadual intRoduction to Shiny

Interactive graphics and dashboards are a powerful tool for communicating your findings and enabling your audience to ask specific questions of datasets. One of the most popular tools for building such visualizations and dashboards is Shiny, an interactive visualization framework in R. Shiny visualizations and dashboards can be easily shared online. In this workshop, Ted Laderas will introduce you to the basic concepts behind making interactive visualizations with Shiny. In the workshop, we will build a dashboard that will give users control to slice a dataset for further exploration, and also use controls to change visual properties of a visualization. We will also discuss deployment of our apps. Please note this workshop assumes basic familiarity with R and the tidyverse and basic knowledge of how functions work in R. All levels are free to attend, but you will get the most out of this workshop if you're familiar with the tidyverse and know something about functions. An introduction to the tidyverse can be found here. A quick review of functions can be found here

Bio: I teach R and Data Science to a variety of audiences, including clinicians, statisticians, and basic scientists. I'm a co-founder of Cascadia-R, and I try to make learning less lonely through communities of practice.