Mark your calendars! This month we will hear from 3 people about their pathways to learning R and the great community-building that happened along the way. Redfin has kindly offered to host us in their space in downtown Seattle.
* Stefanie Butland, Community Manager at rOpenSci
* Malisa Smith, Bioinformatician at University of Washington
* Pamela Moriarty, Data Scientist at zulily
I am the Community Manager for an organization of R practitioners...but I am not an R practitioner. For the first 1.5 years in my job, this was a feature, but lately it has felt more like a bug. In this talk I will introduce rOpenSci, our packages, and our system for transparent software peer review, and then share my story of starting to learn R by (not so) passive absorption of information and best practices from R-Ladies, rOpenSci, and the broader R world.
Flow cytometry is commonly used by biologists to measure the abundance of specific molecules in millions of cells, while retaining information at the single-cell level. The resulting high-dimensional, high-throughput datasets have led to the development of unique software for analyzing flow cytometry data. I will talk about how I learned to use open source R packages for analyzing flow data, and I hope that my experience will help other people navigate the landscape of flow cytometry analysis tools and online software resources in general.
My entry into the world of R, which also served as my introduction to coding, was headfirst and unplanned. While some aspects of my approach had advantages, it also made for a very...bumpy...road. Taking advantage of hindsight, I'll focus on how to make your path to learning R smoother than mine was.