Abstract
For projects in R, the drake package can help. It analyzes your workflow, skips steps with up-to-date results, and orchestrates the rest with optional distributed computing. At the end, drake provides evidence that your results match the underlying code and data, which increases your ability to trust your research.
Recently I got interested in using the xaringan package for creating HTML based R Markdown documents because I could use the widgetframe package to embed htmlwidgets as responsive iframes (I had created some spinning 3D visulizations with pseudo-coloring I wanted to present interactively).
xaringan, it’s a R pacakges for creating slideshows with remark.js through R Markdown.
Around the same time I learnt about Drake (or “Data Frames in R for Make”) which is an amazing a time-saving reproducible build system for data scientist specifically tailored to R. The pacakge makes use of the futures package allowing the use of parallel computing on high-performance computing systems.
I recently gave a talk at the Douglas Mental Health University Institute talking about the advantages of Drake (and a few other interesting projects).
Matthew J. Oldach, M.Sc.
Senior Consultant and Team Lead
I am an experienced professional in Bioinformatics, Software Development, Data Science and DevOps. With a diverse skill set, I excel in various technical areas such as data wrangling, statistical modeling, machine learning, shiny, data visualization, report automation, code optimization, AWS, Docker, and workflow orchestrators.