The Practical Genomics workshop provides hands-on training in computational analysis of modern genomics datasets.  This series focuses on making technologies accessible to biologists of all experience levels, including undergraduates, graduate students, postdoctoral fellows, faculty and staff.  This workshop runs for two weeks, with two full days of instruction each week, providing many opportunities to learn about the latest genomic technologies and how to use them to answer biological questions.

• Oct 30 & 31 — Introduce participants with little to no prior computational experience to the basics of data transformation and visualization using cloud computing, R/RStudio, tidyverse and Bioconductor. These two days also cover how to load and clean data, perform basic exploratory data analyses and create visualizations. By the end of these two days, participants will be able to use these tools to analyze and visualize data in a variety of fields, including biology and medicine.

• Nov 6 & 7 — Introduce participants to the basics of single cell analysis, including dimension reduction, clustering and marker gene detection. Subsequent topics include cell annotation, differential gene expression, and gene set analysis, all of which will be covered using Bioconductor frameworks.

Participants are required to complete approximately one day of preparatory work to create the appropriate cloud computing accounts and familiarize themselves with R and RStudio console. This work is essential as all sessions incorporate hands-on live coding demos where learners code-along with instructors, and breakout exercises where learners practice with the support of TAs.

Due to this hands-on design, recordings will not be available, but all instructional materials will be usable after the workshop.