Agenda for the Bioconductor 3.12 workshops at Harvard
Authors: Vince Carey, Another Author.
Last modified: 1 Nov, 2020.
Overview
Description
This document is a technical illustration of how workshop documents are authored and rendered. The content of this document will change completely as the workshop content is specified.
Pre-requisites
- Basic knowledge of R syntax
- Familiarity with Rstudio
- Basic understanding of modern genomics. For example, the distinction between whole genome sequencing and RNA-seq should be clear.
- Basic familiarity with the concepts of statistical analysis, such as the definition of the t-test for comparing sample means, the interpretation of histograms. An understanding of experimental design is helpful.
- Readings:
Participation
Describe how students will be expected to participate in the workshop.
R / Bioconductor packages used
List any R / Bioconductor packages that will be explicitly covered.
Time outline
An example for a 45-minute workshop:
| Brief intro to R/Rstudio |
10m |
| Biological context |
10m |
| Packages to be used |
10m |
| Analytical approach to the question |
15m |
| Simple exercises |
10m |
| Review |
5m |
Workshop goals and objectives
List “big picture” student-centered workshop goals and learning objectives. Learning goals and objectives are related, but not the same thing. These goals and objectives will help some people to decide whether to attend the conference for training purposes, so please make these as precise and accurate as possible.
Learning goals are high-level descriptions of what participants will learn and be able to do after the workshop is over. Learning objectives, on the other hand, describe in very specific and measurable terms specific skills or knowledge attained. The Bloom’s Taxonomy may be a useful framework for defining and describing your goals and objectives, although there are others.
Learning goals
Some examples:
- describe how to…
- identify methods for…
- understand the difference between…
Learning objectives
- analyze xyz data to produce…
- create xyz plots
- evaluate xyz data for artifacts
Workshop
Divide the workshop into sections (## A Section). Include fully-evaluated R code chunks. Develop exercises and solutions, and anticipate that your audience will walk through the code with you, or work on the code idependently – do not be too ambitious in the material that you present.