Building Carpentries-based Bioconductor Lessons

Jenny Drnevich1

Building Carpentries-based Bioconductor Lessons

Authors: Jenny Drnevich2, Charlotte Soneson3, Toby Hodges4, Laurent Gatto5.
Last modified: 15 Mar 2021.



The Bioconductor teaching committee was established in early 2020, and one of its aims is to coordinate the development of Bioconductor-focused training material, consistent with the guiding principles of the Carpentries ( During its first year, the committee has started the development of three lessons: an introduction to R (with a Bioconductor focus), an overview of the Bioconductor project, and a lesson on bulk RNA-seq analysis with Bioconductor. In this workshop, we would like to raise awareness of the existing lessons within the Bioconductor community, and invite contributions from interested community members. We will start by giving an overview of the Carpentries guiding principles and the procedures for proposing and developing a Bioconductor lesson. After that, we will invite participants to actively engage with and contribute to the existing material, as well as form new working groups for development of additional lessons.


Essential pre-requisites:

  • Basic knowledge of R syntax
  • An interest in teaching R to others

Suggested pre-requisites:

  • Basic knowledge of git
  • Basic knowledge of Rmarkdown

Background reading:


Attendees are interested in learning about the Carpentries’ guiding principles on the science of learning and how to apply them in their own teaching. They will review existing workshop material from the Bioconductor teaching committee and participate in a “lesson sprint”: contribute ideas, suggestions for improvement, evaluation tests, etc. They will also have the opportunity to suggest other lessons and network with others to hopefully form groups to develop these lessons in the future.

R / Bioconductor packages used


Time outline

Activity Time
Carpentries guiding principles 20m
Overview of workshops in development 20m
Lesson sprint 50m
Future lesson planning 20m

Workshop goals and objectives

Learning goals

  • Describe the backwards design instructional model and how it influences the development of course content.
  • Assess the Introduction to R workshop being developed by the Bioconductor teaching committee and provide feedback whether the lesson design fulfills the stated learning objectives.
  • Understand how to create meaningful assessment exercises to test whether learners have learned a particular skill or concept or what misconceptions they still have.
  • Form collaborative groups for future lesson development.

Learning objectives

  • Identify the target audience and learning objectives of the Bioconductor-focused Introduction to R workshop.
  • Modify/edit workshop materials to better obtain the stated learning objectives.
  • Create multiple choice, fill in the blanks, minimal fix, and/or code adaptation exercises to assess specific knowledge gained.
  • Network with others interested in teaching R/Bioconductor workshops.


Carpentries guiding principles

Overview of workshops in development

An introduction to R

Target audience: At least a mid-level Bachelor student with basic biology knowledge. They have or will have some type of -omic data they will need to analyze and visualize but possibly no prior experience in programming or data analysis.

Data set: subset of BachMammaryData

Learning objectives:

  • Be able to organize data in a spreadsheet in a manner conducive to reading into R
  • Know how to check for and correct common data entry errors (e.g., inconsistent capitalizations, naming conventions, non-allowed characters, etc.)
  • Import data into R and put in a proper object class
  • Produce visual summaries of the data

Introduction to R curricula: Lesson: Data organization and management Lesson: Data import and cleaning Lesson: Data manipulation and visualization

Overview of the Bioconductor project

Target audience: At least a mid-level Bachelor student with basic biology knowledge. They have or will have some type of -omic data they will need to analyze and visualize, and have the obtained the learning objectives of the Introduction to R workshop. They want to learn how to do the analysis themselves but do not know how to start or what software packages are available.

Data set: ?

Learning objectives:

  • Navigate the Bioconductor website and learn to how to find packages for particular types of -omics data
  • Install specific Bioconductor packages in R
  • Open a package vignette a practice running through the example
  • Name the different types of Bioconductor S4 object types and what kind of data they hold.
  • Modify code

Bulk RNA-seq analysis

Target audience: At least a graduate student basic biology knowledge. They have or will have bulk RNA-Seq count data they need to analyze and visualize. They are already familiar with R, RStudio and Bioconductor.

Data set: ?

Learning objectives:

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