Incubator Lesson Spotlight: Analysis and Interpretation of Bulk RNA-Seq Data using Bioconductor

Tue, 13 Jul 2021 00:00:00 +0000

The Incubator Lesson Spotlight highlights a lesson under development by our community in The Carpentries Incubator. In this edition, we look at the progress being made on the {{page.lesson_title}} lesson, and hear from the authors about how The Carpentries community can get involved with the ongoing development of this lesson.

Lesson Profile

Title: {{page.lesson_title}}
Lesson Pages: https://carpentries-incubator.github.io/bioc-rnaseq
Lesson Repository: https://github.com/carpentries-incubator/bioc-rnaseq

Learning Objectives

After following this lesson, learners will be able to:

choose an appropriate design for a bulk RNA Sequencing experiment.
import and annotate quantified RNA-Seq data in R.
assess the quality of experimental results represented as a gene expression matrix.
run a standard differential expression analysis and interpret the output.
execute a gene set analysis.

Target Audience

This lesson is aimed at researchers who are already aware of what Bioconductor is and how it can benefit their data analysis. They are comfortable with basic operations in R, such as creating numeric, character vector, and data frame variables, installing and loading packages from CRAN and Bioconductor, and visualising data in common formats such as bar and scatter plots. These researchers want to learn how to use R and Bioconductor to explore and analyse data produced in bulk RNA sequencing experiments, and visualise and interpret the results of these analyses.

Robert Castelo on The Carpentries

Incubator Lesson Spotlight: Analysis and Interpretation of Bulk RNA-Seq Data using Bioconductor

Lesson Profile

Learning Objectives

Target Audience