Bioconductor for Genomics

This course will introduce you to the basic data structures and genomic data analysis in Bioconductor. Specifically, we will focus on the basics of RNAseq analysis, including differential expression, annotation, and gene set analysis. We will also focus on loading data and metadata into data structures such as SummarizedExperiment. By the end of this course, you should be familiar with a basic RNAseq analysis workflow utilizing RNAseq count data.

Please note that this course requires the Intro to R course as a prerequisite, or the equivalent course. Please note that this course does not cover RNAseq workflows such as MultiQC and alignment.

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Class information

  • Dates: Spring 2026: April 28, May 5, 12, 19, 26, June 2

  • Time: Tuesdays Noon - 1:30 pm PT

  • Time commitment: 6 weeks of 1.5 hour classes and 1-2 hours of practice outside class.

  • Audience: FH Research Staff wanting to use Bioconductor to analyze RNA-seq data

  • Prerequisites: Intro to R

  • Followed by: None

Learning Objectives (LOs)

  • Explain and Utilize Bioconductor data structures such as SummarizedExperiment to integrate metadata and assay data in your analysis

  • Explore, QC, and clean a RNAseq dataset

  • Utilize Differential Expression analysis on an RNAseq dataset using Bioconductor Packages

  • Identify and Annotate Gene Sets for downstream analysis

  • Load data from RNAseq experiments into Bioconductor

Frequently Asked Questions

  • How often is this class taught?

    This class is offered twice a year (currently fall and spring quarters). Check the schedule to see when it will next be offered.

  • Can I work through the materials without taking the class?

    Yes, you can access the course materials on your own any time.

  • Can I get a badge without taking the class?

    You need to complete the live class to get a badge.

  • Can I take the class if I’m not an employee at Fred Hutch?

    The class is open to members of the Cancer Consortium including Fred Hutch, the University of Washington, and Seattle Children’s Hospital.

  • Can I take more than one class at once?

    You can, but we recommend you don’t mix R and Python at the same time, because it can be confusing to switch between the two.

  • Can I take this class more than once?

    You can sign up more than once, but be aware that there is tyspically a waitlist. We will prioritize students who have not taken the class. If there is room you are welcome to take it again.