Introduction to bulk RNA-seq (Part II)

(Differential Gene Expression and Functional analysis) 


Note: Until further notice, workshops will be taught online via Zoom. However, we anticipate returning to in-person teaching in 2022.

Next workshop dates and times:

Friday, May 6th : 10 AM - 12 PM

Tuesday, May 10th : 10 AM - 12 PM

Friday, May 13th 10 AM - 12 PM

Tuesday, May 17th 10 AM - 12 PM

Instruction for this workshop will be mostly learner-centric requiring workshop participants to spend between 3-5 hours on reading and exercises from selected lessons before the workshop sessions. Online and in-person classes will be focused on exercises and discussion. Please make sure you take this into account when you sign up for the workshop!

Description:

This hands-on workshop will introduce participants to statistical methods and considerations utilized to perform differential gene expression analysis on bulk RNA-seq data. Participants will learn about best practices in quality control, how to perform statistical analysis to obtain lists of differentially expressed (DE) genes using DESeq2. The workshop will also give participants an overview of tools for functional analysis of DE genes and how to extract some biological meaning from large gene lists.


** Please note that this workshop does NOT cover single-cell RNA-seq analysis. **

** Please note that you DO NOT need to attend Part I to attend this workshop, all you need is R fluency.

Prerequisites:

This is one of our advanced workshops, and requires registrants to have attended the following basic workshop offered by our training team within the last 6 months:

Prerequisite FAQI am fluent in R but have not attended the HBC prerequisite workshop, can I still register?

Yes, you can register but please do the following:

Who should attend?

Eligible* Harvard researchers who have attended our Introduction to R workshop (or have working knowledge of R), and want to learn: 

  1. How to perform a differential expression analysis at the gene-level
  2. How to effectively use R to get your data in the appropriate format for DE analysis
  3. The steps and statistical approaches used in assessing the quality of your abundance estimates (count data)
  4. How to visualize expression patterns for differentially expressed genes
  5. How to perform functional analysis on gene lists with R-based tools

Cost and Registration:

There is a non-refundable and non-transferable $50 registration fee for this online workshop. 

We will be accepting 35-45 participants on a first-come, first-served basis:

NOTE: You will not have a reserved seat for this workshop until you pay the registration fee. Please make sure you pay within the time stated in that email, else you will lose your spot to someone on the waitlist. 

Eligibility requirements:

To be eligible to attend this workshop you should fulfill at least one of the following criteria:

If you are unsure of your eligibility, please register anyways and we will get back to you.

Registration is closed

(Registration will open 3 weeks prior to first day of the workshop)

NOTE: We do * not * record our training sessions. 

Questions?

Please contact us at hbctraining@hsph.harvard.edu with any questions.