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Bioinformatics Workshop Series - Session 4 - Manipulate DESeq2’s results() and plot functions

Bioinformatics Workshop Series - Session 4 - Manipulate DESeq2’s results() and plot functions In-Person

Registration Required

Workshop Series: Introduction to bulk RNA-seq analysis - from counts to functional analysis 

Summary:

The Bioinformatics Support Hub has designed this hands-on teaching series for researchers interested in learning the basic steps for re-analysis of publicly available bulk-RNAseq data. Over the next two months, you can learn basic concepts concerning genomic data annotation and vocabulary, where to find bulk RNAseq data to re-analyze, how to perform differential gene analysis in RStudio and with point-click proprietary software, how to visualize your results, how to find transcription factors that may be regulating differentially expressed genes, and finally different approaches to perform gene pathway analysis. *Registrations for October sessions will open at the end of September.

Session 4. Manipulate DESeq2’s results() and plot functions

Join us for the thrisd part on how to run a differential gene expression analysis with *DESeq2.

This session will focus on how to extract results when your study has more than two groups and how to use the basic plots available in DESeq2 package to visualize your data.

Be advised that in this session we will not cover how to import data into RStudio and setup a differential gene expression analysis with the R package DESeq2, which was the focus of the previous session.     

You will learn how to:

  • Use *DESeq2* function *resultsNames()* to retrieve the different comparisons that were setup in DESeq2 analysis design
  • Use the argument *contrast = * within the function *results()* to retrieve the results of comparisons between specific groups in a study with 4 groups
  • Use functions *plotPCA()*, *MAplot()* and *plot()* as basic tools to visualize data analyzed with DESeq2 package.

Requirements:

Details:

Target audience: These classes are meant to novices in bulk RNAseq analysis, with none to minimal knowledge in R programming.

Seating – in person classes are limited to 16 places.

Registrations - open to all interested. However, seating will be on “first come, first served” basis.

Recording – we will record the sessions so you can follow asynchronously.

Series Program:

Date

Session

Mode

Presenter

9/14/23

Session 1 - Intro to annotation of gene expression data 

In-person

Rolando Milian

9/21/23

Session 2 - Find, Download and Transform public bulk RNA seq data to analyze with DESeq2 in RStudio

In-person

Sofia Fertuzinhos

9/28/23

Session 3 - Upload bulk RNAseq data tables into RStudio and setup a DESeq2 analysis

In-person

Sofia Fertuzinhos

10/5/23

Session 4 - Manipulate DESeq2’s results() and plot functions

In-person

Sofia Fertuzinhos

10/12/23

Session 5 – DEMO - Analyzing and Visualizing RNAseq public dataset using Qlucore Omics Explorer

Online

Yana Stackpole - Qlucore

10/19/23

Session 6 – DEMO - Transcription factors analysis with TRANSFAC

Online

Volker – Transfac

10/24/23

Session 7 - Functional analysis of omics data: Overrepresentation Analysis ORA 

In-person

Rolando Milian

10/26/23

Session 8 - Gene Set Enrichment Analysis GSEA 

In-person

Rolando Milian

 

Date:
Thursday, October 5, 2023
Time:
10:00am - 12:00pm
Time Zone:
Eastern Time - US & Canada (change)
Location:
SHM L 111, Cushing/Whitney Medical Library, 333 Cedar Street
Campus:
Medical School
Categories:
  Bioinformatics  
Registration has closed.

Event Organizer

Profile photo of Rolando Garcia-Milian
Rolando Garcia-Milian
Profile photo of Sofia Fertuzinhos
Sofia Fertuzinhos