BIOS6660


Analysis of Genomics Data Using R and Bioconductor

Week 1 - Jan 22 - Course Overview

Course Overview and logistics
Go to Slide
Syllabus

Week 2 - Jan 27 & 29 - RStudio and R Primer

Jan 27 Learning Objective

  • Getting familiar with the RStudio software environment


Go to Slide

Jan 29 Learning Objectives

  • Feature Resoures: Guerilla Guild to R
  • Review what you learned from Roger Peng R tutorial video
  • Hands On: "We BLATted the internet"
  • Create RStudio Project
  • Style guide


Go to Slide

Week 3 - Feb 3 & Feb 5 - Programming and Plotting: Part 1

Feb 3 Learning Objectives


Go to Slide


Student contribute resources:

Week 4 - Feb 10 & Feb 12 - Programming and Plotting: Part 2

Feb 10 Learning Objectives

    • Regular Expression
    • Debugging in R
  • Hands On: Visual debugging in RStudio


Go to Slide

Feb 12 Learning Objectives

    • Reproducible Research
    • The 'knitr' package
  • Hands On: Generate Report


Go to Slide

Week 5- Feb 19 Bioconductor and Storage Solution

Learning Objectives

    • Bioconductor Storage Solution


Go to Slide

Week 6 & 7 Microarray Analysis

Day1 Feb 24: Learning Objectives

  • Case Study: Robert Stearman
    • Application to Pulmonary Arterial Hypertension
  • How Bioconductor handles microarray data


Go to Slide
Go to PowerPoint file

Day 2 Feb 26: Learning Objectives

  • Microarray Analysis using "EMA" package


Go to Slide

Day 3 Mar 3: Learning Objectives

  • Trouble Shooting Case 1 Microarray Data Analysis


Go to Slide

Day 4 Mar 5: Learning Objectives


Go to Slide

Week 8 & 9 RNA-seq

Day1 March 10: Learning Objectives

  • Case Study: Dr. Eric Schmidt
    • Using RNA sequencing to investigate pulmonary endothelial glycocalyx recovery after sepsis
  • Using Bioconductor for RNA-seq data analysis


Go to Slide
Go to PowerPoint file
Go to supplementary file
Thomas Girke Sample RNA-seq analysis PDF

Day 2 March 12: Learning Objectives

  • RNAseq analysis: Thomas Girke lesson


Go to Slide

Day 3 Mar 17: Learning Objectives

  • Trouble Shooting Case 2 RNA-seq Data Analysis


Go to Slide

Day 4 Mar 19: Learning Objectives
Go to Slide

Week 10 & 11 ChIP-seq

Day1 March 31: Learning Objectives

  • Case Study: Dr. David Bentley
    • ChIP-seq a match made in heaven: Chromatin Immunoprecipitation and Deep Sequencing
  • Using Bioconductor for ChIP-seq data analysis


Go to Slide
Go to PowerPoint file

Day 2 April 2: Learning Objectives

  • ChIP-seq analysis: Thomas Girke lesson


Go to Slide

Day 3 April 7: Learning Objectives

  • Trouble Shooting Case 3 ChIP-seq Data Analysis


Go to Slide

Day 4 April 9: Learning Objectives
Go to Slide

Week 12 & 13 shRNA-seq

Day1 April 14: Learning Objectives

  • Case Study: Dr. Mark Gregory
    • Large-scale shRNA screens to identify novel combination therapies for the treatment of cancer


Go to Slide
Go to PowerPoint file

Day 2 April 16: Learning Objectives


Go to PowerPoint file

Day 3 April 21: Learning Objectives

  • Trouble Shooting Case 4 shRNA-seq Data Analysis


Go to Slide

Day 4 April 23: Learning Objectives
Go to Slide

Week 14 & 15 Exome-seq Analysis

Day 2 April 30: Learning Objectives


Go to PowerPoint file

Day 3 April 21: Learning Objectives

  • Trouble Shooting Case 4 Exome-seq Data Analysis


Go to Slide

Day 4 April 23: Learning Objectives
Go to Slide