Day 3 - RNA-Seq Analysis

Day 3 - RNA-Seq Analysis


QC, Exploratory-analysis, Differential-expression, Statistical-model, Pre-processing



  • Both


Day 3 focuses on statistical analysis of RNA-Seq data and identification of differentiall expressed genes in multiple comparisons.


This day covers in detail the theory of stastical modeling, in general and for count data, plus how to properly specify the model design and pull desired contrasts from the model and do venn diagrams of overlaps between significant gene lists.


  • Basic knowledge of R
  • All the information in Day 1 and Day 2, but not the practical outputs

Target audience

Graduates students/post docs/beginning faculty

Learning objectives

  • Be able to describe the basic formulation of a statistical test
  • Be able to specify the proper statistical model for a 2x2 factorial design and pull out pairwise contrasts and the interaction.
  • Be able to follow and modify R scripts for statistical analysis and venn diagrams.


  • Review of Day 2 & R practice
  • Lecture on Statistical Analysis
  • Lecture on Venn Diagrams


  • Data for Day 2 review
  • All data needed to run Day 3 practicals


6 hours contact time; practicals intersperced with lectures; easily can fit into 1 day + lunch and breaks

Content stability

Should be stable

Technical requirements

  • R >= 3.1.3 on any OS plus Bioconductor packages edgeR, limma, affycoretools and WGCNA

Literature references

Keywords: QC, Exploratory-analysis, Differential-expression, Statistical-model, Pre-processing

Additional information

Authors: Jenny Drnevich @jenny, Radhika Khetani @radhika, Jessica Kirkpatrick