Day 3 - RNA-Seq Analysis
Day 3 - RNA-Seq Analysis
Keywords
QC, Exploratory-analysis, Differential-expression, Statistical-model, Pre-processing
Authors
- Jenny Drnevich @jenny
- Radhika Khetani @radhika
- Jessica Kirkpatrick krkptrc2@illinois.edu
Type
- Both
Description
Day 3 focuses on statistical analysis of RNA-Seq data and identification of differentiall expressed genes in multiple comparisons.
Aims
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.
Prerequisites
- 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.
Materials
- Review of Day 2 & R practice
- Lecture on Statistical Analysis
- Lecture on Venn Diagrams
Data
- Data for Day 2 review
- All data needed to run Day 3 practicals
Timing
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
Activity log