Intermediate RNA Seq Analysis Using R

Description

The learning objectives for this workshop include: 1) How to go from a matrix of raw gene expression counts to differentially expressed genes. 2) How to analyze experimental designs that go beyond 2-group comparisons using edgeR’s generalized linear modeling capabilities. 3) Ways to test specific hypotheses using a joint model fit. Prerequisites: A minimum of 4 to 6 months experience programming in R and have taken the RNAseq Analysis in R workshop or something equivalent.

Learning Path

   This is an intermediate workshop in the RNA-Seq Analysis series. Prior experience with R and pre-processing of RNA-Seq data is required. See introductory workshop:

• Introduction to RNA-Seq Analysis

Materials

Click here to download the materials and the slides.

Pre-workshop Instructions

Before the workshop, please make sure that you have R and RStudio installed on your laptops. Please also install the statmod, edgeR, tidyverse, magrittr, org.Mm.eg.db and ggplot2 packages in R.

Online Learning

1. Refer to this tutorial article by Chen et al. for a step-by-guide.

2. Check out the RNA-Seq Analysis with R Bioconductor module in the UCSF library's Collaborative Learning Environment.