Informatics for RNA-seq Analysis
High-throughput sequencing of RNA libraries (RNA-seq) has become increasingly common and largely supplanted gene microarrays for transcriptome profiling. When processed appropriately, RNA-seq data has the potential to provide a considerably more detailed view of the transcriptome. The CBW has developed a 3-day course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages. The tutorials are designed as self-contained units that include example data (Illumina paired-end RNA-seq data) and detailed instructions for installation of all required bioinformatics tools (HISAT, StringTie, etc.).
Participants will gain practical experience and skills to be able to:
- Perform command-line Linux based analysis on the cloud
- Assess quality of RNA-seq data
- Align RNA-seq data to a reference genome
- Estimate known gene and transcript expression
- Perform differential expression analysis
- Discover novel isoforms
- Visualize and summarize the output of RNA-seq analyses in R
- Assemble transcripts from RNA-Seq data.
Graduates, postgraduates, and PIs working or about to embark on an analysis of RNA-seq data. Attendees may be familiar with some aspect of RNA-seq analysis (e.g. gene expression analysis) or have no direct experience.
Prerequisites: Basic familiarity with Linux environment and S, R, or Matlab. Must be able to complete and understand the following simple Linux and R tutorials (up to and including “Descriptive Statistics”) before attending:
- UNIX Tutorial (up to and including Tutorial Four) [http://www.ee.surrey.ac.uk/Teaching/Unix/]
- Quick & Dirty Guide to R [http://ww2.coastal.edu/kingw/statistics/R-tutorials/text/quick&dirty_R.txt]
You will also require your own laptop computer. Minimum requirements: 1024x768 screen resolution, 1.5GHz CPU, 2GB RAM, 10GB free disk space, recent versions of Windows, Mac OS X or Linux (Most computers purchased in the past 3-4 years likely meet these requirements). If you do not have access to your own computer, you may loan one from the CBW. Please contact email@example.com for more information.
Pre-work and pre-readings can be found at https://bioinformaticsdotca.github.io/rnaseq_2018.
Module 1: Introduction to Cloud Computing (Obi Griffith)
Module 2: Introduction to RNA sequencing and analysis (Malachi Griffith)
Module 3: RNA-Seq alignment and visualization (Fouad Yousif)
Module 4: Expression and differential expression (Obi Griffith)
Module 5: Reference free alignment (Malachi Griffith)
Module 6: Genome Guided and Genome-Free Transcriptome Assembly (Brian Haas)
Module 7: Functional Annotation and Analysis of Transcripts (Brian Haas)